diff --git a/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala b/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
index 3800dca..b22bd74 100644
--- a/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
+++ b/connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
@@ -168,7 +168,7 @@
 
   test("reading from multiple paths") {
     val df = spark.read.format("avro").load(episodesAvro, episodesAvro)
-    assert(df.count == 16)
+    assert(df.count() == 16)
   }
 
   test("reading and writing partitioned data") {
@@ -197,7 +197,7 @@
     withTempPath { dir =>
       val df = spark.read.format("avro").load(episodesAvro)
       df.write.parquet(dir.getCanonicalPath)
-      assert(spark.read.parquet(dir.getCanonicalPath).count() === df.count)
+      assert(spark.read.parquet(dir.getCanonicalPath).count() === df.count())
     }
   }
 
@@ -549,7 +549,7 @@
         Row(null, null, null, null, null)))
       val df = spark.createDataFrame(rdd, schema)
       df.write.format("avro").save(dir.toString)
-      assert(spark.read.format("avro").load(dir.toString).count == rdd.count)
+      assert(spark.read.format("avro").load(dir.toString).count() == rdd.count())
     }
   }
 
@@ -568,7 +568,7 @@
       ))
       val df = spark.createDataFrame(rdd, schema)
       df.write.format("avro").save(dir.toString)
-      assert(spark.read.format("avro").load(dir.toString).count == rdd.count)
+      assert(spark.read.format("avro").load(dir.toString).count() == rdd.count())
     }
   }
 
@@ -628,7 +628,7 @@
         ))
         val df = spark.createDataFrame(rdd, schema)
         df.write.format("avro").save(dir.toString)
-        assert(spark.read.format("avro").load(dir.toString).count == rdd.count)
+        assert(spark.read.format("avro").load(dir.toString).count() == rdd.count())
         checkAnswer(
           spark.read.format("avro").load(dir.toString).select("date"),
           Seq(Row(null), Row(new Date(1451865600000L)), Row(new Date(1459987200000L))))
@@ -666,7 +666,7 @@
           Array[Row](Row("Bobby G. can't swim")))))
       val df = spark.createDataFrame(rdd, testSchema)
       df.write.format("avro").save(dir.toString)
-      assert(spark.read.format("avro").load(dir.toString).count == rdd.count)
+      assert(spark.read.format("avro").load(dir.toString).count() == rdd.count())
     }
   }
 
@@ -1021,7 +1021,7 @@
       val currentDate = new Date(System.currentTimeMillis())
       val schema = StructType(Seq(
         StructField("_1", DateType, false), StructField("_2", TimestampType, false)))
-      val writeDs = Seq((currentDate, currentTime)).toDS
+      val writeDs = Seq((currentDate, currentTime)).toDS()
 
       val avroDir = tempDir + "/avro"
       writeDs.write.format("avro").save(avroDir)
@@ -1050,12 +1050,12 @@
         StructField("_1", DateType, nullable = true),
         StructField("_2", TimestampType, nullable = true))
       )
-      val writeDs = Seq((nullDate, nullTime)).toDS
+      val writeDs = Seq((nullDate, nullTime)).toDS()
 
       val avroDir = tempDir + "/avro"
       writeDs.write.format("avro").save(avroDir)
       val readValues =
-        spark.read.schema(schema).format("avro").load(avroDir).as[(Date, Timestamp)].collect
+        spark.read.schema(schema).format("avro").load(avroDir).as[(Date, Timestamp)].collect()
 
       assert(readValues.size == 1)
       assert(readValues.head == ((nullDate, nullTime)))
@@ -1147,7 +1147,7 @@
     val result = spark
       .read
       .option("avroSchema", avroSchema)
-      .format("avro").load(testAvro).select("missingField").first
+      .format("avro").load(testAvro).select("missingField").first()
     assert(result === Row("foo"))
   }
 
@@ -1743,13 +1743,13 @@
     // Test if load works as expected
     withTempPath { tempDir =>
       val df = spark.read.format("avro").load(episodesAvro)
-      assert(df.count == 8)
+      assert(df.count() == 8)
 
       val tempSaveDir = s"$tempDir/save/"
 
       df.write.format("avro").save(tempSaveDir)
       val newDf = spark.read.format("avro").load(tempSaveDir)
-      assert(newDf.count == 8)
+      assert(newDf.count() == 8)
     }
   }
 
@@ -1757,7 +1757,7 @@
     // Test if load works as expected
     withTempPath { tempDir =>
       val df = spark.read.format("avro").load(episodesAvro)
-      assert(df.count == 8)
+      assert(df.count() == 8)
 
       val tempSaveDir = s"$tempDir/save/"
       df.write.format("avro").save(tempSaveDir)
@@ -1928,11 +1928,11 @@
 
   test("read avro file partitioned") {
     withTempPath { dir =>
-      val df = (0 to 1024 * 3).toDS.map(i => s"record${i}").toDF("records")
+      val df = (0 to 1024 * 3).toDS().map(i => s"record${i}").toDF("records")
       val outputDir = s"$dir/${UUID.randomUUID}"
       df.write.format("avro").save(outputDir)
       val input = spark.read.format("avro").load(outputDir)
-      assert(input.collect.toSet.size === 1024 * 3 + 1)
+      assert(input.collect().toSet.size === 1024 * 3 + 1)
       assert(input.rdd.partitions.size > 2)
     }
   }
@@ -2057,21 +2057,21 @@
 
       val fileWithoutExtension = s"${dir.getCanonicalPath}/episodes"
       val df1 = spark.read.format("avro").load(fileWithoutExtension)
-      assert(df1.count == 8)
+      assert(df1.count() == 8)
 
       val schema = new StructType()
         .add("title", StringType)
         .add("air_date", StringType)
         .add("doctor", IntegerType)
       val df2 = spark.read.schema(schema).format("avro").load(fileWithoutExtension)
-      assert(df2.count == 8)
+      assert(df2.count() == 8)
     }
   }
 
   test("SPARK-24836: checking the ignoreExtension option") {
     withTempPath { tempDir =>
       val df = spark.read.format("avro").load(episodesAvro)
-      assert(df.count == 8)
+      assert(df.count() == 8)
 
       val tempSaveDir = s"$tempDir/save/"
       df.write.format("avro").save(tempSaveDir)
@@ -2084,7 +2084,7 @@
         .format("avro")
         .load(tempSaveDir)
 
-      assert(newDf.count == 8)
+      assert(newDf.count() == 8)
     }
   }
 
diff --git a/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroReadBenchmark.scala b/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroReadBenchmark.scala
index aa0d713..80f0d6b 100644
--- a/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroReadBenchmark.scala
+++ b/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroReadBenchmark.scala
@@ -64,7 +64,7 @@
     withTempPath { dir =>
       withTempTable("t1", "avroTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql(s"SELECT CAST(value as ${dataType.sql}) id FROM t1"))
 
@@ -83,7 +83,7 @@
     withTempPath { dir =>
       withTempTable("t1", "avroTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(
           dir,
@@ -104,7 +104,7 @@
     withTempPath { dir =>
       withTempTable("t1", "avroTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT value % 2 AS p, value AS id FROM t1"), Some("p"))
 
@@ -177,7 +177,7 @@
         import spark.implicits._
         val middle = width / 2
         val selectExpr = (1 to width).map(i => s"value as c$i")
-        spark.range(values).map(_ => Random.nextLong).toDF()
+        spark.range(values).map(_ => Random.nextLong()).toDF()
           .selectExpr(selectExpr: _*).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT * FROM t1"))
@@ -200,7 +200,7 @@
         import spark.implicits._
         val middle = width / 2
         val selectExpr = (1 to width).map(i => s"value as c$i")
-        spark.range(values).map(_ => Random.nextLong).toDF()
+        spark.range(values).map(_ => Random.nextLong()).toDF()
           .selectExpr(selectExpr: _*)
           .repartition(files) // ensure at least `files` number of splits (but maybe more)
           .createOrReplaceTempView("t1")
diff --git a/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroWriteBenchmark.scala b/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroWriteBenchmark.scala
index d1db290..e61ac43 100644
--- a/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroWriteBenchmark.scala
+++ b/connector/avro/src/test/scala/org/apache/spark/sql/execution/benchmark/AvroWriteBenchmark.scala
@@ -47,7 +47,7 @@
         val selectExpr = (1 to width).map(i => s"value as c$i")
         // repartition to ensure we will write multiple files
         val df = spark.range(values)
-          .map(_ => Random.nextInt).selectExpr(selectExpr: _*).repartition(files)
+          .map(_ => Random.nextInt()).selectExpr(selectExpr: _*).repartition(files)
           .persist(StorageLevel.DISK_ONLY)
         // cache the data to ensure we are not benchmarking range or repartition
         df.noop()
@@ -55,7 +55,7 @@
         val benchmark = new Benchmark(s"Write wide rows into $files files", values, output = output)
         benchmark.addCase("Write wide rows") { _ =>
           spark.sql("SELECT * FROM t1").
-            write.format("avro").save(s"${dir.getCanonicalPath}/${Random.nextLong.abs}")
+            write.format("avro").save(s"${dir.getCanonicalPath}/${Random.nextLong().abs}")
         }
         benchmark.run()
       }
diff --git a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ClientE2ETestSuite.scala b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ClientE2ETestSuite.scala
index 04d284f..d9a77f2 100644
--- a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ClientE2ETestSuite.scala
+++ b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ClientE2ETestSuite.scala
@@ -63,7 +63,7 @@
         })
 
       val ex = intercept[SparkException] {
-        Seq("1").toDS.withColumn("udf_val", throwException($"value")).collect()
+        Seq("1").toDS().withColumn("udf_val", throwException($"value")).collect()
       }
 
       assert(ex.getCause.isInstanceOf[SparkException])
@@ -103,7 +103,7 @@
         udf((_: String) => throw new SparkException("test" * 10000))
 
       val ex = intercept[SparkException] {
-        Seq("1").toDS.withColumn("udf_val", throwException($"value")).collect()
+        Seq("1").toDS().withColumn("udf_val", throwException($"value")).collect()
       }
 
       assert(ex.getErrorClass != null)
@@ -1011,9 +1011,9 @@
     assert(df1.sameSemantics(df3) === false)
     assert(df3.sameSemantics(df4) === true)
 
-    assert(df1.semanticHash === df2.semanticHash)
-    assert(df1.semanticHash !== df3.semanticHash)
-    assert(df3.semanticHash === df4.semanticHash)
+    assert(df1.semanticHash() === df2.semanticHash())
+    assert(df1.semanticHash() !== df3.semanticHash())
+    assert(df3.semanticHash() === df4.semanticHash())
   }
 
   test("toJSON") {
@@ -1414,7 +1414,7 @@
     val r4 = uuid()
     val r5 = shuffle(col("a"))
     df.select(r, r.as("r"), r2, r2.as("r2"), r3, r3.as("r3"), r4, r4.as("r4"), r5, r5.as("r5"))
-      .collect
+      .collect()
       .foreach { row =>
         (0 until 5).foreach(i => assert(row.get(i * 2) === row.get(i * 2 + 1)))
       }
diff --git a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionSuite.scala b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionSuite.scala
index ef1cf78..b77e929 100644
--- a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionSuite.scala
+++ b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionSuite.scala
@@ -293,7 +293,7 @@
     val df = createDFWithNestedColumns
 
     // Rows with the specified nested columns whose null values are dropped.
-    assert(df.count == 3)
+    assert(df.count() == 3)
     checkAnswer(df.na.drop("any", Seq("c1.c1-1")), Seq(Row(Row("b1", "b2"))))
   }
 
diff --git a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala
index 609fad5..bd0aabc 100644
--- a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala
+++ b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala
@@ -340,7 +340,7 @@
       assert(kvgds == null)
       i + 1
     }
-    val result = df.select(f($"id")).as[Long].head
+    val result = df.select(f($"id")).as[Long].head()
     assert(result == 1L)
   }
 }
diff --git a/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/ArtifactManager.scala b/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/ArtifactManager.scala
index 2f8eacb..7401164 100644
--- a/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/ArtifactManager.scala
+++ b/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/ArtifactManager.scala
@@ -171,7 +171,7 @@
       return
     }
 
-    val promise = Promise[Seq[ArtifactSummary]]
+    val promise = Promise[Seq[ArtifactSummary]]()
     val responseHandler = new StreamObserver[proto.AddArtifactsResponse] {
       private val summaries = mutable.Buffer.empty[ArtifactSummary]
       override def onNext(v: AddArtifactsResponse): Unit = {
diff --git a/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/GrpcRetryHandler.scala b/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/GrpcRetryHandler.scala
index 74c8423..0f8178c 100644
--- a/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/GrpcRetryHandler.scala
+++ b/connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/GrpcRetryHandler.scala
@@ -75,7 +75,7 @@
     }
 
     override def next(): U = {
-      retryIter(_.next)
+      retryIter(_.next())
     }
 
     override def hasNext: Boolean = {
diff --git a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/ExecuteResponseObserver.scala b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/ExecuteResponseObserver.scala
index e99e3a9..3c416bb 100644
--- a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/ExecuteResponseObserver.scala
+++ b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/ExecuteResponseObserver.scala
@@ -183,10 +183,10 @@
       throw new SparkSQLException(
         errorClass = "INVALID_CURSOR.POSITION_NOT_AVAILABLE",
         messageParameters = Map("index" -> index.toString, "responseId" -> responseId))
-    } else if (getLastResponseIndex.exists(index > _)) {
+    } else if (getLastResponseIndex().exists(index > _)) {
       // If index > lastIndex, it's out of bounds. This is an internal error.
       throw new IllegalStateException(
-        s"Cursor position $index is beyond last index $getLastResponseIndex.")
+        s"Cursor position $index is beyond last index ${getLastResponseIndex()}.")
     }
     ret
   }
diff --git a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/SparkConnectPlanExecution.scala b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/SparkConnectPlanExecution.scala
index ddad7da..a3ce813 100644
--- a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/SparkConnectPlanExecution.scala
+++ b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/SparkConnectPlanExecution.scala
@@ -57,7 +57,7 @@
         s"Illegal operation type ${request.getPlan.getOpTypeCase} to be handled here.")
     }
     val planner = new SparkConnectPlanner(executeHolder)
-    val tracker = executeHolder.eventsManager.createQueryPlanningTracker
+    val tracker = executeHolder.eventsManager.createQueryPlanningTracker()
     val dataframe =
       Dataset.ofRows(
         sessionHolder.session,
diff --git a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
index 299f4f8..f5d83b8 100644
--- a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
+++ b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
@@ -2514,7 +2514,7 @@
     val namedArguments = getSqlCommand.getNamedArgumentsMap
     val posArgs = getSqlCommand.getPosArgsList
     val posArguments = getSqlCommand.getPosArgumentsList
-    val tracker = executeHolder.eventsManager.createQueryPlanningTracker
+    val tracker = executeHolder.eventsManager.createQueryPlanningTracker()
     val df = if (!namedArguments.isEmpty) {
       session.sql(
         getSqlCommand.getSql,
@@ -2724,7 +2724,7 @@
       replace = createView.getReplace,
       viewType = viewType)
 
-    val tracker = executeHolder.eventsManager.createQueryPlanningTracker
+    val tracker = executeHolder.eventsManager.createQueryPlanningTracker()
     Dataset.ofRows(session, plan, tracker).queryExecution.commandExecuted
     executeHolder.eventsManager.postFinished()
   }
@@ -2742,7 +2742,7 @@
     // Transform the input plan into the logical plan.
     val plan = transformRelation(writeOperation.getInput)
     // And create a Dataset from the plan.
-    val tracker = executeHolder.eventsManager.createQueryPlanningTracker
+    val tracker = executeHolder.eventsManager.createQueryPlanningTracker()
     val dataset = Dataset.ofRows(session, plan, tracker)
 
     val w = dataset.write
@@ -2814,7 +2814,7 @@
     // Transform the input plan into the logical plan.
     val plan = transformRelation(writeOperation.getInput)
     // And create a Dataset from the plan.
-    val tracker = executeHolder.eventsManager.createQueryPlanningTracker
+    val tracker = executeHolder.eventsManager.createQueryPlanningTracker()
     val dataset = Dataset.ofRows(session, plan, tracker)
 
     val w = dataset.writeTo(table = writeOperation.getTableName)
@@ -2873,7 +2873,7 @@
       writeOp: WriteStreamOperationStart,
       responseObserver: StreamObserver[ExecutePlanResponse]): Unit = {
     val plan = transformRelation(writeOp.getInput)
-    val tracker = executeHolder.eventsManager.createQueryPlanningTracker
+    val tracker = executeHolder.eventsManager.createQueryPlanningTracker()
     val dataset = Dataset.ofRows(session, plan, tracker)
     // Call manually as writeStream does not trigger ReadyForExecution
     tracker.setReadyForExecution()
@@ -3082,7 +3082,7 @@
           val exception_builder = StreamingQueryCommandResult.ExceptionResult
             .newBuilder()
           exception_builder
-            .setExceptionMessage(e.toString)
+            .setExceptionMessage(e.toString())
             .setErrorClass(e.getErrorClass)
 
           val stackTrace = Option(ExceptionUtils.getStackTrace(e))
diff --git a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/ExecuteEventsManager.scala b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/ExecuteEventsManager.scala
index 9e8a945..2430716 100644
--- a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/ExecuteEventsManager.scala
+++ b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/ExecuteEventsManager.scala
@@ -245,7 +245,7 @@
         postAnalyzed(Some(analyzedPlan))
       }
 
-      def readyForExecution(tracker: QueryPlanningTracker): Unit = postReadyForExecution
+      def readyForExecution(tracker: QueryPlanningTracker): Unit = postReadyForExecution()
     }))
   }
 
diff --git a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/SparkConnectServer.scala b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/SparkConnectServer.scala
index fbaa9e0..3b42b58 100644
--- a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/SparkConnectServer.scala
+++ b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/service/SparkConnectServer.scala
@@ -31,7 +31,7 @@
   def main(args: Array[String]): Unit = {
     // Set the active Spark Session, and starts SparkEnv instance (via Spark Context)
     logInfo("Starting Spark session.")
-    val session = SparkSession.builder.getOrCreate()
+    val session = SparkSession.builder().getOrCreate()
     try {
       try {
         SparkConnectService.start(session.sparkContext)
diff --git a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectServiceSuite.scala b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectServiceSuite.scala
index abbb181..ce45262 100644
--- a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectServiceSuite.scala
+++ b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/planner/SparkConnectServiceSuite.scala
@@ -606,7 +606,7 @@
           }
 
           override def onError(throwable: Throwable): Unit = {
-            verifyEvents.onCanceled
+            verifyEvents.onCanceled()
           }
 
           override def onCompleted(): Unit = {
diff --git a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/AddArtifactsHandlerSuite.scala b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/AddArtifactsHandlerSuite.scala
index 7dedf5e..2a65032 100644
--- a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/AddArtifactsHandlerSuite.scala
+++ b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/AddArtifactsHandlerSuite.scala
@@ -184,7 +184,7 @@
   }
 
   test("single chunk artifact") {
-    val promise = Promise[AddArtifactsResponse]
+    val promise = Promise[AddArtifactsResponse]()
     val handler = new TestAddArtifactsHandler(new DummyStreamObserver(promise))
     try {
       val name = "classes/smallClassFile.class"
@@ -208,7 +208,7 @@
   }
 
   test("Multi chunk artifact") {
-    val promise = Promise[AddArtifactsResponse]
+    val promise = Promise[AddArtifactsResponse]()
     val handler = new TestAddArtifactsHandler(new DummyStreamObserver(promise))
     try {
       val name = "jars/junitLargeJar.jar"
@@ -232,7 +232,7 @@
   }
 
   test("Mix of single-chunk and chunked artifacts") {
-    val promise = Promise[AddArtifactsResponse]
+    val promise = Promise[AddArtifactsResponse]()
     val handler = new TestAddArtifactsHandler(new DummyStreamObserver(promise))
     try {
       val names = Seq(
@@ -272,7 +272,7 @@
   }
 
   test("Artifacts that fail CRC are not added to the artifact manager") {
-    val promise = Promise[AddArtifactsResponse]
+    val promise = Promise[AddArtifactsResponse]()
     val handler = new TestAddArtifactsHandler(new DummyStreamObserver(promise))
     try {
       val name = "classes/smallClassFile.class"
@@ -365,7 +365,7 @@
   }
 
   test("Artifacts names are not allowed to be absolute paths") {
-    val promise = Promise[AddArtifactsResponse]
+    val promise = Promise[AddArtifactsResponse]()
     val handler = new TestAddArtifactsHandler(new DummyStreamObserver(promise))
     try {
       val name = "/absolute/path/"
@@ -382,7 +382,7 @@
   }
 
   test("Artifact name/paths cannot reference parent/sibling/nephew directories") {
-    val promise = Promise[AddArtifactsResponse]
+    val promise = Promise[AddArtifactsResponse]()
     val handler = new TestAddArtifactsHandler(new DummyStreamObserver(promise))
     try {
       val names = Seq("..", "../sibling", "../nephew/directory", "a/../../b", "x/../y/../..")
diff --git a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/ArtifactStatusesHandlerSuite.scala b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/ArtifactStatusesHandlerSuite.scala
index b7a92fa..54f7396 100644
--- a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/ArtifactStatusesHandlerSuite.scala
+++ b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/ArtifactStatusesHandlerSuite.scala
@@ -38,7 +38,7 @@
 
 class ArtifactStatusesHandlerSuite extends SharedSparkSession with ResourceHelper {
   def getStatuses(names: Seq[String], exist: Set[String]): ArtifactStatusesResponse = {
-    val promise = Promise[ArtifactStatusesResponse]
+    val promise = Promise[ArtifactStatusesResponse]()
     val handler = new SparkConnectArtifactStatusesHandler(new DummyStreamObserver(promise)) {
       override protected def cacheExists(
           userId: String,
diff --git a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/FetchErrorDetailsHandlerSuite.scala b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/FetchErrorDetailsHandlerSuite.scala
index 1b908ca..40439a2 100644
--- a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/FetchErrorDetailsHandlerSuite.scala
+++ b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/FetchErrorDetailsHandlerSuite.scala
@@ -51,7 +51,7 @@
       userId: String,
       sessionId: String,
       errorId: String): FetchErrorDetailsResponse = {
-    val promise = Promise[FetchErrorDetailsResponse]
+    val promise = Promise[FetchErrorDetailsResponse]()
     val handler =
       new SparkConnectFetchErrorDetailsHandler(new FetchErrorDetailsResponseObserver(promise))
     val context = proto.UserContext
diff --git a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/InterceptorRegistrySuite.scala b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/InterceptorRegistrySuite.scala
index 33f6627..8f76d58 100644
--- a/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/InterceptorRegistrySuite.scala
+++ b/connector/connect/server/src/test/scala/org/apache/spark/sql/connect/service/InterceptorRegistrySuite.scala
@@ -130,7 +130,7 @@
         "org.apache.spark.sql.connect.service.TestingInterceptorNoTrivialCtor") {
       checkError(
         exception = intercept[SparkException] {
-          SparkConnectInterceptorRegistry.createConfiguredInterceptors
+          SparkConnectInterceptorRegistry.createConfiguredInterceptors()
         },
         errorClass = "CONNECT.INTERCEPTOR_CTOR_MISSING",
         parameters =
@@ -142,7 +142,7 @@
         "org.apache.spark.sql.connect.service.TestingInterceptorInstantiationError") {
       checkError(
         exception = intercept[SparkException] {
-          SparkConnectInterceptorRegistry.createConfiguredInterceptors
+          SparkConnectInterceptorRegistry.createConfiguredInterceptors()
         },
         errorClass = "CONNECT.INTERCEPTOR_RUNTIME_ERROR",
         parameters = Map("msg" -> "Bad Error"))
@@ -151,10 +151,10 @@
 
   test("No configured interceptors returns empty list") {
     // Not set.
-    assert(SparkConnectInterceptorRegistry.createConfiguredInterceptors.isEmpty)
+    assert(SparkConnectInterceptorRegistry.createConfiguredInterceptors().isEmpty)
     // Set to empty string
     withSparkConf(Connect.CONNECT_GRPC_INTERCEPTOR_CLASSES.key -> "") {
-      assert(SparkConnectInterceptorRegistry.createConfiguredInterceptors.isEmpty)
+      assert(SparkConnectInterceptorRegistry.createConfiguredInterceptors().isEmpty)
     }
   }
 
@@ -163,14 +163,14 @@
       Connect.CONNECT_GRPC_INTERCEPTOR_CLASSES.key ->
         (" org.apache.spark.sql.connect.service.DummyInterceptor," +
           "    org.apache.spark.sql.connect.service.DummyInterceptor   ")) {
-      assert(SparkConnectInterceptorRegistry.createConfiguredInterceptors.size == 2)
+      assert(SparkConnectInterceptorRegistry.createConfiguredInterceptors().size == 2)
     }
   }
 
   test("Configured class not found is properly thrown") {
     withSparkConf(Connect.CONNECT_GRPC_INTERCEPTOR_CLASSES.key -> "this.class.does.not.exist") {
       assertThrows[ClassNotFoundException] {
-        SparkConnectInterceptorRegistry.createConfiguredInterceptors
+        SparkConnectInterceptorRegistry.createConfiguredInterceptors()
       }
     }
   }
diff --git a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/DB2IntegrationSuite.scala b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/DB2IntegrationSuite.scala
index e425151..e4ee7ab 100644
--- a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/DB2IntegrationSuite.scala
+++ b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/DB2IntegrationSuite.scala
@@ -187,7 +187,7 @@
       .option("url", jdbcUrl)
       .option("query", query)
       .load()
-    assert(df.collect.toSet === expectedResult)
+    assert(df.collect().toSet === expectedResult)
 
     // query option in the create table path.
     sql(
@@ -196,7 +196,7 @@
          |USING org.apache.spark.sql.jdbc
          |OPTIONS (url '$jdbcUrl', query '$query')
        """.stripMargin.replaceAll("\n", " "))
-    assert(sql("select x, y from queryOption").collect.toSet == expectedResult)
+    assert(sql("select x, y from queryOption").collect().toSet == expectedResult)
   }
 
   test("SPARK-30062") {
@@ -210,10 +210,10 @@
     for (_ <- 0 to 2) {
       df.write.mode(SaveMode.Append).jdbc(jdbcUrl, "tblcopy", new Properties)
     }
-    assert(sqlContext.read.jdbc(jdbcUrl, "tblcopy", new Properties).count === 6)
+    assert(sqlContext.read.jdbc(jdbcUrl, "tblcopy", new Properties).count() === 6)
     df.write.mode(SaveMode.Overwrite).option("truncate", true)
       .jdbc(jdbcUrl, "tblcopy", new Properties)
-    val actual = sqlContext.read.jdbc(jdbcUrl, "tblcopy", new Properties).collect
+    val actual = sqlContext.read.jdbc(jdbcUrl, "tblcopy", new Properties).collect()
     assert(actual.length === 2)
     assert(actual.toSet === expectedResult)
   }
diff --git a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MsSqlServerIntegrationSuite.scala b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MsSqlServerIntegrationSuite.scala
index 455416e..80ef33b 100644
--- a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MsSqlServerIntegrationSuite.scala
+++ b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MsSqlServerIntegrationSuite.scala
@@ -399,7 +399,7 @@
       .option("prepareQuery", prepareQuery)
       .option("query", query)
       .load()
-    assert(df.collect.toSet === expectedResult)
+    assert(df.collect().toSet === expectedResult)
   }
 
   test("SPARK-37259: prepareQuery and dbtable JDBC options") {
@@ -417,7 +417,7 @@
       .option("prepareQuery", prepareQuery)
       .option("dbtable", dbtable)
       .load()
-    assert(df.collect.toSet === expectedResult)
+    assert(df.collect().toSet === expectedResult)
   }
 
   test("SPARK-37259: temp table prepareQuery and query JDBC options") {
@@ -435,6 +435,6 @@
       .option("prepareQuery", prepareQuery)
       .option("query", query)
       .load()
-    assert(df.collect.toSet === expectedResult)
+    assert(df.collect().toSet === expectedResult)
   }
 }
diff --git a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MySQLIntegrationSuite.scala b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MySQLIntegrationSuite.scala
index dc3acb6..4294041 100644
--- a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MySQLIntegrationSuite.scala
+++ b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/MySQLIntegrationSuite.scala
@@ -183,7 +183,7 @@
       .option("url", jdbcUrl)
       .option("query", query)
       .load()
-    assert(df.collect.toSet === expectedResult)
+    assert(df.collect().toSet === expectedResult)
 
     // query option in the create table path.
     sql(
@@ -192,6 +192,6 @@
          |USING org.apache.spark.sql.jdbc
          |OPTIONS (url '$jdbcUrl', query '$query')
        """.stripMargin.replaceAll("\n", " "))
-    assert(sql("select x, y from queryOption").collect.toSet == expectedResult)
+    assert(sql("select x, y from queryOption").collect().toSet == expectedResult)
   }
 }
diff --git a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/OracleIntegrationSuite.scala b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/OracleIntegrationSuite.scala
index 4378c69..102a85e 100644
--- a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/OracleIntegrationSuite.scala
+++ b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/OracleIntegrationSuite.scala
@@ -460,7 +460,7 @@
           """"D" >= '2018-07-11' AND "D" < '2018-07-15'""",
           """"D" >= '2018-07-15'"""))
     }
-    assert(df1.collect.toSet === expectedResult)
+    assert(df1.collect().toSet === expectedResult)
 
     // TimestampType partition column
     val df2 = spark.read.format("jdbc")
@@ -482,7 +482,7 @@
           """"T" < '2018-07-15 20:50:32.5' or "T" is null""",
           """"T" >= '2018-07-15 20:50:32.5'"""))
     }
-    assert(df2.collect.toSet === expectedResult)
+    assert(df2.collect().toSet === expectedResult)
   }
 
   test("query JDBC option") {
@@ -499,7 +499,7 @@
       .option("query", query)
       .option("oracle.jdbc.mapDateToTimestamp", "false")
       .load()
-    assert(df.collect.toSet === expectedResult)
+    assert(df.collect().toSet === expectedResult)
 
     // query option in the create table path.
     sql(
@@ -510,7 +510,7 @@
          |   query '$query',
          |   oracle.jdbc.mapDateToTimestamp false)
        """.stripMargin.replaceAll("\n", " "))
-    assert(sql("select id, d, t from queryOption").collect.toSet == expectedResult)
+    assert(sql("select id, d, t from queryOption").collect().toSet == expectedResult)
   }
 
   test("SPARK-32992: map Oracle's ROWID type to StringType") {
diff --git a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala
index 90d6f6a..e4b0535 100644
--- a/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala
+++ b/connector/docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala
@@ -344,7 +344,7 @@
       .option("url", jdbcUrl)
       .option("query", query)
       .load()
-    assert(df.collect.toSet === expectedResult)
+    assert(df.collect().toSet === expectedResult)
 
     // query option in the create table path.
     sql(
@@ -353,7 +353,7 @@
          |USING org.apache.spark.sql.jdbc
          |OPTIONS (url '$jdbcUrl', query '$query')
        """.stripMargin.replaceAll("\n", " "))
-    assert(sql("select c1, c3 from queryOption").collect.toSet == expectedResult)
+    assert(sql("select c1, c3 from queryOption").collect().toSet == expectedResult)
   }
 
   test("write byte as smallint") {
diff --git a/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaOffsetReaderConsumer.scala b/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaOffsetReaderConsumer.scala
index 6198b64..e83a2c9 100644
--- a/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaOffsetReaderConsumer.scala
+++ b/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaOffsetReaderConsumer.scala
@@ -535,7 +535,7 @@
       }
       KafkaOffsetRange(tp, fromOffset, untilOffset, preferredLoc = None)
     }
-    rangeCalculator.getRanges(ranges, getSortedExecutorList)
+    rangeCalculator.getRanges(ranges, getSortedExecutorList())
   }
 
   private def partitionsAssignedToConsumer(
diff --git a/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumer.scala b/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumer.scala
index 245700d..1b1e0f1 100644
--- a/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumer.scala
+++ b/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumer.scala
@@ -701,7 +701,7 @@
   def acquire(
       topicPartition: TopicPartition,
       kafkaParams: ju.Map[String, Object]): KafkaDataConsumer = {
-    if (TaskContext.get != null && TaskContext.get.attemptNumber >= 1) {
+    if (TaskContext.get() != null && TaskContext.get().attemptNumber() >= 1) {
       val cacheKey = new CacheKey(topicPartition, kafkaParams)
 
       // If this is reattempt at running the task, then invalidate cached consumer if any.
diff --git a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaContinuousSourceSuite.scala b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaContinuousSourceSuite.scala
index 6801d14..e42662c 100644
--- a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaContinuousSourceSuite.scala
+++ b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaContinuousSourceSuite.scala
@@ -65,7 +65,7 @@
 
           eventually(timeout(streamingTimeout)) {
             // Should read all committed messages
-            checkAnswer(spark.table(table), (1 to 5).toDF)
+            checkAnswer(spark.table(table), (1 to 5).toDF())
           }
 
           producer.beginTransaction()
@@ -75,7 +75,7 @@
           producer.abortTransaction()
 
           // Should not read aborted messages
-          checkAnswer(spark.table(table), (1 to 5).toDF)
+          checkAnswer(spark.table(table), (1 to 5).toDF())
 
           producer.beginTransaction()
           (11 to 15).foreach { i =>
@@ -85,7 +85,7 @@
 
           eventually(timeout(streamingTimeout)) {
             // Should skip aborted messages and read new committed ones.
-            checkAnswer(spark.table(table), ((1 to 5) ++ (11 to 15)).toDF)
+            checkAnswer(spark.table(table), ((1 to 5) ++ (11 to 15)).toDF())
           }
         } finally {
           q.stop()
@@ -126,14 +126,14 @@
 
           eventually(timeout(streamingTimeout)) {
             // Should read uncommitted messages
-            checkAnswer(spark.table(table), (1 to 5).toDF)
+            checkAnswer(spark.table(table), (1 to 5).toDF())
           }
 
           producer.commitTransaction()
 
           eventually(timeout(streamingTimeout)) {
             // Should read all committed messages
-            checkAnswer(spark.table(table), (1 to 5).toDF)
+            checkAnswer(spark.table(table), (1 to 5).toDF())
           }
 
           producer.beginTransaction()
@@ -144,7 +144,7 @@
 
           eventually(timeout(streamingTimeout)) {
             // Should read aborted messages
-            checkAnswer(spark.table(table), (1 to 10).toDF)
+            checkAnswer(spark.table(table), (1 to 10).toDF())
           }
 
           producer.beginTransaction()
@@ -154,14 +154,14 @@
 
           eventually(timeout(streamingTimeout)) {
             // Should read all messages including committed, aborted and uncommitted messages
-            checkAnswer(spark.table(table), (1 to 15).toDF)
+            checkAnswer(spark.table(table), (1 to 15).toDF())
           }
 
           producer.commitTransaction()
 
           eventually(timeout(streamingTimeout)) {
             // Should read all messages including committed and aborted messages
-            checkAnswer(spark.table(table), (1 to 15).toDF)
+            checkAnswer(spark.table(table), (1 to 15).toDF())
           }
         } finally {
           q.stop()
diff --git a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaMicroBatchSourceSuite.scala b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaMicroBatchSourceSuite.scala
index 2315147..4e8da13 100644
--- a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaMicroBatchSourceSuite.scala
+++ b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaMicroBatchSourceSuite.scala
@@ -248,7 +248,7 @@
           .option("subscribe", outputTopic)
           .load()
           .select(expr("CAST(value AS string)"))
-          .toDF
+          .toDF()
           .collect().map(_.getAs[String]("value")).toList
       }
 
@@ -439,7 +439,7 @@
       .option("kafka.bootstrap.servers", testUtils.brokerAddress)
       .option("subscribe", topic)
 
-    testStream(reader.load)(
+    testStream(reader.load())(
       makeSureGetOffsetCalled,
       StopStream,
       StartStream(),
@@ -853,7 +853,7 @@
         true
       },
       AssertOnQuery { q =>
-        val latestOffset: Option[(Long, OffsetSeq)] = q.offsetLog.getLatest
+        val latestOffset: Option[(Long, OffsetSeq)] = q.offsetLog.getLatest()
         latestOffset.exists { offset =>
           !offset._2.offsets.exists(_.exists(_.json == "{}"))
         }
@@ -2499,7 +2499,7 @@
       .trigger(defaultTrigger)
       .start()
     eventually(timeout(streamingTimeout)) {
-      assert(spark.table("kafkaColumnTypes").count == 1,
+      assert(spark.table("kafkaColumnTypes").count() == 1,
         s"Unexpected results: ${spark.table("kafkaColumnTypes").collectAsList()}")
     }
     val row = spark.table("kafkaColumnTypes").head()
diff --git a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaRelationSuite.scala b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaRelationSuite.scala
index 6e1ece3..8d4e3e5 100644
--- a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaRelationSuite.scala
+++ b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaRelationSuite.scala
@@ -97,11 +97,11 @@
     // Specify explicit earliest and latest offset values
     val df = createDF(topic,
       withOptions = Map("startingOffsets" -> "earliest", "endingOffsets" -> "latest"))
-    checkAnswer(df, (0 to 20).map(_.toString).toDF)
+    checkAnswer(df, (0 to 20).map(_.toString).toDF())
 
     // "latest" should late bind to the current (latest) offset in the df
     testUtils.sendMessages(topic, (21 to 29).map(_.toString).toArray, Some(2))
-    checkAnswer(df, (0 to 29).map(_.toString).toDF)
+    checkAnswer(df, (0 to 29).map(_.toString).toDF())
   }
 
   test("default starting and ending offsets") {
@@ -114,7 +114,7 @@
     // Implicit offset values, should default to earliest and latest
     val df = createDF(topic)
     // Test that we default to "earliest" and "latest"
-    checkAnswer(df, (0 to 20).map(_.toString).toDF)
+    checkAnswer(df, (0 to 20).map(_.toString).toDF())
   }
 
   test("explicit offsets") {
@@ -140,15 +140,15 @@
     val endingOffsets = JsonUtils.partitionOffsets(endPartitionOffsets)
     val df = createDF(topic,
         withOptions = Map("startingOffsets" -> startingOffsets, "endingOffsets" -> endingOffsets))
-    checkAnswer(df, (0 to 20).map(_.toString).toDF)
+    checkAnswer(df, (0 to 20).map(_.toString).toDF())
 
     // static offset partition 2, nothing should change
     testUtils.sendMessages(topic, (31 to 39).map(_.toString).toArray, Some(2))
-    checkAnswer(df, (0 to 20).map(_.toString).toDF)
+    checkAnswer(df, (0 to 20).map(_.toString).toDF())
 
     // latest offset partition 1, should change
     testUtils.sendMessages(topic, (21 to 30).map(_.toString).toArray, Some(1))
-    checkAnswer(df, (0 to 30).map(_.toString).toDF)
+    checkAnswer(df, (0 to 30).map(_.toString).toDF())
   }
 
   test("default starting and ending offsets with headers") {
@@ -171,7 +171,7 @@
     // Test that we default to "earliest" and "latest"
     checkAnswer(df, Seq(("1", null),
       ("2", Seq(("a", "b".getBytes(UTF_8)), ("c", "d".getBytes(UTF_8)))),
-      ("3", Seq(("e", "f".getBytes(UTF_8)), ("e", "g".getBytes(UTF_8))))).toDF)
+      ("3", Seq(("e", "f".getBytes(UTF_8)), ("e", "g".getBytes(UTF_8))))).toDF())
   }
 
   test("timestamp provided for starting and ending") {
@@ -393,7 +393,7 @@
       .option("subscribe", topic)
 
     val df2 = optionFn(df).load().selectExpr("CAST(value AS STRING)")
-    checkAnswer(df2, expectation.map(_.toString).toDF)
+    checkAnswer(df2, expectation.map(_.toString).toDF())
   }
 
   test("reuse same dataframe in query") {
@@ -405,7 +405,7 @@
     // Specify explicit earliest and latest offset values
     val df = createDF(topic,
       withOptions = Map("startingOffsets" -> "earliest", "endingOffsets" -> "latest"))
-    checkAnswer(df.union(df), ((0 to 10) ++ (0 to 10)).map(_.toString).toDF)
+    checkAnswer(df.union(df), ((0 to 10) ++ (0 to 10)).map(_.toString).toDF())
   }
 
   test("test late binding start offsets") {
@@ -432,13 +432,13 @@
       val df = createDF(topic,
         withOptions = Map("startingOffsets" -> "earliest", "endingOffsets" -> "latest"),
         Some(kafkaUtils.brokerAddress))
-      checkAnswer(df, (0 to 9).map(_.toString).toDF)
+      checkAnswer(df, (0 to 9).map(_.toString).toDF())
       // Blow away current set of messages.
       kafkaUtils.cleanupLogs()
       // Add some more data, but do not call cleanup
       kafkaUtils.sendMessages(topic, (10 to 19).map(_.toString).toArray, Some(0))
       // Ensure that we late bind to the new starting position
-      checkAnswer(df, (10 to 19).map(_.toString).toDF)
+      checkAnswer(df, (10 to 19).map(_.toString).toDF())
     } finally {
       if (kafkaUtils != null) {
         kafkaUtils.teardown()
@@ -521,7 +521,7 @@
 
       // Should read all committed messages
       testUtils.waitUntilOffsetAppears(new TopicPartition(topic, 0), 6)
-      checkAnswer(df, (1 to 5).map(_.toString).toDF)
+      checkAnswer(df, (1 to 5).map(_.toString).toDF())
 
       producer.beginTransaction()
       (6 to 10).foreach { i =>
@@ -531,7 +531,7 @@
 
       // Should not read aborted messages
       testUtils.waitUntilOffsetAppears(new TopicPartition(topic, 0), 12)
-      checkAnswer(df, (1 to 5).map(_.toString).toDF)
+      checkAnswer(df, (1 to 5).map(_.toString).toDF())
 
       producer.beginTransaction()
       (11 to 15).foreach { i =>
@@ -541,7 +541,7 @@
 
       // Should skip aborted messages and read new committed ones.
       testUtils.waitUntilOffsetAppears(new TopicPartition(topic, 0), 18)
-      checkAnswer(df, ((1 to 5) ++ (11 to 15)).map(_.toString).toDF)
+      checkAnswer(df, ((1 to 5) ++ (11 to 15)).map(_.toString).toDF())
     }
   }
 
@@ -565,13 +565,13 @@
 
       // "read_uncommitted" should see all messages including uncommitted ones
       testUtils.waitUntilOffsetAppears(new TopicPartition(topic, 0), 5)
-      checkAnswer(df, (1 to 5).map(_.toString).toDF)
+      checkAnswer(df, (1 to 5).map(_.toString).toDF())
 
       producer.commitTransaction()
 
       // Should read all committed messages
       testUtils.waitUntilOffsetAppears(new TopicPartition(topic, 0), 6)
-      checkAnswer(df, (1 to 5).map(_.toString).toDF)
+      checkAnswer(df, (1 to 5).map(_.toString).toDF())
 
       producer.beginTransaction()
       (6 to 10).foreach { i =>
@@ -581,7 +581,7 @@
 
       // "read_uncommitted" should see all messages including uncommitted or aborted ones
       testUtils.waitUntilOffsetAppears(new TopicPartition(topic, 0), 12)
-      checkAnswer(df, (1 to 10).map(_.toString).toDF)
+      checkAnswer(df, (1 to 10).map(_.toString).toDF())
 
       producer.beginTransaction()
       (11 to 15).foreach { i =>
@@ -591,7 +591,7 @@
 
       // Should read all messages
       testUtils.waitUntilOffsetAppears(new TopicPartition(topic, 0), 18)
-      checkAnswer(df, (1 to 15).map(_.toString).toDF)
+      checkAnswer(df, (1 to 15).map(_.toString).toDF())
     }
   }
 
diff --git a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumerSuite.scala b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumerSuite.scala
index 8c5289a..d494433 100644
--- a/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumerSuite.scala
+++ b/connector/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/consumer/KafkaDataConsumerSuite.scala
@@ -197,7 +197,7 @@
     @volatile var error: Throwable = null
 
     def consume(i: Int): Unit = {
-      val taskContext = if (Random.nextBoolean) {
+      val taskContext = if (Random.nextBoolean()) {
         new TaskContextImpl(0, 0, 0, 0, attemptNumber = Random.nextInt(2), 1,
           null, null, null)
       } else {
diff --git a/connector/kafka-0-10-token-provider/src/main/scala/org/apache/spark/kafka010/KafkaTokenUtil.scala b/connector/kafka-0-10-token-provider/src/main/scala/org/apache/spark/kafka010/KafkaTokenUtil.scala
index 93cc522..497ba03 100644
--- a/connector/kafka-0-10-token-provider/src/main/scala/org/apache/spark/kafka010/KafkaTokenUtil.scala
+++ b/connector/kafka-0-10-token-provider/src/main/scala/org/apache/spark/kafka010/KafkaTokenUtil.scala
@@ -195,7 +195,7 @@
       kerberosServiceName: String): String = {
     val params =
       s"""
-      |${SecurityUtils.getKrb5LoginModuleName} required
+      |${SecurityUtils.getKrb5LoginModuleName()} required
       | debug=${SecurityUtils.isGlobalKrbDebugEnabled()}
       | useKeyTab=true
       | serviceName="$kerberosServiceName"
@@ -209,7 +209,7 @@
   private def getTicketCacheJaasParams(clusterConf: KafkaTokenClusterConf): String = {
     val params =
       s"""
-      |${SecurityUtils.getKrb5LoginModuleName} required
+      |${SecurityUtils.getKrb5LoginModuleName()} required
       | debug=${SecurityUtils.isGlobalKrbDebugEnabled()}
       | useTicketCache=true
       | serviceName="${clusterConf.kerberosServiceName}";
diff --git a/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/DirectKafkaInputDStream.scala b/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/DirectKafkaInputDStream.scala
index 971b3b3..d803726 100644
--- a/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/DirectKafkaInputDStream.scala
+++ b/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/DirectKafkaInputDStream.scala
@@ -83,7 +83,7 @@
   }
 
   protected def getBrokers = {
-    val c = consumer
+    val c = consumer()
     val result = new ju.HashMap[TopicPartition, String]()
     val hosts = new ju.HashMap[TopicPartition, String]()
     val assignments = c.assignment().iterator()
@@ -187,7 +187,7 @@
    * Returns the latest (highest) available offsets, taking new partitions into account.
    */
   protected def latestOffsets(): Map[TopicPartition, Long] = {
-    val c = consumer
+    val c = consumer()
     paranoidPoll(c)
     val parts = c.assignment().asScala
 
@@ -247,7 +247,7 @@
     val metadata = Map(
       "offsets" -> offsetRanges.toList,
       StreamInputInfo.METADATA_KEY_DESCRIPTION -> description)
-    val inputInfo = StreamInputInfo(id, rdd.count, metadata)
+    val inputInfo = StreamInputInfo(id, rdd.count(), metadata)
     ssc.scheduler.inputInfoTracker.reportInfo(validTime, inputInfo)
 
     currentOffsets = untilOffsets
@@ -256,7 +256,7 @@
   }
 
   override def start(): Unit = {
-    val c = consumer
+    val c = consumer()
     paranoidPoll(c)
     if (currentOffsets.isEmpty) {
       currentOffsets = c.assignment().asScala.map { tp =>
@@ -296,14 +296,14 @@
     val m = new ju.HashMap[TopicPartition, OffsetAndMetadata]()
     var osr = commitQueue.poll()
     while (null != osr) {
-      val tp = osr.topicPartition
+      val tp = osr.topicPartition()
       val x = m.get(tp)
       val offset = if (null == x) { osr.untilOffset } else { Math.max(x.offset, osr.untilOffset) }
       m.put(tp, new OffsetAndMetadata(offset))
       osr = commitQueue.poll()
     }
     if (!m.isEmpty) {
-      consumer.commitAsync(m, commitCallback.get)
+      consumer().commitAsync(m, commitCallback.get)
     }
   }
 
diff --git a/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumer.scala b/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumer.scala
index 8becbe4..c7ac6a8 100644
--- a/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumer.scala
+++ b/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumer.scala
@@ -293,7 +293,7 @@
 
     lazy val newInternalConsumer = new InternalKafkaConsumer[K, V](topicPartition, kafkaParams)
 
-    if (context != null && context.attemptNumber >= 1) {
+    if (context != null && context.attemptNumber() >= 1) {
       // If this is reattempt at running the task, then invalidate cached consumers if any and
       // start with a new one. If prior attempt failures were cache related then this way old
       // problematic consumers can be removed.
diff --git a/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaRDD.scala b/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaRDD.scala
index b6ce5e2..b8dbfe2 100644
--- a/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaRDD.scala
+++ b/connector/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaRDD.scala
@@ -87,7 +87,7 @@
     if (compacted) {
       super.count()
     } else {
-      offsetRanges.map(_.count).sum
+      offsetRanges.map(_.count()).sum
     }
 
   override def countApprox(
@@ -97,7 +97,7 @@
     if (compacted) {
       super.countApprox(timeout, confidence)
     } else {
-      val c = count
+      val c = count()
       new PartialResult(new BoundedDouble(c, 1.0, c, c), true)
     }
 
@@ -105,7 +105,7 @@
     if (compacted) {
       super.isEmpty()
     } else {
-      count == 0L
+      count() == 0L
     }
 
   override def take(num: Int): Array[ConsumerRecord[K, V]] =
@@ -116,7 +116,7 @@
     } else {
       val nonEmptyPartitions = this.partitions
         .map(_.asInstanceOf[KafkaRDDPartition])
-        .filter(_.count > 0)
+        .filter(_.count() > 0)
 
       if (nonEmptyPartitions.isEmpty) {
         Array.empty[ConsumerRecord[K, V]]
@@ -125,7 +125,7 @@
         val parts = nonEmptyPartitions.foldLeft(Map[Int, Int]()) { (result, part) =>
           val remain = num - result.values.sum
           if (remain > 0) {
-            val taken = Math.min(remain, part.count)
+            val taken = Math.min(remain, part.count())
             result + (part.index -> taken.toInt)
           } else {
             result
@@ -135,7 +135,7 @@
         context.runJob(
           this,
           (tc: TaskContext, it: Iterator[ConsumerRecord[K, V]]) =>
-          it.take(parts(tc.partitionId)).toArray, parts.keys.toArray
+          it.take(parts(tc.partitionId())).toArray, parts.keys.toArray
         ).flatten
       }
     }
@@ -162,7 +162,7 @@
     // TODO what about hosts specified by ip vs name
     val part = thePart.asInstanceOf[KafkaRDDPartition]
     val allExecs = executors()
-    val tp = part.topicPartition
+    val tp = part.topicPartition()
     val prefHost = preferredHosts.get(tp)
     val prefExecs = if (null == prefHost) allExecs else allExecs.filter(_.host == prefHost)
     val execs = if (prefExecs.isEmpty) allExecs else prefExecs
diff --git a/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/DirectKafkaStreamSuite.scala b/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/DirectKafkaStreamSuite.scala
index 978baaa..7b2cac4a 100644
--- a/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/DirectKafkaStreamSuite.scala
+++ b/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/DirectKafkaStreamSuite.scala
@@ -90,7 +90,7 @@
     kp.put("bootstrap.servers", kafkaTestUtils.brokerAddress)
     kp.put("key.deserializer", classOf[StringDeserializer])
     kp.put("value.deserializer", classOf[StringDeserializer])
-    kp.put("group.id", s"test-consumer-${Random.nextInt}-${System.currentTimeMillis}")
+    kp.put("group.id", s"test-consumer-${Random.nextInt()}-${System.currentTimeMillis}")
     extra.foreach(e => kp.put(e._1, e._2))
     kp
   }
@@ -138,7 +138,7 @@
         val partSize = all.size
         val rangeSize = off.untilOffset - off.fromOffset
         Iterator((partSize, rangeSize))
-      }.collect
+      }.collect()
 
       // Verify whether number of elements in each partition
       // matches with the corresponding offset range
@@ -204,7 +204,7 @@
         val partSize = all.size
         val rangeSize = off.untilOffset - off.fromOffset
         Iterator((partSize, rangeSize))
-      }.collect
+      }.collect()
 
       // Verify whether number of elements in each partition
       // matches with the corresponding offset range
@@ -255,9 +255,9 @@
         preferredHosts,
         ConsumerStrategies.Subscribe[String, String](List(topic), kafkaParams.asScala),
         new DefaultPerPartitionConfig(sparkConf))
-      s.consumer.poll(0)
+      s.consumer().poll(0)
       assert(
-        s.consumer.position(topicPartition) >= offsetBeforeStart,
+        s.consumer().position(topicPartition) >= offsetBeforeStart,
         "Start offset not from latest"
       )
       s
@@ -311,9 +311,9 @@
           kafkaParams.asScala,
           Map(topicPartition -> 11L)),
         new DefaultPerPartitionConfig(sparkConf))
-      s.consumer.poll(0)
+      s.consumer().poll(0)
       assert(
-        s.consumer.position(topicPartition) >= offsetBeforeStart,
+        s.consumer().position(topicPartition) >= offsetBeforeStart,
         "Start offset not from latest"
       )
       s
diff --git a/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumerSuite.scala b/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumerSuite.scala
index 0d1e13b..d7591a9 100644
--- a/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumerSuite.scala
+++ b/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaDataConsumerSuite.scala
@@ -123,8 +123,8 @@
     @volatile var error: Throwable = null
 
     def consume(i: Int): Unit = {
-      val useCache = Random.nextBoolean
-      val taskContext = if (Random.nextBoolean) {
+      val useCache = Random.nextBoolean()
+      val taskContext = if (Random.nextBoolean()) {
         new TaskContextImpl(0, 0, 0, 0, attemptNumber = Random.nextInt(2), 1, null, null, null)
       } else {
         null
diff --git a/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaRDDSuite.scala b/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaRDDSuite.scala
index 986943ac6..2591fff 100644
--- a/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaRDDSuite.scala
+++ b/connector/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/KafkaRDDSuite.scala
@@ -59,7 +59,7 @@
     try {
       try {
         if (sc != null) {
-          sc.stop
+          sc.stop()
           sc = null
         }
       } finally {
@@ -77,7 +77,7 @@
     "bootstrap.servers" -> kafkaTestUtils.brokerAddress,
     "key.deserializer" -> classOf[StringDeserializer],
     "value.deserializer" -> classOf[StringDeserializer],
-    "group.id" -> s"test-consumer-${Random.nextInt}-${System.currentTimeMillis}"
+    "group.id" -> s"test-consumer-${Random.nextInt()}-${System.currentTimeMillis}"
   ).asJava
 
   private val preferredHosts = LocationStrategies.PreferConsistent
@@ -130,7 +130,7 @@
 
 
   test("basic usage") {
-    val topic = s"topicbasic-${Random.nextInt}-${System.currentTimeMillis}"
+    val topic = s"topicbasic-${Random.nextInt()}-${System.currentTimeMillis}"
     kafkaTestUtils.createTopic(topic)
     val messages = Array("the", "quick", "brown", "fox")
     kafkaTestUtils.sendMessages(topic, messages)
@@ -142,13 +142,13 @@
     val rdd = KafkaUtils.createRDD[String, String](sc, kafkaParams, offsetRanges, preferredHosts)
       .map(_.value)
 
-    val received = rdd.collect.toSet
+    val received = rdd.collect().toSet
     assert(received === messages.toSet)
 
     // size-related method optimizations return sane results
-    assert(rdd.count === messages.size)
-    assert(rdd.countApprox(0).getFinalValue.mean === messages.size)
-    assert(!rdd.isEmpty)
+    assert(rdd.count() === messages.size)
+    assert(rdd.countApprox(0).getFinalValue().mean === messages.size)
+    assert(!rdd.isEmpty())
     assert(rdd.take(1).size === 1)
     assert(rdd.take(1).head === messages.head)
     assert(rdd.take(messages.size + 10).size === messages.size)
@@ -156,7 +156,7 @@
     val emptyRdd = KafkaUtils.createRDD[String, String](
       sc, kafkaParams, Array(OffsetRange(topic, 0, 0, 0)), preferredHosts)
 
-    assert(emptyRdd.isEmpty)
+    assert(emptyRdd.isEmpty())
 
     // invalid offset ranges throw exceptions
     val badRanges = Array(OffsetRange(topic, 0, 0, messages.size + 1))
@@ -172,7 +172,7 @@
     compactConf.set("spark.streaming.kafka.allowNonConsecutiveOffsets", "true")
     sc.stop()
     sc = new SparkContext(compactConf)
-    val topic = s"topiccompacted-${Random.nextInt}-${System.currentTimeMillis}"
+    val topic = s"topiccompacted-${Random.nextInt()}-${System.currentTimeMillis}"
 
     val messages = Array(
       ("a", "1"),
@@ -212,13 +212,13 @@
       val dir = new File(kafkaTestUtils.brokerLogDir, topic + "-0")
       assert(dir.listFiles().exists(_.getName.endsWith(".deleted")))
     }
-    val received = rdd.collect.toSet
+    val received = rdd.collect().toSet
     assert(received === compactedMessages.toSet)
 
     // size-related method optimizations return sane results
-    assert(rdd.count === compactedMessages.size)
-    assert(rdd.countApprox(0).getFinalValue.mean === compactedMessages.size)
-    assert(!rdd.isEmpty)
+    assert(rdd.count() === compactedMessages.size)
+    assert(rdd.countApprox(0).getFinalValue().mean === compactedMessages.size)
+    assert(!rdd.isEmpty())
     assert(rdd.take(1).size === 1)
     assert(rdd.take(1).head === compactedMessages.head)
     assert(rdd.take(messages.size + 10).size === compactedMessages.size)
@@ -226,7 +226,7 @@
     val emptyRdd = KafkaUtils.createRDD[String, String](
       sc, kafkaParams, Array(OffsetRange(topic, 0, 0, 0)), preferredHosts)
 
-    assert(emptyRdd.isEmpty)
+    assert(emptyRdd.isEmpty())
 
     // invalid offset ranges throw exceptions
     val badRanges = Array(OffsetRange(topic, 0, 0, messages.size + 1))
@@ -239,7 +239,7 @@
 
   test("iterator boundary conditions") {
     // the idea is to find e.g. off-by-one errors between what kafka has available and the rdd
-    val topic = s"topicboundary-${Random.nextInt}-${System.currentTimeMillis}"
+    val topic = s"topicboundary-${Random.nextInt()}-${System.currentTimeMillis}"
     val sent = Map("a" -> 5, "b" -> 3, "c" -> 10)
     kafkaTestUtils.createTopic(topic)
 
@@ -256,7 +256,7 @@
     val rangeCount = ranges.map(o => o.untilOffset - o.fromOffset).sum
 
     assert(rangeCount === sentCount, "offset range didn't include all sent messages")
-    assert(rdd.map(_.offset).collect.sorted === (0 until sentCount).toArray,
+    assert(rdd.map(_.offset).collect().sorted === (0 until sentCount).toArray,
       "didn't get all sent messages")
 
     // this is the "0 messages" case
@@ -268,7 +268,7 @@
 
     kafkaTestUtils.sendMessages(topic, sentOnlyOne)
 
-    assert(rdd2.map(_.value).collect.size === 0, "got messages when there shouldn't be any")
+    assert(rdd2.map(_.value).collect().size === 0, "got messages when there shouldn't be any")
 
     // this is the "exactly 1 message" case, namely the single message from sentOnlyOne above
     val rdd3 = KafkaUtils.createRDD[String, String](sc, kafkaParams,
@@ -277,7 +277,7 @@
     // send lots of messages after rdd was defined, they shouldn't show up
     kafkaTestUtils.sendMessages(topic, Map("extra" -> 22))
 
-    assert(rdd3.map(_.value).collect.head === sentOnlyOne.keys.head,
+    assert(rdd3.map(_.value).collect().head === sentOnlyOne.keys.head,
       "didn't get exactly one message")
   }
 
diff --git a/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KPLBasedKinesisTestUtils.scala b/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KPLBasedKinesisTestUtils.scala
index c76eb7c..f95bee1 100644
--- a/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KPLBasedKinesisTestUtils.scala
+++ b/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KPLBasedKinesisTestUtils.scala
@@ -69,7 +69,7 @@
           sentSeqNumbers += ((num, seqNumber))
         }
       }
-      Futures.addCallback(future, kinesisCallBack, ThreadUtils.sameThreadExecutorService)
+      Futures.addCallback(future, kinesisCallBack, ThreadUtils.sameThreadExecutorService())
     }
     producer.flushSync()
     shardIdToSeqNumbers.mapValues(_.toSeq).toMap
diff --git a/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisInputDStreamBuilderSuite.scala b/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisInputDStreamBuilderSuite.scala
index ba04c01..9f2e34e 100644
--- a/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisInputDStreamBuilderSuite.scala
+++ b/connector/kinesis-asl/src/test/scala/org/apache/spark/streaming/kinesis/KinesisInputDStreamBuilderSuite.scala
@@ -184,7 +184,7 @@
         .checkpointAppName(appName)
         .checkpointInterval(checkpointInterval)
         .storageLevel(storageLevel)
-        .build
+        .build()
     }
   }
 }
diff --git a/core/src/main/scala/org/apache/spark/BarrierCoordinator.scala b/core/src/main/scala/org/apache/spark/BarrierCoordinator.scala
index 8ffccdf..9bc7ade 100644
--- a/core/src/main/scala/org/apache/spark/BarrierCoordinator.scala
+++ b/core/src/main/scala/org/apache/spark/BarrierCoordinator.scala
@@ -57,7 +57,7 @@
   private val listener = new SparkListener {
     override def onStageCompleted(stageCompleted: SparkListenerStageCompleted): Unit = {
       val stageInfo = stageCompleted.stageInfo
-      val barrierId = ContextBarrierId(stageInfo.stageId, stageInfo.attemptNumber)
+      val barrierId = ContextBarrierId(stageInfo.stageId, stageInfo.attemptNumber())
       // Clear ContextBarrierState from a finished stage attempt.
       cleanupBarrierStage(barrierId)
     }
diff --git a/core/src/main/scala/org/apache/spark/BarrierTaskContext.scala b/core/src/main/scala/org/apache/spark/BarrierTaskContext.scala
index ff14103..0f9abaf 100644
--- a/core/src/main/scala/org/apache/spark/BarrierTaskContext.scala
+++ b/core/src/main/scala/org/apache/spark/BarrierTaskContext.scala
@@ -56,14 +56,15 @@
   private var barrierEpoch = 0
 
   private def runBarrier(message: String, requestMethod: RequestMethod.Value): Array[String] = {
-    logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) has entered " +
-      s"the global sync, current barrier epoch is $barrierEpoch.")
+    logInfo(s"Task ${taskAttemptId()} from Stage ${stageId()}(Attempt ${stageAttemptNumber()}) " +
+      s"has entered the global sync, current barrier epoch is $barrierEpoch.")
     logTrace("Current callSite: " + Utils.getCallSite())
 
     val startTime = System.currentTimeMillis()
     val timerTask = new TimerTask {
       override def run(): Unit = {
-        logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) waiting " +
+        logInfo(s"Task ${taskAttemptId()} from Stage ${stageId()}(Attempt " +
+          s"${stageAttemptNumber()}) waiting " +
           s"under the global sync since $startTime, has been waiting for " +
           s"${MILLISECONDS.toSeconds(System.currentTimeMillis() - startTime)} seconds, " +
           s"current barrier epoch is $barrierEpoch.")
@@ -74,8 +75,8 @@
 
     try {
       val abortableRpcFuture = barrierCoordinator.askAbortable[Array[String]](
-        message = RequestToSync(numPartitions, stageId, stageAttemptNumber, taskAttemptId,
-          barrierEpoch, partitionId, message, requestMethod),
+        message = RequestToSync(numPartitions(), stageId(), stageAttemptNumber(), taskAttemptId(),
+          barrierEpoch, partitionId(), message, requestMethod),
         // Set a fixed timeout for RPC here, so users shall get a SparkException thrown by
         // BarrierCoordinator on timeout, instead of RPCTimeoutException from the RPC framework.
         timeout = new RpcTimeout(365.days, "barrierTimeout"))
@@ -102,15 +103,15 @@
       val messages = abortableRpcFuture.future.value.get.get
 
       barrierEpoch += 1
-      logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) finished " +
-        "global sync successfully, waited for " +
+      logInfo(s"Task ${taskAttemptId()} from Stage ${stageId()}(Attempt ${stageAttemptNumber()}) " +
+        s"finished global sync successfully, waited for " +
         s"${MILLISECONDS.toSeconds(System.currentTimeMillis() - startTime)} seconds, " +
         s"current barrier epoch is $barrierEpoch.")
       messages
     } catch {
       case e: SparkException =>
-        logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) failed " +
-          "to perform global sync, waited for " +
+        logInfo(s"Task ${taskAttemptId()} from Stage ${stageId()}(Attempt " +
+          s"${stageAttemptNumber()}) failed to perform global sync, waited for " +
           s"${MILLISECONDS.toSeconds(System.currentTimeMillis() - startTime)} seconds, " +
           s"current barrier epoch is $barrierEpoch.")
         throw e
diff --git a/core/src/main/scala/org/apache/spark/Heartbeater.scala b/core/src/main/scala/org/apache/spark/Heartbeater.scala
index 4f749dd..090458e 100644
--- a/core/src/main/scala/org/apache/spark/Heartbeater.scala
+++ b/core/src/main/scala/org/apache/spark/Heartbeater.scala
@@ -40,7 +40,7 @@
   /** Schedules a task to report a heartbeat. */
   def start(): Unit = {
     // Wait a random interval so the heartbeats don't end up in sync
-    val initialDelay = intervalMs + (math.random * intervalMs).asInstanceOf[Int]
+    val initialDelay = intervalMs + (math.random() * intervalMs).asInstanceOf[Int]
 
     val heartbeatTask = new Runnable() {
       override def run(): Unit = Utils.logUncaughtExceptions(reportHeartbeat())
diff --git a/core/src/main/scala/org/apache/spark/SecurityManager.scala b/core/src/main/scala/org/apache/spark/SecurityManager.scala
index 821577f0..f8961ff 100644
--- a/core/src/main/scala/org/apache/spark/SecurityManager.scala
+++ b/core/src/main/scala/org/apache/spark/SecurityManager.scala
@@ -304,7 +304,7 @@
    * @return the secret key as a String if authentication is enabled, otherwise returns null
    */
   def getSecretKey(): String = {
-    if (isAuthenticationEnabled) {
+    if (isAuthenticationEnabled()) {
       val creds = UserGroupInformation.getCurrentUser().getCredentials()
       Option(creds.getSecretKey(SECRET_LOOKUP_KEY))
         .map { bytes => new String(bytes, UTF_8) }
@@ -396,7 +396,7 @@
       aclUsers: Set[String],
       aclGroups: Set[String]): Boolean = {
     if (user == null ||
-        !aclsEnabled ||
+        !aclsEnabled() ||
         aclUsers.contains(WILDCARD_ACL) ||
         aclUsers.contains(user) ||
         aclGroups.contains(WILDCARD_ACL)) {
diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala
index 008b963..893895e 100644
--- a/core/src/main/scala/org/apache/spark/SparkContext.scala
+++ b/core/src/main/scala/org/apache/spark/SparkContext.scala
@@ -1688,7 +1688,7 @@
     require(!classOf[RDD[_]].isAssignableFrom(classTag[T].runtimeClass),
       "Can not directly broadcast RDDs; instead, call collect() and broadcast the result.")
     val bc = env.broadcastManager.newBroadcast[T](value, isLocal, serializedOnly)
-    val callSite = getCallSite
+    val callSite = getCallSite()
     logInfo("Created broadcast " + bc.id + " from " + callSite.shortForm)
     cleaner.foreach(_.registerBroadcastForCleanup(bc))
     bc
@@ -2417,7 +2417,7 @@
     if (stopped.get()) {
       throw new IllegalStateException("SparkContext has been shutdown")
     }
-    val callSite = getCallSite
+    val callSite = getCallSite()
     val cleanedFunc = clean(func)
     logInfo("Starting job: " + callSite.shortForm)
     if (conf.getBoolean("spark.logLineage", false)) {
@@ -2539,7 +2539,7 @@
       evaluator: ApproximateEvaluator[U, R],
       timeout: Long): PartialResult[R] = {
     assertNotStopped()
-    val callSite = getCallSite
+    val callSite = getCallSite()
     logInfo("Starting job: " + callSite.shortForm)
     val start = System.nanoTime
     val cleanedFunc = clean(func)
@@ -2569,7 +2569,7 @@
   {
     assertNotStopped()
     val cleanF = clean(processPartition)
-    val callSite = getCallSite
+    val callSite = getCallSite()
     val waiter = dagScheduler.submitJob(
       rdd,
       (context: TaskContext, iter: Iterator[T]) => cleanF(iter),
@@ -2733,7 +2733,7 @@
   /** Default level of parallelism to use when not given by user (e.g. parallelize and makeRDD). */
   def defaultParallelism: Int = {
     assertNotStopped()
-    taskScheduler.defaultParallelism
+    taskScheduler.defaultParallelism()
   }
 
   /**
@@ -2803,7 +2803,7 @@
       val addedArchivePaths = allAddedArchives.keys.toSeq
       val environmentDetails = SparkEnv.environmentDetails(conf, hadoopConfiguration,
         schedulingMode, addedJarPaths, addedFilePaths, addedArchivePaths,
-        env.metricsSystem.metricsProperties.asScala.toMap)
+        env.metricsSystem.metricsProperties().asScala.toMap)
       val environmentUpdate = SparkListenerEnvironmentUpdate(environmentDetails)
       listenerBus.post(environmentUpdate)
     }
diff --git a/core/src/main/scala/org/apache/spark/TestUtils.scala b/core/src/main/scala/org/apache/spark/TestUtils.scala
index f0dbfa9..8c3af98 100644
--- a/core/src/main/scala/org/apache/spark/TestUtils.scala
+++ b/core/src/main/scala/org/apache/spark/TestUtils.scala
@@ -398,7 +398,7 @@
 
   def withHttpServer(resBaseDir: String = ".")(body: URL => Unit): Unit = {
     // 0 as port means choosing randomly from the available ports
-    val server = new Server(new InetSocketAddress(Utils.localCanonicalHostName, 0))
+    val server = new Server(new InetSocketAddress(Utils.localCanonicalHostName(), 0))
     val resHandler = new ResourceHandler()
     resHandler.setResourceBase(resBaseDir)
     val handlers = new HandlerList()
diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala
index 80c6e1f..6ead369 100644
--- a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala
+++ b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala
@@ -749,7 +749,7 @@
    *
    * @since 3.5.0
    */
-  def getJobTags(): util.Set[String] = sc.getJobTags.asJava
+  def getJobTags(): util.Set[String] = sc.getJobTags().asJava
 
   /**
    * Clear the current thread's job tags.
diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala b/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala
index 4eafbbd..840352e 100644
--- a/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala
+++ b/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala
@@ -221,7 +221,7 @@
     }
 
     if (reuseWorker) {
-      val key = (worker, context.taskAttemptId)
+      val key = (worker, context.taskAttemptId())
       // SPARK-35009: avoid creating multiple monitor threads for the same python worker
       // and task context
       if (PythonRunner.runningMonitorThreads.add(key)) {
@@ -399,7 +399,7 @@
         dataOut.flush()
       } catch {
         case t: Throwable if NonFatal(t) || t.isInstanceOf[Exception] =>
-          if (context.isCompleted || context.isInterrupted) {
+          if (context.isCompleted() || context.isInterrupted()) {
             logDebug("Exception/NonFatal Error thrown after task completion (likely due to " +
               "cleanup)", t)
             if (worker.channel.isConnected) {
@@ -507,8 +507,8 @@
         init, finish))
       val memoryBytesSpilled = stream.readLong()
       val diskBytesSpilled = stream.readLong()
-      context.taskMetrics.incMemoryBytesSpilled(memoryBytesSpilled)
-      context.taskMetrics.incDiskBytesSpilled(diskBytesSpilled)
+      context.taskMetrics().incMemoryBytesSpilled(memoryBytesSpilled)
+      context.taskMetrics().incDiskBytesSpilled(diskBytesSpilled)
     }
 
     protected def handlePythonException(): PythonException = {
@@ -533,7 +533,7 @@
     }
 
     protected val handleException: PartialFunction[Throwable, OUT] = {
-      case e: Exception if context.isInterrupted =>
+      case e: Exception if context.isInterrupted() =>
         logDebug("Exception thrown after task interruption", e)
         throw new TaskKilledException(context.getKillReason().getOrElse("unknown reason"))
 
@@ -570,16 +570,16 @@
     private def monitorWorker(): Unit = {
       // Kill the worker if it is interrupted, checking until task completion.
       // TODO: This has a race condition if interruption occurs, as completed may still become true.
-      while (!context.isInterrupted && !context.isCompleted) {
+      while (!context.isInterrupted() && !context.isCompleted()) {
         Thread.sleep(2000)
       }
-      if (!context.isCompleted) {
+      if (!context.isCompleted()) {
         Thread.sleep(taskKillTimeout)
-        if (!context.isCompleted) {
+        if (!context.isCompleted()) {
           try {
             // Mimic the task name used in `Executor` to help the user find out the task to blame.
-            val taskName = s"${context.partitionId}.${context.attemptNumber} " +
-              s"in stage ${context.stageId} (TID ${context.taskAttemptId})"
+            val taskName = s"${context.partitionId()}.${context.attemptNumber()} " +
+              s"in stage ${context.stageId()} (TID ${context.taskAttemptId()})"
             logWarning(s"Incomplete task $taskName interrupted: Attempting to kill Python Worker")
             env.destroyPythonWorker(
               pythonExec, workerModule, daemonModule, envVars.asScala.toMap, worker)
@@ -596,7 +596,7 @@
         monitorWorker()
       } finally {
         if (reuseWorker) {
-          val key = (worker, context.taskAttemptId)
+          val key = (worker, context.taskAttemptId())
           PythonRunner.runningMonitorThreads.remove(key)
         }
       }
diff --git a/core/src/main/scala/org/apache/spark/api/r/BaseRRunner.scala b/core/src/main/scala/org/apache/spark/api/r/BaseRRunner.scala
index 0f93873..09add64 100644
--- a/core/src/main/scala/org/apache/spark/api/r/BaseRRunner.scala
+++ b/core/src/main/scala/org/apache/spark/api/r/BaseRRunner.scala
@@ -236,7 +236,7 @@
   val lines = new Array[String](errBufferSize)
   var lineIdx = 0
   override def run(): Unit = {
-    for (line <- Source.fromInputStream(in).getLines) {
+    for (line <- Source.fromInputStream(in).getLines()) {
       synchronized {
         lines(lineIdx) = line
         lineIdx = (lineIdx + 1) % errBufferSize
diff --git a/core/src/main/scala/org/apache/spark/deploy/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/deploy/JsonProtocol.scala
index 0a5399a..8c35608 100644
--- a/core/src/main/scala/org/apache/spark/deploy/JsonProtocol.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/JsonProtocol.scala
@@ -29,7 +29,7 @@
 
   private def writeResourcesInfo(info: Map[String, ResourceInformation]): JObject = {
     val jsonFields = info.map {
-      case (k, v) => JField(k, v.toJson)
+      case (k, v) => JField(k, v.toJson())
     }
     JObject(jsonFields.toList)
   }
diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
index c100e92..bd6507c 100644
--- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala
@@ -612,7 +612,7 @@
       stream.flush()
 
       // Get the output and discard any unnecessary lines from it.
-      Source.fromString(new String(out.toByteArray(), StandardCharsets.UTF_8)).getLines
+      Source.fromString(new String(out.toByteArray(), StandardCharsets.UTF_8)).getLines()
         .filter { line =>
           !line.startsWith("log4j") && !line.startsWith("usage")
         }
diff --git a/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala b/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala
index 99b3184..3592673 100644
--- a/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala
@@ -203,7 +203,7 @@
     if (!Utils.isTesting) {
       ThreadUtils.newDaemonFixedThreadPool(NUM_PROCESSING_THREADS, "log-replay-executor")
     } else {
-      ThreadUtils.sameThreadExecutorService
+      ThreadUtils.sameThreadExecutorService()
     }
   }
 
diff --git a/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala b/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala
index f2cd5b7..887adc4 100644
--- a/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala
@@ -72,7 +72,7 @@
             } else if (eventLogsUnderProcessCount > 0) {
               <h4>No completed applications found!</h4>
             } else {
-              <h4>No completed applications found!</h4> ++ parent.emptyListingHtml
+              <h4>No completed applications found!</h4> ++ parent.emptyListingHtml()
             }
             }
 
diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/CommandUtils.scala b/core/src/main/scala/org/apache/spark/deploy/worker/CommandUtils.scala
index d689eb0..c04214d 100644
--- a/core/src/main/scala/org/apache/spark/deploy/worker/CommandUtils.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/worker/CommandUtils.scala
@@ -87,8 +87,8 @@
     }
 
     // set auth secret to env variable if needed
-    if (securityMgr.isAuthenticationEnabled) {
-      newEnvironment += (SecurityManager.ENV_AUTH_SECRET -> securityMgr.getSecretKey)
+    if (securityMgr.isAuthenticationEnabled()) {
+      newEnvironment += (SecurityManager.ENV_AUTH_SECRET -> securityMgr.getSecretKey())
     }
     // set SSL env variables if needed
     newEnvironment ++= securityMgr.getEnvironmentForSslRpcPasswords
diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
index 9fb66fa..44082ae 100755
--- a/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
@@ -103,7 +103,7 @@
   private val FUZZ_MULTIPLIER_INTERVAL_LOWER_BOUND = 0.500
   private val REGISTRATION_RETRY_FUZZ_MULTIPLIER = {
     val randomNumberGenerator = new Random(UUID.randomUUID.getMostSignificantBits)
-    randomNumberGenerator.nextDouble + FUZZ_MULTIPLIER_INTERVAL_LOWER_BOUND
+    randomNumberGenerator.nextDouble() + FUZZ_MULTIPLIER_INTERVAL_LOWER_BOUND
   }
   private val INITIAL_REGISTRATION_RETRY_INTERVAL_SECONDS = (math.round(10 *
     REGISTRATION_RETRY_FUZZ_MULTIPLIER))
diff --git a/core/src/main/scala/org/apache/spark/executor/ProcfsMetricsGetter.scala b/core/src/main/scala/org/apache/spark/executor/ProcfsMetricsGetter.scala
index 5448d7d..463552f 100644
--- a/core/src/main/scala/org/apache/spark/executor/ProcfsMetricsGetter.scala
+++ b/core/src/main/scala/org/apache/spark/executor/ProcfsMetricsGetter.scala
@@ -174,7 +174,7 @@
         val f = new File(pidDir, procfsStatFile)
         new BufferedReader(new InputStreamReader(new FileInputStream(f), UTF_8))
       }
-      Utils.tryWithResource(openReader) { in =>
+      Utils.tryWithResource(openReader()) { in =>
         val procInfo = in.readLine
         val procInfoSplit = procInfo.split(" ")
         val vmem = procInfoSplit(22).toLong
@@ -210,7 +210,7 @@
     if (!isAvailable) {
       return ProcfsMetrics(0, 0, 0, 0, 0, 0)
     }
-    val pids = computeProcessTree
+    val pids = computeProcessTree()
     var allMetrics = ProcfsMetrics(0, 0, 0, 0, 0, 0)
     for (p <- pids) {
       try {
diff --git a/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala b/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala
index 95ac877..f0d6cba 100644
--- a/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala
+++ b/core/src/main/scala/org/apache/spark/input/PortableDataStream.scala
@@ -100,7 +100,7 @@
     if (!processed) {
       val fileIn = new PortableDataStream(split, context, index)
       value = parseStream(fileIn)
-      key = fileIn.getPath
+      key = fileIn.getPath()
       processed = true
       true
     } else {
diff --git a/core/src/main/scala/org/apache/spark/internal/io/SparkHadoopWriter.scala b/core/src/main/scala/org/apache/spark/internal/io/SparkHadoopWriter.scala
index 4eeec63..0643ab3 100644
--- a/core/src/main/scala/org/apache/spark/internal/io/SparkHadoopWriter.scala
+++ b/core/src/main/scala/org/apache/spark/internal/io/SparkHadoopWriter.scala
@@ -83,14 +83,14 @@
       val ret = sparkContext.runJob(rdd, (context: TaskContext, iter: Iterator[(K, V)]) => {
         // SPARK-24552: Generate a unique "attempt ID" based on the stage and task attempt numbers.
         // Assumes that there won't be more than Short.MaxValue attempts, at least not concurrently.
-        val attemptId = (context.stageAttemptNumber << 16) | context.attemptNumber
+        val attemptId = (context.stageAttemptNumber() << 16) | context.attemptNumber()
 
         executeTask(
           context = context,
           config = config,
           jobTrackerId = jobTrackerId,
           commitJobId = commitJobId,
-          sparkPartitionId = context.partitionId,
+          sparkPartitionId = context.partitionId(),
           sparkAttemptNumber = attemptId,
           committer = committer,
           iterator = iter)
diff --git a/core/src/main/scala/org/apache/spark/launcher/LauncherBackend.scala b/core/src/main/scala/org/apache/spark/launcher/LauncherBackend.scala
index 77bbbd9..c70087d 100644
--- a/core/src/main/scala/org/apache/spark/launcher/LauncherBackend.scala
+++ b/core/src/main/scala/org/apache/spark/launcher/LauncherBackend.scala
@@ -67,13 +67,13 @@
   }
 
   def setAppId(appId: String): Unit = {
-    if (connection != null && isConnected) {
+    if (connection != null && isConnected()) {
       connection.send(new SetAppId(appId))
     }
   }
 
   def setState(state: SparkAppHandle.State): Unit = {
-    if (connection != null && isConnected && lastState != state) {
+    if (connection != null && isConnected() && lastState != state) {
       connection.send(new SetState(state))
       lastState = state
     }
diff --git a/core/src/main/scala/org/apache/spark/memory/UnifiedMemoryManager.scala b/core/src/main/scala/org/apache/spark/memory/UnifiedMemoryManager.scala
index 7f12789..73805c1 100644
--- a/core/src/main/scala/org/apache/spark/memory/UnifiedMemoryManager.scala
+++ b/core/src/main/scala/org/apache/spark/memory/UnifiedMemoryManager.scala
@@ -145,7 +145,7 @@
     }
 
     executionPool.acquireMemory(
-      numBytes, taskAttemptId, maybeGrowExecutionPool, () => computeMaxExecutionPoolSize)
+      numBytes, taskAttemptId, maybeGrowExecutionPool, () => computeMaxExecutionPoolSize())
   }
 
   override def acquireStorageMemory(
diff --git a/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala
index 2c4a228..777bc0a 100644
--- a/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala
+++ b/core/src/main/scala/org/apache/spark/metrics/MetricsSystem.scala
@@ -101,12 +101,12 @@
       registerSources()
     }
     registerSinks()
-    sinks.foreach(_.start)
+    sinks.foreach(_.start())
   }
 
   def stop(): Unit = {
     if (running) {
-      sinks.foreach(_.stop)
+      sinks.foreach(_.stop())
       registry.removeMatching((_: String, _: Metric) => true)
     } else {
       logWarning("Stopping a MetricsSystem that is not running")
diff --git a/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala b/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala
index 9f89c82..612a3da 100644
--- a/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala
@@ -66,7 +66,7 @@
    * Returns a future for retrieving the first num elements of the RDD.
    */
   def takeAsync(num: Int): FutureAction[Seq[T]] = self.withScope {
-    val callSite = self.context.getCallSite
+    val callSite = self.context.getCallSite()
     val localProperties = self.context.getLocalProperties
     // Cached thread pool to handle aggregation of subtasks.
     implicit val executionContext = AsyncRDDActions.futureExecutionContext
diff --git a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
index 0b5f6a3..9430a69 100644
--- a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
@@ -302,7 +302,7 @@
       private val inputFormat = getInputFormat(jobConf)
       HadoopRDD.addLocalConfiguration(
         new SimpleDateFormat("yyyyMMddHHmmss", Locale.US).format(createTime),
-        context.stageId, theSplit.index, context.attemptNumber, jobConf)
+        context.stageId(), theSplit.index, context.attemptNumber(), jobConf)
 
       reader =
         try {
diff --git a/core/src/main/scala/org/apache/spark/rdd/PipedRDD.scala b/core/src/main/scala/org/apache/spark/rdd/PipedRDD.scala
index 4f3683e..c4a35c4 100644
--- a/core/src/main/scala/org/apache/spark/rdd/PipedRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/PipedRDD.scala
@@ -118,7 +118,7 @@
       override def run(): Unit = {
         val err = proc.getErrorStream
         try {
-          for (line <- Source.fromInputStream(err)(encoding).getLines) {
+          for (line <- Source.fromInputStream(err)(encoding).getLines()) {
             // scalastyle:off println
             System.err.println(line)
             // scalastyle:on println
@@ -182,7 +182,7 @@
     }
 
     // Return an iterator that read lines from the process's stdout
-    val lines = Source.fromInputStream(proc.getInputStream)(encoding).getLines
+    val lines = Source.fromInputStream(proc.getInputStream)(encoding).getLines()
     new Iterator[String] {
       def next(): String = {
         if (!hasNext) {
diff --git a/core/src/main/scala/org/apache/spark/rdd/ReliableCheckpointRDD.scala b/core/src/main/scala/org/apache/spark/rdd/ReliableCheckpointRDD.scala
index 7339eb6..863bcd5 100644
--- a/core/src/main/scala/org/apache/spark/rdd/ReliableCheckpointRDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/ReliableCheckpointRDD.scala
@@ -247,7 +247,7 @@
   private def writePartitionerToCheckpointDir(
     sc: SparkContext, partitioner: Partitioner, checkpointDirPath: Path): Unit = {
     try {
-      val partitionerFilePath = new Path(checkpointDirPath, checkpointPartitionerFileName)
+      val partitionerFilePath = new Path(checkpointDirPath, checkpointPartitionerFileName())
       val bufferSize = sc.conf.get(BUFFER_SIZE)
       val fs = partitionerFilePath.getFileSystem(sc.hadoopConfiguration)
       val fileOutputStream = fs.create(partitionerFilePath, false, bufferSize)
@@ -276,14 +276,14 @@
       checkpointDirPath: String): Option[Partitioner] = {
     try {
       val bufferSize = sc.conf.get(BUFFER_SIZE)
-      val partitionerFilePath = new Path(checkpointDirPath, checkpointPartitionerFileName)
+      val partitionerFilePath = new Path(checkpointDirPath, checkpointPartitionerFileName())
       val fs = partitionerFilePath.getFileSystem(sc.hadoopConfiguration)
       val fileInputStream = fs.open(partitionerFilePath, bufferSize)
       val serializer = SparkEnv.get.serializer.newInstance()
       val partitioner = Utils.tryWithSafeFinally {
         val deserializeStream = serializer.deserializeStream(fileInputStream)
         Utils.tryWithSafeFinally {
-          deserializeStream.readObject[Partitioner]
+          deserializeStream.readObject[Partitioner]()
         } {
           deserializeStream.close()
         }
diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
index 230e49db..7241376 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
@@ -701,7 +701,7 @@
       val toVisit = waitingForVisit.remove(0)
       if (!visited(toVisit)) {
         visited += toVisit
-        Option(toVisit.getResourceProfile).foreach(resourceProfiles += _)
+        Option(toVisit.getResourceProfile()).foreach(resourceProfiles += _)
         toVisit.dependencies.foreach {
           case shuffleDep: ShuffleDependency[_, _, _] =>
             parents += shuffleDep
@@ -1605,7 +1605,7 @@
             val locs = taskIdToLocations(id)
             val part = partitions(id)
             stage.pendingPartitions += id
-            new ShuffleMapTask(stage.id, stage.latestInfo.attemptNumber, taskBinary,
+            new ShuffleMapTask(stage.id, stage.latestInfo.attemptNumber(), taskBinary,
               part, stage.numPartitions, locs, artifacts, properties, serializedTaskMetrics,
               Option(jobId), Option(sc.applicationId), sc.applicationAttemptId,
               stage.rdd.isBarrier())
@@ -1616,7 +1616,7 @@
             val p: Int = stage.partitions(id)
             val part = partitions(p)
             val locs = taskIdToLocations(id)
-            new ResultTask(stage.id, stage.latestInfo.attemptNumber,
+            new ResultTask(stage.id, stage.latestInfo.attemptNumber(),
               taskBinary, part, stage.numPartitions, locs, id, artifacts, properties,
               serializedTaskMetrics, Option(jobId), Option(sc.applicationId),
               sc.applicationAttemptId, stage.rdd.isBarrier())
@@ -1638,7 +1638,7 @@
       }
 
       taskScheduler.submitTasks(new TaskSet(
-        tasks.toArray, stage.id, stage.latestInfo.attemptNumber, jobId, properties,
+        tasks.toArray, stage.id, stage.latestInfo.attemptNumber(), jobId, properties,
         stage.resourceProfileId, shuffleId))
     } else {
       // Because we posted SparkListenerStageSubmitted earlier, we should mark
@@ -1939,10 +1939,10 @@
         val failedStage = stageIdToStage(task.stageId)
         val mapStage = shuffleIdToMapStage(shuffleId)
 
-        if (failedStage.latestInfo.attemptNumber != task.stageAttemptId) {
+        if (failedStage.latestInfo.attemptNumber() != task.stageAttemptId) {
           logInfo(s"Ignoring fetch failure from $task as it's from $failedStage attempt" +
             s" ${task.stageAttemptId} and there is a more recent attempt for that stage " +
-            s"(attempt ${failedStage.latestInfo.attemptNumber}) running")
+            s"(attempt ${failedStage.latestInfo.attemptNumber()}) running")
         } else {
           val ignoreStageFailure = ignoreDecommissionFetchFailure &&
             isExecutorDecommissioningOrDecommissioned(taskScheduler, bmAddress)
@@ -2166,10 +2166,10 @@
 
         // Always fail the current stage and retry all the tasks when a barrier task fail.
         val failedStage = stageIdToStage(task.stageId)
-        if (failedStage.latestInfo.attemptNumber != task.stageAttemptId) {
+        if (failedStage.latestInfo.attemptNumber() != task.stageAttemptId) {
           logInfo(s"Ignoring task failure from $task as it's from $failedStage attempt" +
             s" ${task.stageAttemptId} and there is a more recent attempt for that stage " +
-            s"(attempt ${failedStage.latestInfo.attemptNumber}) running")
+            s"(attempt ${failedStage.latestInfo.attemptNumber()}) running")
         } else {
           logInfo(s"Marking $failedStage (${failedStage.name}) as failed due to a barrier task " +
             "failed.")
diff --git a/core/src/main/scala/org/apache/spark/scheduler/StatsReportListener.scala b/core/src/main/scala/org/apache/spark/scheduler/StatsReportListener.scala
index be88148..1f12b46 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/StatsReportListener.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/StatsReportListener.scala
@@ -79,7 +79,7 @@
       x => info.completionTime.getOrElse(System.currentTimeMillis()) - x
     ).getOrElse("-")
 
-    s"Stage(${info.stageId}, ${info.attemptNumber}); Name: '${info.name}'; " +
+    s"Stage(${info.stageId}, ${info.attemptNumber()}); Name: '${info.name}'; " +
       s"Status: ${info.getStatusString}$failureReason; numTasks: ${info.numTasks}; " +
       s"Took: $timeTaken msec"
   }
diff --git a/core/src/main/scala/org/apache/spark/scheduler/Task.scala b/core/src/main/scala/org/apache/spark/scheduler/Task.scala
index 39667ea..1ecd185 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/Task.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/Task.scala
@@ -207,10 +207,10 @@
   def collectAccumulatorUpdates(taskFailed: Boolean = false): Seq[AccumulatorV2[_, _]] = {
     if (context != null) {
       // Note: internal accumulators representing task metrics always count failed values
-      context.taskMetrics.nonZeroInternalAccums() ++
+      context.taskMetrics().nonZeroInternalAccums() ++
         // zero value external accumulators may still be useful, e.g. SQLMetrics, we should not
         // filter them out.
-        context.taskMetrics.externalAccums.filter(a => !taskFailed || a.countFailedValues)
+        context.taskMetrics().externalAccums.filter(a => !taskFailed || a.countFailedValues)
     } else {
       Seq.empty
     }
diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
index fefca85..d00578e 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
@@ -1214,10 +1214,10 @@
   }
 
   private def waitBackendReady(): Unit = {
-    if (backend.isReady) {
+    if (backend.isReady()) {
       return
     }
-    while (!backend.isReady) {
+    while (!backend.isReady()) {
       // Might take a while for backend to be ready if it is waiting on resources.
       if (sc.stopped.get) {
         // For example: the master removes the application for some reason
diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
index de9c58e..6157a3e 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala
@@ -1152,7 +1152,7 @@
               // config executorDecommissionKillInterval. If the task is going to finish after
               // decommissioning, then we will eagerly speculate the task.
               val taskEndTimeBasedOnMedianDuration =
-                info.launchTime + successfulTaskDurations.percentile
+                info.launchTime + successfulTaskDurations.percentile()
               val executorDecomTime = decomState.startTime + executorDecommissionKillInterval.get
               executorDecomTime < taskEndTimeBasedOnMedianDuration
             }
@@ -1195,7 +1195,7 @@
     val numSuccessfulTasks = successfulTaskDurations.size()
     val timeMs = clock.getTimeMillis()
     if (numSuccessfulTasks >= minFinishedForSpeculation) {
-      val medianDuration = successfulTaskDurations.percentile
+      val medianDuration = successfulTaskDurations.percentile()
       val threshold = max(speculationMultiplier * medianDuration, minTimeToSpeculation)
       // TODO: Threshold should also look at standard deviation of task durations and have a lower
       // bound based on that.
diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
index 274f867..dd53757 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
@@ -248,7 +248,7 @@
           attributes, resources, resourceProfileId) =>
         if (executorDataMap.contains(executorId)) {
           context.sendFailure(new IllegalStateException(s"Duplicate executor ID: $executorId"))
-        } else if (scheduler.excludedNodes.contains(hostname) ||
+        } else if (scheduler.excludedNodes().contains(hostname) ||
             isExecutorExcluded(executorId, hostname)) {
           // If the cluster manager gives us an executor on an excluded node (because it
           // already started allocating those resources before we informed it of our exclusion,
@@ -718,7 +718,7 @@
   def sufficientResourcesRegistered(): Boolean = true
 
   override def isReady(): Boolean = {
-    if (sufficientResourcesRegistered) {
+    if (sufficientResourcesRegistered()) {
       logInfo("SchedulerBackend is ready for scheduling beginning after " +
         s"reached minRegisteredResourcesRatio: $minRegisteredRatio")
       return true
@@ -881,7 +881,7 @@
       // Note: it's possible that something else allocated an executor and we have
       // a negative delta, we can just avoid mutating the queue.
       while (toConsume > 0 && times.nonEmpty) {
-        val h = times.dequeue
+        val h = times.dequeue()
         if (h._1 > toConsume) {
           // Prepend updated first req to times, constant time op
           ((h._1 - toConsume, h._2)) +=: times
diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneSchedulerBackend.scala
index f1be78a..482e186 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneSchedulerBackend.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/StandaloneSchedulerBackend.scala
@@ -217,7 +217,7 @@
   override def applicationId(): String =
     Option(appId).getOrElse {
       logWarning("Application ID is not initialized yet.")
-      super.applicationId
+      super.applicationId()
     }
 
   /**
diff --git a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala
index 60af1ab..6130808 100644
--- a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala
+++ b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala
@@ -168,11 +168,11 @@
     // GenericDatum(Reader|Writer).
     def registerAvro[T <: GenericContainer]()(implicit ct: ClassTag[T]): Unit =
       kryo.register(ct.runtimeClass, new GenericAvroSerializer[T](avroSchemas))
-    registerAvro[GenericRecord]
-    registerAvro[GenericData.Record]
-    registerAvro[GenericData.Array[_]]
-    registerAvro[GenericData.EnumSymbol]
-    registerAvro[GenericData.Fixed]
+    registerAvro[GenericRecord]()
+    registerAvro[GenericData.Record]()
+    registerAvro[GenericData.Array[_]]()
+    registerAvro[GenericData.EnumSymbol]()
+    registerAvro[GenericData.Fixed]()
 
     // Use the default classloader when calling the user registrator.
     Utils.withContextClassLoader(classLoader) {
diff --git a/core/src/main/scala/org/apache/spark/status/AppStatusListener.scala b/core/src/main/scala/org/apache/spark/status/AppStatusListener.scala
index 0ae053d..63c202a 100644
--- a/core/src/main/scala/org/apache/spark/status/AppStatusListener.scala
+++ b/core/src/main/scala/org/apache/spark/status/AppStatusListener.scala
@@ -250,7 +250,7 @@
       }
       // Remove all RDD partitions that reference the removed executor
       liveRDDs.values.foreach { rdd =>
-        rdd.getPartitions.values
+        rdd.getPartitions().values
           .filter(_.executors.contains(event.executorId))
           .foreach { partition =>
             if (partition.executors.length == 1) {
@@ -812,7 +812,7 @@
 
   override def onStageCompleted(event: SparkListenerStageCompleted): Unit = {
     val maybeStage =
-      Option(liveStages.get((event.stageInfo.stageId, event.stageInfo.attemptNumber)))
+      Option(liveStages.get((event.stageInfo.stageId, event.stageInfo.attemptNumber())))
     maybeStage.foreach { stage =>
       val now = System.nanoTime()
       stage.info = event.stageInfo
@@ -860,7 +860,7 @@
       val removeStage = stage.activeTasks == 0
       update(stage, now, last = removeStage)
       if (removeStage) {
-        liveStages.remove((event.stageInfo.stageId, event.stageInfo.attemptNumber))
+        liveStages.remove((event.stageInfo.stageId, event.stageInfo.attemptNumber()))
       }
       if (stage.status == v1.StageStatus.COMPLETE) {
         appSummary = new AppSummary(appSummary.numCompletedJobs, appSummary.numCompletedStages + 1)
@@ -1209,7 +1209,7 @@
   }
 
   private def getOrCreateStage(info: StageInfo): LiveStage = {
-    val stage = liveStages.computeIfAbsent((info.stageId, info.attemptNumber),
+    val stage = liveStages.computeIfAbsent((info.stageId, info.attemptNumber()),
       (_: (Int, Int)) => new LiveStage(info))
     stage.info = info
     stage
@@ -1377,7 +1377,7 @@
   private def cleanupTasks(stage: LiveStage): Unit = {
     val countToDelete = calculateNumberToRemove(stage.savedTasks.get(), maxTasksPerStage).toInt
     if (countToDelete > 0) {
-      val stageKey = Array(stage.info.stageId, stage.info.attemptNumber)
+      val stageKey = Array(stage.info.stageId, stage.info.attemptNumber())
       val view = kvstore.view(classOf[TaskDataWrapper])
         .index(TaskIndexNames.COMPLETION_TIME)
         .parent(stageKey)
diff --git a/core/src/main/scala/org/apache/spark/status/ElementTrackingStore.scala b/core/src/main/scala/org/apache/spark/status/ElementTrackingStore.scala
index 2bc8f4d..4aef7f9 100644
--- a/core/src/main/scala/org/apache/spark/status/ElementTrackingStore.scala
+++ b/core/src/main/scala/org/apache/spark/status/ElementTrackingStore.scala
@@ -73,7 +73,7 @@
   private val executor: ExecutorService = if (conf.get(ASYNC_TRACKING_ENABLED)) {
     ThreadUtils.newDaemonSingleThreadExecutor("element-tracking-store-worker")
   } else {
-    ThreadUtils.sameThreadExecutorService
+    ThreadUtils.sameThreadExecutorService()
   }
 
   @volatile private var stopped = false
diff --git a/core/src/main/scala/org/apache/spark/status/LiveEntity.scala b/core/src/main/scala/org/apache/spark/status/LiveEntity.scala
index eb51cb9..efc6704 100644
--- a/core/src/main/scala/org/apache/spark/status/LiveEntity.scala
+++ b/core/src/main/scala/org/apache/spark/status/LiveEntity.scala
@@ -364,7 +364,7 @@
       executorLogs,
       memoryMetrics,
       excludedInStages,
-      Some(peakExecutorMetrics).filter(_.isSet),
+      Some(peakExecutorMetrics).filter(_.isSet()),
       attributes,
       resources,
       resourceProfileId,
@@ -408,7 +408,7 @@
       metrics.memoryBytesSpilled,
       metrics.diskBytesSpilled,
       isExcluded,
-      Some(peakExecutorMetrics).filter(_.isSet),
+      Some(peakExecutorMetrics).filter(_.isSet()),
       isExcluded)
     new ExecutorStageSummaryWrapper(stageId, attemptId, executorId, info)
   }
@@ -472,7 +472,7 @@
   val peakExecutorMetrics = new ExecutorMetrics()
 
   lazy val speculationStageSummary: LiveSpeculationStageSummary =
-    new LiveSpeculationStageSummary(info.stageId, info.attemptNumber)
+    new LiveSpeculationStageSummary(info.stageId, info.attemptNumber())
 
   // Used for cleanup of tasks after they reach the configured limit. Not written to the store.
   @volatile var cleaning = false
@@ -480,14 +480,14 @@
 
   def executorSummary(executorId: String): LiveExecutorStageSummary = {
     executorSummaries.getOrElseUpdate(executorId,
-      new LiveExecutorStageSummary(info.stageId, info.attemptNumber, executorId))
+      new LiveExecutorStageSummary(info.stageId, info.attemptNumber(), executorId))
   }
 
   def toApi(): v1.StageData = {
     new v1.StageData(
       status = status,
       stageId = info.stageId,
-      attemptId = info.attemptNumber,
+      attemptId = info.attemptNumber(),
       numTasks = info.numTasks,
       numActiveTasks = activeTasks,
       numCompleteTasks = completedTasks,
@@ -559,7 +559,7 @@
       speculationSummary = None,
       killedTasksSummary = killedSummary,
       resourceProfileId = info.resourceProfileId,
-      peakExecutorMetrics = Some(peakExecutorMetrics).filter(_.isSet),
+      peakExecutorMetrics = Some(peakExecutorMetrics).filter(_.isSet()),
       taskMetricsDistributions = None,
       executorMetricsDistributions = None,
       isShufflePushEnabled = info.isShufflePushEnabled,
diff --git a/core/src/main/scala/org/apache/spark/status/api/v1/PrometheusResource.scala b/core/src/main/scala/org/apache/spark/status/api/v1/PrometheusResource.scala
index ca088dc..8cfed4a 100644
--- a/core/src/main/scala/org/apache/spark/status/api/v1/PrometheusResource.scala
+++ b/core/src/main/scala/org/apache/spark/status/api/v1/PrometheusResource.scala
@@ -48,8 +48,8 @@
     store.executorList(true).foreach { executor =>
       val prefix = "metrics_executor_"
       val labels = Seq(
-        "application_id" -> store.applicationInfo.id,
-        "application_name" -> store.applicationInfo.name,
+        "application_id" -> store.applicationInfo().id,
+        "application_name" -> store.applicationInfo().name,
         "executor_id" -> executor.id
       ).map { case (k, v) => s"""$k="$v"""" }.mkString("{", ", ", "}")
       sb.append(s"${prefix}rddBlocks$labels ${executor.rddBlocks}\n")
diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala
index 454c770..aa9ba7c 100644
--- a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala
+++ b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala
@@ -1315,7 +1315,7 @@
     val taskAttemptId = taskContext.map(_.taskAttemptId())
     // SPARK-27666. When a task completes, Spark automatically releases all the blocks locked
     // by this task. We should not release any locks for a task that is already completed.
-    if (taskContext.isDefined && taskContext.get.isCompleted) {
+    if (taskContext.isDefined && taskContext.get.isCompleted()) {
       logWarning(s"Task ${taskAttemptId.get} already completed, not releasing lock for $blockId")
     } else {
       blockInfoManager.unlock(blockId, taskAttemptId)
diff --git a/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala b/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala
index ca111a8..948acb7 100644
--- a/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala
+++ b/core/src/main/scala/org/apache/spark/ui/UIWorkloadGenerator.scala
@@ -67,30 +67,30 @@
     def nextFloat(): Float = new Random().nextFloat()
 
     val jobs = Seq[(String, () => Long)](
-      ("Count", () => baseData.count),
-      ("Cache and Count", () => baseData.map(x => x).cache().count),
-      ("Single Shuffle", () => baseData.map(x => (x % 10, x)).reduceByKey(_ + _).count),
-      ("Entirely failed phase", () => baseData.map { x => throw new Exception(); 1 }.count),
+      ("Count", () => baseData.count()),
+      ("Cache and Count", () => baseData.map(x => x).cache().count()),
+      ("Single Shuffle", () => baseData.map(x => (x % 10, x)).reduceByKey(_ + _).count()),
+      ("Entirely failed phase", () => baseData.map { x => throw new Exception(); 1 }.count()),
       ("Partially failed phase", () => {
-        baseData.map{x =>
+        baseData.map { x =>
           val probFailure = (4.0 / NUM_PARTITIONS)
           if (nextFloat() < probFailure) {
             throw new Exception("This is a task failure")
           }
           1
-        }.count
+        }.count()
       }),
       ("Partially failed phase (longer tasks)", () => {
-        baseData.map{x =>
+        baseData.map { x =>
           val probFailure = (4.0 / NUM_PARTITIONS)
           if (nextFloat() < probFailure) {
             Thread.sleep(100)
             throw new Exception("This is a task failure")
           }
           1
-        }.count
+        }.count()
       }),
-      ("Job with delays", () => baseData.map(x => Thread.sleep(100)).count)
+      ("Job with delays", () => baseData.map(x => Thread.sleep(100)).count())
     )
 
     val barrier = new Semaphore(-nJobSet * jobs.size + 1)
diff --git a/core/src/main/scala/org/apache/spark/ui/scope/RDDOperationGraph.scala b/core/src/main/scala/org/apache/spark/ui/scope/RDDOperationGraph.scala
index e531bcf..9a035e0 100644
--- a/core/src/main/scala/org/apache/spark/ui/scope/RDDOperationGraph.scala
+++ b/core/src/main/scala/org/apache/spark/ui/scope/RDDOperationGraph.scala
@@ -136,7 +136,7 @@
     // Use a special prefix here to differentiate this cluster from other operation clusters
     val stageClusterId = STAGE_CLUSTER_PREFIX + stage.stageId
     val stageClusterName = s"Stage ${stage.stageId}" +
-      { if (stage.attemptNumber == 0) "" else s" (attempt ${stage.attemptNumber})" }
+      { if (stage.attemptNumber() == 0) "" else s" (attempt ${stage.attemptNumber()})" }
     val rootCluster = new RDDOperationCluster(stageClusterId, false, stageClusterName)
 
     var rootNodeCount = 0
diff --git a/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala b/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala
index 54c267c..29fb020 100644
--- a/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala
+++ b/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala
@@ -685,7 +685,7 @@
     }
 
     while (!stack.isEmpty) {
-      val currentId = stack.pop
+      val currentId = stack.pop()
       visited += currentId
 
       val currentClass = currentId.cls
diff --git a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala
index 6525bd3..b3c208b 100644
--- a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala
+++ b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala
@@ -387,7 +387,7 @@
       includeAccumulables: Boolean): Unit = {
     g.writeStartObject()
     g.writeNumberField("Stage ID", stageInfo.stageId)
-    g.writeNumberField("Stage Attempt ID", stageInfo.attemptNumber)
+    g.writeNumberField("Stage Attempt ID", stageInfo.attemptNumber())
     g.writeStringField("Stage Name", stageInfo.name)
     g.writeNumberField ("Number of Tasks", stageInfo.numTasks)
     g.writeArrayFieldStart("RDD Info")
diff --git a/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala
index 10ff801..704aeae 100644
--- a/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala
+++ b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala
@@ -197,7 +197,7 @@
   private def estimate(obj: AnyRef, visited: IdentityHashMap[AnyRef, AnyRef]): Long = {
     val state = new SearchState(visited)
     state.enqueue(obj)
-    while (!state.isFinished) {
+    while (!state.isFinished()) {
       visitSingleObject(state.dequeue(), state)
     }
     state.size
diff --git a/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala b/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala
index 71f3b0b..3afbe32 100644
--- a/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala
+++ b/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala
@@ -565,7 +565,7 @@
       if (hasSpilled) {
         false
       } else {
-        logInfo(s"Task ${context.taskAttemptId} force spilling in-memory map to disk and " +
+        logInfo(s"Task ${context.taskAttemptId()} force spilling in-memory map to disk and " +
           s"it will release ${org.apache.spark.util.Utils.bytesToString(getUsed())} memory")
         val nextUpstream = spillMemoryIteratorToDisk(upstream)
         assert(!upstream.hasNext)
@@ -581,7 +581,7 @@
     }
 
     def toCompletionIterator: CompletionIterator[(K, C), SpillableIterator] = {
-      CompletionIterator[(K, C), SpillableIterator](this, this.destroy)
+      CompletionIterator[(K, C), SpillableIterator](this, this.destroy())
     }
 
     def readNext(): (K, C) = SPILL_LOCK.synchronized {
diff --git a/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala b/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala
index 4250172..5051b88 100644
--- a/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala
+++ b/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala
@@ -816,7 +816,7 @@
         false
       } else {
         val inMemoryIterator = new WritablePartitionedIterator[K, C](upstream)
-        logInfo(s"Task ${TaskContext.get().taskAttemptId} force spilling in-memory map to disk " +
+        logInfo(s"Task ${TaskContext.get().taskAttemptId()} force spilling in-memory map to disk " +
           s"and it will release ${org.apache.spark.util.Utils.bytesToString(getUsed())} memory")
         val spillFile = spillMemoryIteratorToDisk(inMemoryIterator)
         forceSpillFiles += spillFile
diff --git a/core/src/main/scala/org/apache/spark/util/collection/ImmutableBitSet.scala b/core/src/main/scala/org/apache/spark/util/collection/ImmutableBitSet.scala
index 82413f4..8047f50 100644
--- a/core/src/main/scala/org/apache/spark/util/collection/ImmutableBitSet.scala
+++ b/core/src/main/scala/org/apache/spark/util/collection/ImmutableBitSet.scala
@@ -28,7 +28,7 @@
   {
     val bitsIterator = bitsToSet.iterator
     while (bitsIterator.hasNext) {
-      super.set(bitsIterator.next)
+      super.set(bitsIterator.next())
     }
   }
 
diff --git a/core/src/main/scala/org/apache/spark/util/collection/PartitionedPairBuffer.scala b/core/src/main/scala/org/apache/spark/util/collection/PartitionedPairBuffer.scala
index 652d8c0..b43a8c7 100644
--- a/core/src/main/scala/org/apache/spark/util/collection/PartitionedPairBuffer.scala
+++ b/core/src/main/scala/org/apache/spark/util/collection/PartitionedPairBuffer.scala
@@ -77,7 +77,7 @@
     : Iterator[((Int, K), V)] = {
     val comparator = keyComparator.map(partitionKeyComparator).getOrElse(partitionComparator)
     new Sorter(new KVArraySortDataFormat[(Int, K), AnyRef]).sort(data, 0, curSize, comparator)
-    iterator
+    iterator()
   }
 
   private def iterator(): Iterator[((Int, K), V)] = new Iterator[((Int, K), V)] {
diff --git a/core/src/main/scala/org/apache/spark/util/collection/PercentileHeap.scala b/core/src/main/scala/org/apache/spark/util/collection/PercentileHeap.scala
index ac6bc0e..61f95f8 100644
--- a/core/src/main/scala/org/apache/spark/util/collection/PercentileHeap.scala
+++ b/core/src/main/scala/org/apache/spark/util/collection/PercentileHeap.scala
@@ -47,16 +47,16 @@
    * returned `sorted(p)` where `p = (sorted.length * percentage).toInt`.
    */
   def percentile(): Double = {
-    if (isEmpty) throw new NoSuchElementException("empty")
+    if (isEmpty()) throw new NoSuchElementException("empty")
     largeHeap.peek
   }
 
   def insert(x: Double): Unit = {
-    if (isEmpty) {
+    if (isEmpty()) {
       largeHeap.offer(x)
     } else {
       val p = largeHeap.peek
-      val growBot = ((size + 1) * percentage).toInt > smallHeap.size
+      val growBot = ((size() + 1) * percentage).toInt > smallHeap.size
       if (growBot) {
         if (x < p) {
           smallHeap.offer(-x)
diff --git a/core/src/main/scala/org/apache/spark/util/random/RandomSampler.scala b/core/src/main/scala/org/apache/spark/util/random/RandomSampler.scala
index 6dd2bee..8bf2a70 100644
--- a/core/src/main/scala/org/apache/spark/util/random/RandomSampler.scala
+++ b/core/src/main/scala/org/apache/spark/util/random/RandomSampler.scala
@@ -39,7 +39,7 @@
 
   /** take a random sample */
   def sample(items: Iterator[T]): Iterator[U] =
-    items.filter(_ => sample > 0).asInstanceOf[Iterator[U]]
+    items.filter(_ => sample() > 0).asInstanceOf[Iterator[U]]
 
   /**
    * Whether to sample the next item or not.
diff --git a/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala b/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala
index 5434e82..b78bb1f 100644
--- a/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ContextCleanerSuite.scala
@@ -89,7 +89,7 @@
     val rdd: RDD[_] = Random.nextInt(3) match {
       case 0 => newRDD()
       case 1 => newShuffleRDD()
-      case 2 => newPairRDD.join(newPairRDD())
+      case 2 => newPairRDD().join(newPairRDD())
     }
     if (Random.nextBoolean()) rdd.persist()
     rdd.count()
@@ -288,7 +288,7 @@
     val rddBuffer = (1 to numRdds).map(i => randomRdd()).toBuffer
     val broadcastBuffer = (1 to numBroadcasts).map(i => newBroadcast()).toBuffer
     val rddIds = sc.persistentRdds.keys.toSeq
-    val shuffleIds = 0 until sc.newShuffleId
+    val shuffleIds = 0 until sc.newShuffleId()
     val broadcastIds = broadcastBuffer.map(_.id)
 
     val preGCTester = new CleanerTester(sc, rddIds, shuffleIds, broadcastIds.toSeq)
@@ -328,7 +328,7 @@
     val rddBuffer = (1 to numRdds).map(i => randomRdd()).toBuffer
     val broadcastBuffer = (1 to numBroadcasts).map(i => newBroadcast()).toBuffer
     val rddIds = sc.persistentRdds.keys.toSeq
-    val shuffleIds = 0 until sc.newShuffleId
+    val shuffleIds = 0 until sc.newShuffleId()
     val broadcastIds = broadcastBuffer.map(_.id)
 
     val preGCTester = new CleanerTester(sc, rddIds, shuffleIds, broadcastIds.toSeq)
diff --git a/core/src/test/scala/org/apache/spark/DistributedSuite.scala b/core/src/test/scala/org/apache/spark/DistributedSuite.scala
index ce1df3a..e156533 100644
--- a/core/src/test/scala/org/apache/spark/DistributedSuite.scala
+++ b/core/src/test/scala/org/apache/spark/DistributedSuite.scala
@@ -177,7 +177,7 @@
     TestUtils.waitUntilExecutorsUp(sc, 3, 60000)
     val data = sc.parallelize(1 to 1000, 10)
     val cachedData = data.persist(storageLevel)
-    assert(cachedData.count === 1000)
+    assert(cachedData.count() === 1000)
     assert(sc.getRDDStorageInfo.filter(_.id == cachedData.id).map(_.numCachedPartitions).sum ===
       data.getNumPartitions)
     // Get all the locations of the first partition and try to fetch the partitions
@@ -263,9 +263,9 @@
     DistributedSuite.amMaster = true
     sc = new SparkContext(clusterUrl, "test")
     val data = sc.parallelize(Seq(true, true), 2)
-    assert(data.count === 2) // force executors to start
-    assert(data.map(markNodeIfIdentity).collect.size === 2)
-    assert(data.map(failOnMarkedIdentity).collect.size === 2)
+    assert(data.count() === 2) // force executors to start
+    assert(data.map(markNodeIfIdentity).collect().size === 2)
+    assert(data.map(failOnMarkedIdentity).collect().size === 2)
   }
 
   test("recover from repeated node failures during shuffle-map") {
@@ -274,9 +274,9 @@
     sc = new SparkContext(clusterUrl, "test")
     for (i <- 1 to 3) {
       val data = sc.parallelize(Seq(true, false), 2)
-      assert(data.count === 2)
-      assert(data.map(markNodeIfIdentity).collect.size === 2)
-      assert(data.map(failOnMarkedIdentity).map(x => x -> x).groupByKey.count === 2)
+      assert(data.count() === 2)
+      assert(data.map(markNodeIfIdentity).collect().size === 2)
+      assert(data.map(failOnMarkedIdentity).map(x => x -> x).groupByKey().count() === 2)
     }
   }
 
@@ -286,8 +286,8 @@
     sc = new SparkContext(clusterUrl, "test")
     for (i <- 1 to 3) {
       val data = sc.parallelize(Seq(true, true), 2)
-      assert(data.count === 2)
-      assert(data.map(markNodeIfIdentity).collect.size === 2)
+      assert(data.count() === 2)
+      assert(data.map(markNodeIfIdentity).collect().size === 2)
       // This relies on mergeCombiners being used to perform the actual reduce for this
       // test to actually be testing what it claims.
       val grouped = data.map(x => x -> x).combineByKey(
@@ -295,7 +295,7 @@
                       (x: Boolean, y: Boolean) => x,
                       (x: Boolean, y: Boolean) => failOnMarkedIdentity(x)
                     )
-      assert(grouped.collect.size === 1)
+      assert(grouped.collect().size === 1)
     }
   }
 
@@ -309,14 +309,14 @@
       val data = sc.parallelize(Seq(true, false, false, false), 4)
       data.persist(StorageLevel.MEMORY_ONLY_2)
 
-      assert(data.count === 4)
-      assert(data.map(markNodeIfIdentity).collect.size === 4)
-      assert(data.map(failOnMarkedIdentity).collect.size === 4)
+      assert(data.count() === 4)
+      assert(data.map(markNodeIfIdentity).collect().size === 4)
+      assert(data.map(failOnMarkedIdentity).collect().size === 4)
 
       // Create a new replicated RDD to make sure that cached peer information doesn't cause
       // problems.
       val data2 = sc.parallelize(Seq(true, true), 2).persist(StorageLevel.MEMORY_ONLY_2)
-      assert(data2.count === 2)
+      assert(data2.count() === 2)
     }
   }
 
@@ -325,7 +325,7 @@
     sc = new SparkContext("local-cluster[3,1,1024]", "test")
     val data = sc.parallelize(Seq(true, false, false, false), 4)
     data.persist(StorageLevel.MEMORY_ONLY_2)
-    data.count
+    data.count()
     assert(sc.persistentRdds.nonEmpty)
     data.unpersist(blocking = true)
     assert(sc.persistentRdds.isEmpty)
diff --git a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala
index 41d674f..e1da2b6 100644
--- a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala
@@ -180,7 +180,7 @@
     val execReqs = new ExecutorResourceRequests().cores(4).resource("gpu", 4)
     val taskReqs = new TaskResourceRequests().cpus(1).resource("gpu", 1)
     rp1.require(execReqs).require(taskReqs)
-    val rprof1 = rp1.build
+    val rprof1 = rp1.build()
     rpManager.addResourceProfile(rprof1)
     post(SparkListenerStageSubmitted(createStageInfo(1, 1000, rp = rprof1)))
     val updatesNeeded =
@@ -277,7 +277,7 @@
     val execReqs = new ExecutorResourceRequests().cores(2).resource("gpu", 2)
     val taskReqs = new TaskResourceRequests().cpus(1).resource("gpu", 1)
     rp1.require(execReqs).require(taskReqs)
-    val rprof1 = rp1.build
+    val rprof1 = rp1.build()
     rpManager.addResourceProfile(rprof1)
     when(client.requestTotalExecutors(any(), any(), any())).thenReturn(true)
     post(SparkListenerStageSubmitted(createStageInfo(1, 4, rp = rprof1)))
@@ -292,12 +292,12 @@
     val execReqs = new ExecutorResourceRequests().cores(4).resource("gpu", 4)
     val taskReqs = new TaskResourceRequests().cpus(1).resource("gpu", 1)
     rp1.require(execReqs).require(taskReqs)
-    val rprof1 = rp1.build
+    val rprof1 = rp1.build()
     val rp2 = new ResourceProfileBuilder()
     val execReqs2 = new ExecutorResourceRequests().cores(1)
     val taskReqs2 = new TaskResourceRequests().cpus(1)
     rp2.require(execReqs2).require(taskReqs2)
-    val rprof2 = rp2.build
+    val rprof2 = rp2.build()
     rpManager.addResourceProfile(rprof1)
     rpManager.addResourceProfile(rprof2)
     post(SparkListenerStageSubmitted(createStageInfo(1, 10, rp = rprof1)))
diff --git a/core/src/test/scala/org/apache/spark/FileSuite.scala b/core/src/test/scala/org/apache/spark/FileSuite.scala
index 64e3df7..8977b3b 100644
--- a/core/src/test/scala/org/apache/spark/FileSuite.scala
+++ b/core/src/test/scala/org/apache/spark/FileSuite.scala
@@ -86,11 +86,11 @@
     data.saveAsTextFile(compressedOutputDir, classOf[DefaultCodec])
 
     val normalFile = new File(normalDir, "part-00000")
-    val normalContent = sc.textFile(normalDir).collect
+    val normalContent = sc.textFile(normalDir).collect()
     assert(normalContent === Array.fill(10000)("a"))
 
     val compressedFile = new File(compressedOutputDir, "part-00000" + codec.getDefaultExtension)
-    val compressedContent = sc.textFile(compressedOutputDir).collect
+    val compressedContent = sc.textFile(compressedOutputDir).collect()
     assert(compressedContent === Array.fill(10000)("a"))
 
     assert(compressedFile.length < normalFile.length)
@@ -125,11 +125,11 @@
       data.saveAsSequenceFile(compressedOutputDir, Some(codec.getClass))
 
       val normalFile = new File(normalDir, "part-00000")
-      val normalContent = sc.sequenceFile[String, String](normalDir).collect
+      val normalContent = sc.sequenceFile[String, String](normalDir).collect()
       assert(normalContent === Array.fill(100)(("abc", "abc")))
 
       val compressedFile = new File(compressedOutputDir, "part-00000" + codec.getDefaultExtension)
-      val compressedContent = sc.sequenceFile[String, String](compressedOutputDir).collect
+      val compressedContent = sc.sequenceFile[String, String](compressedOutputDir).collect()
       assert(compressedContent === Array.fill(100)(("abc", "abc")))
 
       assert(compressedFile.length < normalFile.length)
@@ -288,7 +288,7 @@
     val (infile, indata) = inRdd.collect().head
     // Make sure the name and array match
     assert(infile.contains(outFile.toURI.getPath)) // a prefix may get added
-    assert(indata.toArray === testOutput)
+    assert(indata.toArray() === testOutput)
   }
 
   test("portabledatastream caching tests") {
@@ -298,7 +298,7 @@
     val inRdd = sc.binaryFiles(outFile.getAbsolutePath).cache()
     inRdd.foreach(_._2.toArray()) // force the file to read
     // Try reading the output back as an object file
-    assert(inRdd.values.collect().head.toArray === testOutput)
+    assert(inRdd.values.collect().head.toArray() === testOutput)
   }
 
   test("portabledatastream persist disk storage") {
@@ -307,7 +307,7 @@
     val outFile = writeBinaryData(testOutput, 1)
     val inRdd = sc.binaryFiles(outFile.getAbsolutePath).persist(StorageLevel.DISK_ONLY)
     inRdd.foreach(_._2.toArray()) // force the file to read
-    assert(inRdd.values.collect().head.toArray === testOutput)
+    assert(inRdd.values.collect().head.toArray() === testOutput)
   }
 
   test("portabledatastream flatmap tests") {
@@ -320,7 +320,7 @@
     val copyArr = copyRdd.collect()
     assert(copyArr.length == numOfCopies)
     for (i <- copyArr.indices) {
-      assert(copyArr(i).toArray === testOutput)
+      assert(copyArr(i).toArray() === testOutput)
     }
   }
 
@@ -354,7 +354,7 @@
       "mapreduce.input.fileinputformat.split.minsize.per.rack", 5123456)
 
     val (_, data) = sc.binaryFiles(outFile.getAbsolutePath).collect().head
-    assert(data.toArray === testOutput)
+    assert(data.toArray() === testOutput)
   }
 
   test("fixed record length binary file as byte array") {
@@ -363,7 +363,7 @@
     val testOutputCopies = 10
     val outFile = writeBinaryData(testOutput, testOutputCopies)
     val inRdd = sc.binaryRecords(outFile.getAbsolutePath, testOutput.length)
-    assert(inRdd.count == testOutputCopies)
+    assert(inRdd.count() == testOutputCopies)
     val inArr = inRdd.collect()
     for (i <- inArr.indices) {
       assert(inArr(i) === testOutput.map(b => (b + i).toByte))
@@ -699,7 +699,7 @@
     intercept[org.apache.hadoop.mapreduce.lib.input.InvalidInputException] {
       // Exception happens when NewHadoopRDD.getPartitions
       sc.newAPIHadoopFile(deletedPath.toString, classOf[NewTextInputFormat],
-        classOf[LongWritable], classOf[Text]).collect
+        classOf[LongWritable], classOf[Text]).collect()
     }
 
     e = intercept[SparkException] {
diff --git a/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala b/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala
index 95ef417..e3463a9 100644
--- a/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala
+++ b/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala
@@ -77,7 +77,7 @@
     sc = spy[SparkContext](new SparkContext(conf))
     scheduler = mock(classOf[TaskSchedulerImpl])
     when(sc.taskScheduler).thenReturn(scheduler)
-    when(scheduler.excludedNodes).thenReturn(Predef.Set[String]())
+    when(scheduler.excludedNodes()).thenReturn(Predef.Set[String]())
     when(scheduler.sc).thenReturn(sc)
     heartbeatReceiverClock = new ManualClock
     heartbeatReceiver = new HeartbeatReceiver(sc, heartbeatReceiverClock)
diff --git a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala
index fb2c44b..23225b2 100644
--- a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala
+++ b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala
@@ -60,7 +60,7 @@
     testCount()
     testTake()
     // Make sure we can still launch tasks.
-    assert(sc.parallelize(1 to 10, 2).count === 10)
+    assert(sc.parallelize(1 to 10, 2).count() === 10)
   }
 
   test("local mode, fair scheduler") {
@@ -71,7 +71,7 @@
     testCount()
     testTake()
     // Make sure we can still launch tasks.
-    assert(sc.parallelize(1 to 10, 2).count === 10)
+    assert(sc.parallelize(1 to 10, 2).count() === 10)
   }
 
   test("cluster mode, FIFO scheduler") {
@@ -80,7 +80,7 @@
     testCount()
     testTake()
     // Make sure we can still launch tasks.
-    assert(sc.parallelize(1 to 10, 2).count === 10)
+    assert(sc.parallelize(1 to 10, 2).count() === 10)
   }
 
   test("cluster mode, fair scheduler") {
@@ -91,7 +91,7 @@
     testCount()
     testTake()
     // Make sure we can still launch tasks.
-    assert(sc.parallelize(1 to 10, 2).count === 10)
+    assert(sc.parallelize(1 to 10, 2).count() === 10)
   }
 
   test("do not put partially executed partitions into cache") {
diff --git a/core/src/test/scala/org/apache/spark/PartitioningSuite.scala b/core/src/test/scala/org/apache/spark/PartitioningSuite.scala
index 1a3259c..eea7753 100644
--- a/core/src/test/scala/org/apache/spark/PartitioningSuite.scala
+++ b/core/src/test/scala/org/apache/spark/PartitioningSuite.scala
@@ -241,13 +241,13 @@
     // Run the partitions, including the consecutive empty ones, through StatCounter
     val stats: StatCounter = rdd.stats()
     assert(abs(6.0 - stats.sum) < 0.01)
-    assert(abs(6.0/2 - rdd.mean) < 0.01)
-    assert(abs(1.0 - rdd.variance) < 0.01)
-    assert(abs(1.0 - rdd.stdev) < 0.01)
-    assert(abs(rdd.variance - rdd.popVariance) < 1e-14)
-    assert(abs(rdd.stdev - rdd.popStdev) < 1e-14)
-    assert(abs(2.0 - rdd.sampleVariance) < 1e-14)
-    assert(abs(Math.sqrt(2.0) - rdd.sampleStdev) < 1e-14)
+    assert(abs(6.0/2 - rdd.mean()) < 0.01)
+    assert(abs(1.0 - rdd.variance()) < 0.01)
+    assert(abs(1.0 - rdd.stdev()) < 0.01)
+    assert(abs(rdd.variance() - rdd.popVariance()) < 1e-14)
+    assert(abs(rdd.stdev() - rdd.popStdev()) < 1e-14)
+    assert(abs(2.0 - rdd.sampleVariance()) < 1e-14)
+    assert(abs(Math.sqrt(2.0) - rdd.sampleStdev()) < 1e-14)
     assert(stats.max === 4.0)
     assert(stats.min === 2.0)
 
diff --git a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
index 0b6fce5..d403f94 100644
--- a/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ShuffleSuite.scala
@@ -73,7 +73,7 @@
     c.setSerializer(new KryoSerializer(conf))
     val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[_, _, _]].shuffleId
 
-    assert(c.count === 10)
+    assert(c.count() === 10)
 
     // All blocks must have non-zero size
     (0 until NUM_BLOCKS).foreach { id =>
@@ -95,7 +95,7 @@
       NonJavaSerializableClass,
       NonJavaSerializableClass](b, new HashPartitioner(3))
     c.setSerializer(new KryoSerializer(conf))
-    assert(c.count === 10)
+    assert(c.count() === 10)
   }
 
   test("zero sized blocks") {
@@ -113,7 +113,7 @@
       .setSerializer(new KryoSerializer(conf))
 
     val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[_, _, _]].shuffleId
-    assert(c.count === 4)
+    assert(c.count() === 4)
 
     val blockSizes = (0 until NUM_BLOCKS).flatMap { id =>
       val statuses = SparkEnv.get.mapOutputTracker.getMapSizesByExecutorId(shuffleId, id)
@@ -138,7 +138,7 @@
     val c = new ShuffledRDD[Int, Int, Int](b, new HashPartitioner(NUM_BLOCKS))
 
     val shuffleId = c.dependencies.head.asInstanceOf[ShuffleDependency[_, _, _]].shuffleId
-    assert(c.count === 4)
+    assert(c.count() === 4)
 
     val blockSizes = (0 until NUM_BLOCKS).flatMap { id =>
       val statuses = SparkEnv.get.mapOutputTracker.getMapSizesByExecutorId(shuffleId, id)
diff --git a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala
index 4145975..e140180 100644
--- a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala
+++ b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala
@@ -852,8 +852,8 @@
     sc.addSparkListener(listener)
     sc.range(0, 2).groupBy((x: Long) => x % 2, 2).map { case (x, _) =>
       val context = org.apache.spark.TaskContext.get()
-      if (context.stageAttemptNumber == 0) {
-        if (context.partitionId == 0) {
+      if (context.stageAttemptNumber() == 0) {
+        if (context.partitionId() == 0) {
           // Make the first task in the first stage attempt fail.
           throw new FetchFailedException(SparkEnv.get.blockManager.blockManagerId, 0, 0L, 0, 0,
             new java.io.IOException("fake"))
diff --git a/core/src/test/scala/org/apache/spark/SparkFunSuite.scala b/core/src/test/scala/org/apache/spark/SparkFunSuite.scala
index cd77d89..e3792eb 100644
--- a/core/src/test/scala/org/apache/spark/SparkFunSuite.scala
+++ b/core/src/test/scala/org/apache/spark/SparkFunSuite.scala
@@ -200,7 +200,7 @@
 
   protected def logForFailedTest(): Unit = {
     LocalSparkCluster.get.foreach { localCluster =>
-      val workerLogfiles = localCluster.workerLogfiles
+      val workerLogfiles = localCluster.workerLogfiles()
       if (workerLogfiles.nonEmpty) {
         logInfo("\n\n===== EXTRA LOGS FOR THE FAILED TEST\n")
         workerLogfiles.foreach { logFile =>
diff --git a/core/src/test/scala/org/apache/spark/ThreadAudit.scala b/core/src/test/scala/org/apache/spark/ThreadAudit.scala
index 538cf3c9..a1c2d60 100644
--- a/core/src/test/scala/org/apache/spark/ThreadAudit.scala
+++ b/core/src/test/scala/org/apache/spark/ThreadAudit.scala
@@ -122,7 +122,7 @@
   }
 
   private def runningThreadNames(): Set[String] = {
-    runningThreads.map(_.getName).toSet
+    runningThreads().map(_.getName)
   }
 
   private def runningThreads(): Set[Thread] = {
diff --git a/core/src/test/scala/org/apache/spark/UnpersistSuite.scala b/core/src/test/scala/org/apache/spark/UnpersistSuite.scala
index ff6ee79..fc70e13 100644
--- a/core/src/test/scala/org/apache/spark/UnpersistSuite.scala
+++ b/core/src/test/scala/org/apache/spark/UnpersistSuite.scala
@@ -28,7 +28,7 @@
   test("unpersist RDD") {
     sc = new SparkContext("local", "test")
     val rdd = sc.makeRDD(Array(1, 2, 3, 4), 2).cache()
-    rdd.count
+    rdd.count()
     assert(sc.persistentRdds.nonEmpty)
     rdd.unpersist(blocking = true)
     assert(sc.persistentRdds.isEmpty)
diff --git a/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala b/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala
index 5511852..0b33e2a 100644
--- a/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala
+++ b/core/src/test/scala/org/apache/spark/benchmark/Benchmark.scala
@@ -105,7 +105,7 @@
       println("  Running case: " + c.name)
       measure(valuesPerIteration, c.numIters)(c.fn)
     }
-    println
+    println()
 
     val firstBest = results.head.bestMs
     // The results are going to be processor specific so it is useful to include that.
@@ -125,7 +125,7 @@
         "%6.1f" format (1000 / result.bestRate),
         "%3.1fX" format (firstBest / result.bestMs))
     }
-    out.println
+    out.println()
     // scalastyle:on
   }
 
@@ -136,7 +136,7 @@
   def measure(num: Long, overrideNumIters: Int)(f: Timer => Unit): Result = {
     System.gc()  // ensures garbage from previous cases don't impact this one
     val warmupDeadline = warmupTime.fromNow
-    while (!warmupDeadline.isOverdue) {
+    while (!warmupDeadline.isOverdue()) {
       f(new Benchmark.Timer(-1))
     }
     val minIters = if (overrideNumIters != 0) overrideNumIters else minNumIters
diff --git a/core/src/test/scala/org/apache/spark/deploy/DecommissionWorkerSuite.scala b/core/src/test/scala/org/apache/spark/deploy/DecommissionWorkerSuite.scala
index 55d8535..b22c07d 100644
--- a/core/src/test/scala/org/apache/spark/deploy/DecommissionWorkerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/DecommissionWorkerSuite.scala
@@ -213,7 +213,7 @@
     TestUtils.waitUntilExecutorsUp(sc, 2, 60000)
 
     val executorIdToWorkerInfo = getExecutorToWorkerAssignments
-    val executorToDecom = executorIdToWorkerInfo.keysIterator.next
+    val executorToDecom = executorIdToWorkerInfo.keysIterator.next()
 
     // The task code below cannot call executorIdToWorkerInfo, so we need to pre-compute
     // the worker to decom to force it to be serialized into the task.
@@ -249,7 +249,7 @@
       }, preservesPartitioning = true)
         .repartition(1).mapPartitions(iter => {
         val context = TaskContext.get()
-        if (context.attemptNumber == 0 && context.stageAttemptNumber() == 0) {
+        if (context.attemptNumber() == 0 && context.stageAttemptNumber() == 0) {
           // Wait a bit for the decommissioning to be triggered in the listener
           Thread.sleep(5000)
           // MapIndex is explicitly -1 to force the entire host to be decommissioned
diff --git a/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala b/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala
index 5d60aad..98f475e 100644
--- a/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/LogUrlsStandaloneSuite.scala
@@ -59,7 +59,7 @@
     sc.parallelize(1 to 100, 4).map(_.toString).count()
 
     sc.listenerBus.waitUntilEmpty()
-    val listeners = sc.listenerBus.findListenersByClass[SaveExecutorInfo]
+    val listeners = sc.listenerBus.findListenersByClass[SaveExecutorInfo]()
     assert(listeners.size === 1)
     val listener = listeners(0)
     listener.addedExecutorInfos.values.foreach { info =>
diff --git a/core/src/test/scala/org/apache/spark/deploy/history/BasicEventFilterBuilderSuite.scala b/core/src/test/scala/org/apache/spark/deploy/history/BasicEventFilterBuilderSuite.scala
index c905797..c681093 100644
--- a/core/src/test/scala/org/apache/spark/deploy/history/BasicEventFilterBuilderSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/history/BasicEventFilterBuilderSuite.scala
@@ -83,12 +83,12 @@
     // Fail one of the tasks, re-start it.
     time += 1
     s0Tasks.head.markFinished(TaskState.FAILED, time)
-    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber(),
       "taskType", TaskResultLost, s0Tasks.head, new ExecutorMetrics, null))
 
     time += 1
     val reattempt = createTaskWithNewAttempt(s0Tasks.head, time)
-    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber(),
       reattempt))
 
     // Succeed all tasks in stage 0.
@@ -97,7 +97,7 @@
     time += 1
     pending.foreach { task =>
       task.markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber,
+      listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber(),
         "taskType", Success, task, new ExecutorMetrics, TaskMetrics.empty))
     }
 
@@ -122,14 +122,14 @@
     val s1Tasks = createTasks(4, execIds, time)
     s1Tasks.foreach { task =>
       listener.onTaskStart(SparkListenerTaskStart(stages.last.stageId,
-        stages.last.attemptNumber,
+        stages.last.attemptNumber(),
         task))
     }
 
     time += 1
     s1Tasks.foreach { task =>
       task.markFinished(TaskState.FAILED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stages.last.stageId, stages.last.attemptNumber,
+      listener.onTaskEnd(SparkListenerTaskEnd(stages.last.stageId, stages.last.attemptNumber(),
         "taskType", TaskResultLost, task, new ExecutorMetrics, null))
     }
 
@@ -141,7 +141,7 @@
 
     // - Re-submit stage 1, all tasks, and succeed them and the stage.
     val oldS1 = stages.last
-    val newS1 = new StageInfo(oldS1.stageId, oldS1.attemptNumber + 1, oldS1.name, oldS1.numTasks,
+    val newS1 = new StageInfo(oldS1.stageId, oldS1.attemptNumber() + 1, oldS1.name, oldS1.numTasks,
       oldS1.rddInfos, oldS1.parentIds, oldS1.details, oldS1.taskMetrics,
       resourceProfileId = ResourceProfile.DEFAULT_RESOURCE_PROFILE_ID)
 
@@ -152,13 +152,13 @@
     val newS1Tasks = createTasks(4, execIds, time)
 
     newS1Tasks.foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(newS1.stageId, newS1.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(newS1.stageId, newS1.attemptNumber(), task))
     }
 
     time += 1
     newS1Tasks.foreach { task =>
       task.markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(newS1.stageId, newS1.attemptNumber, "taskType",
+      listener.onTaskEnd(SparkListenerTaskEnd(newS1.stageId, newS1.attemptNumber(), "taskType",
         Success, task, new ExecutorMetrics, null))
     }
 
diff --git a/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala b/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala
index 893f108..b35c576 100644
--- a/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala
@@ -1556,7 +1556,7 @@
       provider.checkForLogs()
       provider.cleanLogs()
       assert(dir.listFiles().size === 1)
-      assert(provider.getListing.length === 1)
+      assert(provider.getListing().length === 1)
 
       // Manually delete the appstatus file to make an invalid rolling event log
       val appStatusPath = RollingEventLogFilesWriter.getAppStatusFilePath(new Path(writer.logPath),
@@ -1564,7 +1564,7 @@
       fs.delete(appStatusPath, false)
       provider.checkForLogs()
       provider.cleanLogs()
-      assert(provider.getListing.length === 0)
+      assert(provider.getListing().length === 0)
 
       // Create a new application
       val writer2 = new RollingEventLogFilesWriter("app2", None, dir.toURI, conf, hadoopConf)
@@ -1576,14 +1576,14 @@
       // Both folders exist but only one application found
       provider.checkForLogs()
       provider.cleanLogs()
-      assert(provider.getListing.length === 1)
+      assert(provider.getListing().length === 1)
       assert(dir.listFiles().size === 2)
 
       // Make sure a new provider sees the valid application
       provider.stop()
       val newProvider = new FsHistoryProvider(conf)
       newProvider.checkForLogs()
-      assert(newProvider.getListing.length === 1)
+      assert(newProvider.getListing().length === 1)
     }
   }
 
@@ -1613,7 +1613,7 @@
 
       // The 1st checkForLogs should scan/update app2 only since it is newer than app1
       provider.checkForLogs()
-      assert(provider.getListing.length === 1)
+      assert(provider.getListing().length === 1)
       assert(dir.listFiles().size === 2)
       assert(provider.getListing().map(e => e.id).contains("app2"))
       assert(!provider.getListing().map(e => e.id).contains("app1"))
@@ -1628,7 +1628,7 @@
 
       // The 2nd checkForLogs should scan/update app3 only since it is newer than app1
       provider.checkForLogs()
-      assert(provider.getListing.length === 2)
+      assert(provider.getListing().length === 2)
       assert(dir.listFiles().size === 3)
       assert(provider.getListing().map(e => e.id).contains("app3"))
       assert(!provider.getListing().map(e => e.id).contains("app1"))
@@ -1655,7 +1655,7 @@
       provider.checkForLogs()
       provider.cleanLogs()
       assert(dir.listFiles().size === 1)
-      assert(provider.getListing.length === 1)
+      assert(provider.getListing().length === 1)
 
       // Manually delete event log files and create event log file reader
       val eventLogDir = dir.listFiles().head
diff --git a/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala b/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala
index a42fe5f..9aa366d 100644
--- a/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala
@@ -541,7 +541,7 @@
       assert(4 === getNumJobsRestful(), s"two jobs back-to-back not updated, server=$server\n")
     }
     val jobcount = getNumJobs("/jobs")
-    assert(!isApplicationCompleted(provider.getListing().next))
+    assert(!isApplicationCompleted(provider.getListing().next()))
 
     listApplications(false) should contain(appId)
 
@@ -549,7 +549,7 @@
     resetSparkContext()
     // check the app is now found as completed
     eventually(stdTimeout, stdInterval) {
-      assert(isApplicationCompleted(provider.getListing().next),
+      assert(isApplicationCompleted(provider.getListing().next()),
         s"application never completed, server=$server\n")
     }
 
diff --git a/core/src/test/scala/org/apache/spark/deploy/master/MasterSuite.scala b/core/src/test/scala/org/apache/spark/deploy/master/MasterSuite.scala
index afe8ca4..fc6c7d2 100644
--- a/core/src/test/scala/org/apache/spark/deploy/master/MasterSuite.scala
+++ b/core/src/test/scala/org/apache/spark/deploy/master/MasterSuite.scala
@@ -452,7 +452,7 @@
         workerHtml should include ("Spark Worker at")
         workerHtml should include ("Running Executors (0)")
         verifyStaticResourcesServedByProxy(workerHtml, workerUrl)
-      case _ => fail  // make sure we don't accidentially skip the tests
+      case _ => fail()  // make sure we don't accidentially skip the tests
     }
   }
 
diff --git a/core/src/test/scala/org/apache/spark/executor/CoarseGrainedExecutorBackendSuite.scala b/core/src/test/scala/org/apache/spark/executor/CoarseGrainedExecutorBackendSuite.scala
index 909d605..7a70213 100644
--- a/core/src/test/scala/org/apache/spark/executor/CoarseGrainedExecutorBackendSuite.scala
+++ b/core/src/test/scala/org/apache/spark/executor/CoarseGrainedExecutorBackendSuite.scala
@@ -99,7 +99,7 @@
     val rpBuilder = new ResourceProfileBuilder
     val ereqs = new ExecutorResourceRequests().resource(GPU, 2)
     ereqs.resource(FPGA, 3)
-    val rp = rpBuilder.require(ereqs).build
+    val rp = rpBuilder.require(ereqs).build()
     testParsingMultipleResources(new SparkConf, rp)
   }
 
@@ -177,7 +177,7 @@
     val rpBuilder = new ResourceProfileBuilder
     val ereqs = new ExecutorResourceRequests().resource(GPU, 4)
     val treqs = new TaskResourceRequests().resource(GPU, 1)
-    val rp = rpBuilder.require(ereqs).require(treqs).build
+    val rp = rpBuilder.require(ereqs).require(treqs).build()
     testExecutorResourceFoundLessThanRequired(new SparkConf, rp)
   }
 
@@ -245,7 +245,7 @@
       val rpBuilder = new ResourceProfileBuilder
       val ereqs = new ExecutorResourceRequests().resource(FPGA, 3, scriptPath)
       ereqs.resource(GPU, 2)
-      val rp = rpBuilder.require(ereqs).build
+      val rp = rpBuilder.require(ereqs).build()
       allocatedFileAndConfigsResourceDiscoveryTestFpga(dir, new SparkConf, rp)
     }
   }
diff --git a/core/src/test/scala/org/apache/spark/executor/ExecutorMetricsPollerSuite.scala b/core/src/test/scala/org/apache/spark/executor/ExecutorMetricsPollerSuite.scala
index 11593a0..7a5d32b 100644
--- a/core/src/test/scala/org/apache/spark/executor/ExecutorMetricsPollerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/executor/ExecutorMetricsPollerSuite.scala
@@ -28,7 +28,7 @@
 
     poller.onTaskStart(0L, 0, 0)
     // stage (0, 0) has an active task, so it remains on stageTCMP after heartbeat.
-    assert(poller.getExecutorUpdates.size === 1)
+    assert(poller.getExecutorUpdates().size === 1)
     assert(poller.stageTCMP.size === 1)
     assert(poller.stageTCMP.get((0, 0)).count === 1)
 
@@ -40,9 +40,9 @@
 
     // the next heartbeat will report the peak metrics of stage (0, 0) during the
     // previous heartbeat interval, then remove it from stageTCMP.
-    assert(poller.getExecutorUpdates.size === 1)
+    assert(poller.getExecutorUpdates().size === 1)
     assert(poller.stageTCMP.size === 0)
 
-    poller.stop
+    poller.stop()
   }
 }
diff --git a/core/src/test/scala/org/apache/spark/executor/ProcfsMetricsGetterSuite.scala b/core/src/test/scala/org/apache/spark/executor/ProcfsMetricsGetterSuite.scala
index d583afd..a5b4814 100644
--- a/core/src/test/scala/org/apache/spark/executor/ProcfsMetricsGetterSuite.scala
+++ b/core/src/test/scala/org/apache/spark/executor/ProcfsMetricsGetterSuite.scala
@@ -46,8 +46,8 @@
     val mockedP = spy[ProcfsMetricsGetter](p)
 
     var ptree: Set[Int] = Set(26109, 22763)
-    when(mockedP.computeProcessTree).thenReturn(ptree)
-    var r = mockedP.computeAllMetrics
+    when(mockedP.computeProcessTree()).thenReturn(ptree)
+    var r = mockedP.computeAllMetrics()
     assert(r.jvmVmemTotal == 4769947648L)
     assert(r.jvmRSSTotal == 262610944)
     assert(r.pythonVmemTotal == 360595456)
@@ -55,8 +55,8 @@
 
     // proc file of pid 22764 doesn't exist, so partial metrics shouldn't be returned
     ptree = Set(26109, 22764, 22763)
-    when(mockedP.computeProcessTree).thenReturn(ptree)
-    r = mockedP.computeAllMetrics
+    when(mockedP.computeProcessTree()).thenReturn(ptree)
+    r = mockedP.computeAllMetrics()
     assert(r.jvmVmemTotal == 0)
     assert(r.jvmRSSTotal == 0)
     assert(r.pythonVmemTotal == 0)
diff --git a/core/src/test/scala/org/apache/spark/input/WholeTextFileInputFormatSuite.scala b/core/src/test/scala/org/apache/spark/input/WholeTextFileInputFormatSuite.scala
index f8217b1..417e711 100644
--- a/core/src/test/scala/org/apache/spark/input/WholeTextFileInputFormatSuite.scala
+++ b/core/src/test/scala/org/apache/spark/input/WholeTextFileInputFormatSuite.scala
@@ -68,7 +68,7 @@
         createNativeFile(dir, filename, contents, false)
       }
       // ensure spark job runs successfully without exceptions from the CombineFileInputFormat
-      assert(sc.wholeTextFiles(dir.toString).count == 3)
+      assert(sc.wholeTextFiles(dir.toString).count() == 3)
     }
   }
 }
diff --git a/core/src/test/scala/org/apache/spark/rdd/AsyncRDDActionsSuite.scala b/core/src/test/scala/org/apache/spark/rdd/AsyncRDDActionsSuite.scala
index 5e66ca9..56783de 100644
--- a/core/src/test/scala/org/apache/spark/rdd/AsyncRDDActionsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/AsyncRDDActionsSuite.scala
@@ -209,7 +209,7 @@
   }
 
   private def testAsyncAction[R](action: RDD[Int] => FutureAction[R]): Unit = {
-    val executionContextInvoked = Promise[Unit]
+    val executionContextInvoked = Promise[Unit]()
     val fakeExecutionContext = new ExecutionContext {
       override def execute(runnable: Runnable): Unit = {
         executionContextInvoked.success(())
diff --git a/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala
index a204502..2bed5d6 100644
--- a/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/JdbcRDDSuite.scala
@@ -81,7 +81,7 @@
       1, 100, 3,
       (r: ResultSet) => { r.getInt(1) } ).cache()
 
-    assert(rdd.count === 100)
+    assert(rdd.count() === 100)
     assert(rdd.reduce(_ + _) === 10100)
   }
 
@@ -93,7 +93,7 @@
       "SELECT DATA FROM BIGINT_TEST WHERE ? <= ID AND ID <= ?",
       1131544775L, 567279358897692673L, 20,
       (r: ResultSet) => { r.getInt(1) } ).cache()
-    assert(rdd.count === 100)
+    assert(rdd.count() === 100)
     assert(rdd.reduce(_ + _) === 5050)
   }
 
diff --git a/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala
index da2ccbf..d55acec 100644
--- a/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/PartitionwiseSampledRDDSuite.scala
@@ -44,7 +44,7 @@
     val rdd = sc.makeRDD(Array(1L, 2L, 3L, 4L), 2)
     val sampler = new MockSampler
     val sample = new PartitionwiseSampledRDD[Long, Long](rdd, sampler, false, 0L)
-    assert(sample.distinct().count == 2, "Seeds must be different.")
+    assert(sample.distinct().count() == 2, "Seeds must be different.")
   }
 
   test("concurrency") {
diff --git a/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala
index 4e4eafb..2b9dd32 100644
--- a/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala
@@ -164,7 +164,7 @@
   test("pipe with empty partition") {
     val data = sc.parallelize(Seq("foo", "bing"), 8)
     val piped = data.pipe("wc -c")
-    assert(piped.count == 8)
+    assert(piped.count() == 8)
     val charCounts = piped.map(_.trim.toInt).collect().toSet
     val expected = if (Utils.isWindows) {
       // Note that newline character on Windows is \r\n which are two.
diff --git a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
index 02ffc23..046017a 100644
--- a/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
+++ b/core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala
@@ -61,9 +61,9 @@
     assert(nums.toLocalIterator.toList === List(1, 2, 3, 4))
     val dups = sc.makeRDD(Array(1, 1, 2, 2, 3, 3, 4, 4), 2)
     assert(dups.distinct().count() === 4)
-    assert(dups.distinct().count === 4)  // Can distinct and count be called without parentheses?
-    assert(dups.distinct().collect === dups.distinct().collect)
-    assert(dups.distinct(2).collect === dups.distinct().collect)
+    assert(dups.distinct().count() === 4)  // Can distinct and count be called without parentheses?
+    assert(dups.distinct().collect() === dups.distinct().collect())
+    assert(dups.distinct(2).collect() === dups.distinct().collect())
     assert(nums.reduce(_ + _) === 10)
     assert(nums.fold(0)(_ + _) === 10)
     assert(nums.map(_.toString).collect().toList === List("1", "2", "3", "4"))
@@ -320,7 +320,7 @@
 
   test("empty RDD") {
     val empty = new EmptyRDD[Int](sc)
-    assert(empty.count === 0)
+    assert(empty.count() === 0)
     assert(empty.collect().size === 0)
 
     val thrown = intercept[UnsupportedOperationException]{
@@ -662,7 +662,7 @@
 
     nums = sc.parallelize(1 to 2, 2)
     assert(nums.take(2147483638).size === 2)
-    assert(nums.takeAsync(2147483638).get.size === 2)
+    assert(nums.takeAsync(2147483638).get().size === 2)
   }
 
   test("top with predefined ordering") {
@@ -1117,7 +1117,7 @@
       sc.parallelize(Seq(new BadSerializable, new BadSerializable)).collect()
     }
     // Check that the context has not crashed
-    sc.parallelize(1 to 100).map(x => x*2).collect
+    sc.parallelize(1 to 100).map(x => x * 2).collect()
   }
 
   /** A contrived RDD that allows the manual addition of dependencies after creation. */
@@ -1165,7 +1165,7 @@
     val rdd: RDD[Int] = sc.parallelize(1 to 100)
     val rdd2: RDD[Int] = sc.parallelize(1 to 100)
     val thrown = intercept[SparkException] {
-      rdd.map(x => x * rdd2.count).collect()
+      rdd.map(x => x * rdd2.count()).collect()
     }
     assert(thrown.getMessage.contains("SPARK-5063"))
   }
diff --git a/core/src/test/scala/org/apache/spark/resource/ResourceProfileManagerSuite.scala b/core/src/test/scala/org/apache/spark/resource/ResourceProfileManagerSuite.scala
index 7149267..ab57f1c 100644
--- a/core/src/test/scala/org/apache/spark/resource/ResourceProfileManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/resource/ResourceProfileManagerSuite.scala
@@ -62,7 +62,7 @@
     val rprof = new ResourceProfileBuilder()
     val gpuExecReq =
       new ExecutorResourceRequests().resource("gpu", 2, "someScript")
-    val immrprof = rprof.require(gpuExecReq).build
+    val immrprof = rprof.require(gpuExecReq).build()
     val error = intercept[SparkException] {
       rpmanager.isSupported(immrprof)
     }.getMessage()
@@ -82,7 +82,7 @@
     val rprof = new ResourceProfileBuilder()
     val gpuExecReq =
       new ExecutorResourceRequests().resource("gpu", 2, "someScript")
-    val immrprof = rprof.require(gpuExecReq).build
+    val immrprof = rprof.require(gpuExecReq).build()
     assert(rpmanager.isSupported(immrprof) == true)
   }
 
@@ -97,7 +97,7 @@
     val rprof = new ResourceProfileBuilder()
     val gpuExecReq =
       new ExecutorResourceRequests().resource("gpu", 2, "someScript", "nvidia")
-    val immrprof = rprof.require(gpuExecReq).build
+    val immrprof = rprof.require(gpuExecReq).build()
     assert(rpmanager.isSupported(immrprof) == true)
   }
 
@@ -178,7 +178,7 @@
     val rprof = new ResourceProfileBuilder()
     val gpuExecReq =
       new ExecutorResourceRequests().resource("gpu", 2, "someScript")
-    val immrprof = rprof.require(gpuExecReq).build
+    val immrprof = rprof.require(gpuExecReq).build()
     val error = intercept[SparkException] {
       rpmanager.isSupported(immrprof)
     }.getMessage()
@@ -200,11 +200,11 @@
       val treqs = new TaskResourceRequests()
       treqs.cpus(i)
       rprofBuilder.require(ereqs).require(treqs)
-      val rprof = rprofBuilder.build
+      val rprof = rprofBuilder.build()
       rpmanager.addResourceProfile(rprof)
       if (i == checkId) rpAlreadyExist = Some(rprof)
     }
-    val rpNotMatch = new ResourceProfileBuilder().build
+    val rpNotMatch = new ResourceProfileBuilder().build()
     assert(rpmanager.getEquivalentProfile(rpNotMatch).isEmpty,
       s"resourceProfile should not have existed")
 
@@ -214,7 +214,7 @@
     val treqs = new TaskResourceRequests()
     treqs.cpus(checkId)
     rprofBuilder.require(ereqs).require(treqs)
-    val rpShouldMatch = rprofBuilder.build
+    val rpShouldMatch = rprofBuilder.build()
 
     val equivProf = rpmanager.getEquivalentProfile(rpShouldMatch)
     assert(equivProf.nonEmpty)
diff --git a/core/src/test/scala/org/apache/spark/resource/ResourceProfileSuite.scala b/core/src/test/scala/org/apache/spark/resource/ResourceProfileSuite.scala
index 9a2e47e..fd7018f 100644
--- a/core/src/test/scala/org/apache/spark/resource/ResourceProfileSuite.scala
+++ b/core/src/test/scala/org/apache/spark/resource/ResourceProfileSuite.scala
@@ -288,13 +288,13 @@
     val taskReq = new TaskResourceRequests().resource("gpu", 1)
     val eReq = new ExecutorResourceRequests().resource("gpu", 2, "myscript", "nvidia")
     rprofBuilder.require(taskReq).require(eReq)
-    val rprof = rprofBuilder.build
+    val rprof = rprofBuilder.build()
 
     val rprofBuilder2 = new ResourceProfileBuilder()
     val taskReq2 = new TaskResourceRequests().resource("gpu", 1)
     val eReq2 = new ExecutorResourceRequests().resource("gpu", 2, "myscript", "nvidia")
     rprofBuilder2.require(taskReq2).require(eReq2)
-    val rprof2 = rprofBuilder.build
+    val rprof2 = rprofBuilder.build()
     rprof2.setResourceProfileId(rprof.id)
 
     assert(rprof === rprof2, "resource profile equality not working")
diff --git a/core/src/test/scala/org/apache/spark/resource/ResourceUtilsSuite.scala b/core/src/test/scala/org/apache/spark/resource/ResourceUtilsSuite.scala
index ffe5ff5..1ab9f7c 100644
--- a/core/src/test/scala/org/apache/spark/resource/ResourceUtilsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/resource/ResourceUtilsSuite.scala
@@ -166,7 +166,7 @@
       val ereqs = new ExecutorResourceRequests().resource(GPU, 2, gpuDiscovery)
       val treqs = new TaskResourceRequests().resource(GPU, 1)
 
-      val rp = rpBuilder.require(ereqs).require(treqs).build
+      val rp = rpBuilder.require(ereqs).require(treqs).build()
       val resourcesFromBoth = getOrDiscoverAllResourcesForResourceProfile(
         Some(resourcesFile), SPARK_EXECUTOR_PREFIX, rp, conf)
       val expectedGpuInfo = new ResourceInformation(GPU, Array("0", "1"))
diff --git a/core/src/test/scala/org/apache/spark/scheduler/BarrierTaskContextSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/BarrierTaskContextSuite.scala
index 26cd537..849832c 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/BarrierTaskContextSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/BarrierTaskContextSuite.scala
@@ -81,7 +81,7 @@
     val rdd = sc.makeRDD(1 to 10, 4)
     val rdd2 = rdd.barrier().mapPartitions { it =>
       val context = BarrierTaskContext.get()
-      val partitionId = context.partitionId
+      val partitionId = context.partitionId()
       if (partitionId == 0) {
         context.barrier()
       } else {
@@ -155,7 +155,7 @@
     val rdd2 = rdd.barrier().mapPartitions { it =>
       val context = BarrierTaskContext.get()
       // Task 3 shall sleep 2000ms to ensure barrier() call timeout
-      if (context.taskAttemptId == 3) {
+      if (context.taskAttemptId() == 3) {
         Thread.sleep(2000)
       }
       context.barrier()
@@ -175,7 +175,7 @@
     val rdd = sc.makeRDD(1 to 10, 4)
     val rdd2 = rdd.barrier().mapPartitions { it =>
       val context = BarrierTaskContext.get()
-      if (context.taskAttemptId != 0) {
+      if (context.taskAttemptId() != 0) {
         context.barrier()
       }
       it
@@ -195,7 +195,7 @@
     val rdd2 = rdd.barrier().mapPartitions { it =>
       val context = BarrierTaskContext.get()
       try {
-        if (context.taskAttemptId == 0) {
+        if (context.taskAttemptId() == 0) {
           // Due to some non-obvious reason, the code can trigger an Exception and skip the
           // following statements within the try ... catch block, including the first barrier()
           // call.
diff --git a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
index 7691b98..5040532 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
@@ -457,7 +457,7 @@
    * directly through CompletionEvents.
    */
   private val jobComputeFunc = (context: TaskContext, it: Iterator[(_)]) =>
-    it.next.asInstanceOf[Tuple2[_, _]]._1
+    it.next().asInstanceOf[Tuple2[_, _]]._1
 
   /** Send the given CompletionEvent messages for the tasks in the TaskSet. */
   private def complete(taskSet: TaskSet, taskEndInfos: Seq[(TaskEndReason, Any)]): Unit = {
@@ -3449,12 +3449,12 @@
   test("test 1 resource profile") {
     val ereqs = new ExecutorResourceRequests().cores(4)
     val treqs = new TaskResourceRequests().cpus(1)
-    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build
+    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build()
 
     val rdd = sc.parallelize(1 to 10).map(x => (x, x)).withResources(rp1)
     val (shuffledeps, resourceprofiles) = scheduler.getShuffleDependenciesAndResourceProfiles(rdd)
     val rpMerged = scheduler.mergeResourceProfilesForStage(resourceprofiles)
-    val expectedid = Option(rdd.getResourceProfile).map(_.id)
+    val expectedid = Option(rdd.getResourceProfile()).map(_.id)
     assert(expectedid.isDefined)
     assert(expectedid.get != ResourceProfile.DEFAULT_RESOURCE_PROFILE_ID)
     assert(rpMerged.id == expectedid.get)
@@ -3464,11 +3464,11 @@
     import org.apache.spark.resource._
     val ereqs = new ExecutorResourceRequests().cores(4)
     val treqs = new TaskResourceRequests().cpus(1)
-    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build
+    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build()
 
     val ereqs2 = new ExecutorResourceRequests().cores(2)
     val treqs2 = new TaskResourceRequests().cpus(2)
-    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build
+    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build()
 
     val rdd = sc.parallelize(1 to 10).withResources(rp1).map(x => (x, x)).withResources(rp2)
     val error = intercept[IllegalArgumentException] {
@@ -3484,11 +3484,11 @@
 
     val ereqs = new ExecutorResourceRequests().cores(4)
     val treqs = new TaskResourceRequests().cpus(1)
-    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build
+    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build()
 
     val ereqs2 = new ExecutorResourceRequests().cores(2)
     val treqs2 = new TaskResourceRequests().cpus(2)
-    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build
+    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build()
 
     val rdd = sc.parallelize(1 to 10).withResources(rp1).map(x => (x, x)).withResources(rp2)
     val (shuffledeps, resourceprofiles) = scheduler.getShuffleDependenciesAndResourceProfiles(rdd)
@@ -3502,11 +3502,11 @@
 
     val ereqs = new ExecutorResourceRequests().cores(4)
     val treqs = new TaskResourceRequests().cpus(1)
-    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build
+    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build()
 
     val ereqs2 = new ExecutorResourceRequests().cores(2)
     val treqs2 = new TaskResourceRequests().cpus(2)
-    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build
+    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build()
 
     val rdd = sc.parallelize(1 to 10).withResources(rp1).map(x => (x, x)).withResources(rp2)
     val (_, resourceprofiles) = scheduler.getShuffleDependenciesAndResourceProfiles(rdd)
@@ -3642,10 +3642,10 @@
     import org.apache.spark.resource._
     val ereqs = new ExecutorResourceRequests().cores(4)
     val treqs = new TaskResourceRequests().cpus(1)
-    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build
+    val rp1 = new ResourceProfileBuilder().require(ereqs).require(treqs).build()
     val ereqs2 = new ExecutorResourceRequests().cores(6)
     val treqs2 = new TaskResourceRequests().cpus(2)
-    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build
+    val rp2 = new ResourceProfileBuilder().require(ereqs2).require(treqs2).build()
 
     val rddWithRp = new MyRDD(sc, 2, Nil).withResources(rp1)
     val rddA = new MyRDD(sc, 2, Nil).withResources(rp1)
diff --git a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala
index bd65936..cd8fac2 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala
@@ -173,7 +173,7 @@
       .mapPartitions(_.map(elem => (elem, elem)))
       .filter(elem => elem._1 % 2 == 0)
       .reduceByKey(_ + _)
-      .collect
+      .collect()
     sc.stop()
 
     val eventLogStream = EventLogFileReader.openEventLog(new Path(testDirPath, appId), fileSystem)
diff --git a/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorIntegrationSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorIntegrationSuite.scala
index 45da750..fcacd22 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorIntegrationSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorIntegrationSuite.scala
@@ -59,7 +59,7 @@
 private class ThrowExceptionOnFirstAttemptOutputCommitter extends FileOutputCommitter {
   override def commitTask(context: TaskAttemptContext): Unit = {
     val ctx = TaskContext.get()
-    if (ctx.attemptNumber < 1) {
+    if (ctx.attemptNumber() < 1) {
       throw new java.io.FileNotFoundException("Intentional exception")
     }
     super.commitTask(context)
diff --git a/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorSuite.scala
index 842a261..0533f9d 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorSuite.scala
@@ -304,7 +304,7 @@
   def failFirstCommitAttempt(iter: Iterator[Int]): Unit = {
     val ctx = TaskContext.get()
     runCommitWithProvidedCommitter(ctx, iter,
-      if (ctx.attemptNumber == 0) failingOutputCommitter else successfulOutputCommitter)
+      if (ctx.attemptNumber() == 0) failingOutputCommitter else successfulOutputCommitter)
   }
 
   private def runCommitWithProvidedCommitter(
@@ -324,9 +324,9 @@
     // Create TaskAttemptContext.
     // Hadoop wants a 32-bit task attempt ID, so if ours is bigger than Int.MaxValue, roll it
     // around by taking a mod. We expect that no task will be attempted 2 billion times.
-    val taskAttemptId = (ctx.taskAttemptId % Int.MaxValue).toInt
+    val taskAttemptId = (ctx.taskAttemptId() % Int.MaxValue).toInt
     val attemptId = new TaskAttemptID(
-      new TaskID(jobId.value, TaskType.MAP, ctx.partitionId), taskAttemptId)
+      new TaskID(jobId.value, TaskType.MAP, ctx.partitionId()), taskAttemptId)
     val taskContext = new TaskAttemptContextImpl(jobConf, attemptId)
 
     committer.setupTask(taskContext)
diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala
index 54a42c1..ff5d821 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala
@@ -340,13 +340,13 @@
     sc = new SparkContext("local[1,2]", "test")  // use maxRetries = 2 because we test failed tasks
     // Check that attemptIds are 0 for all tasks' initial attempts
     val attemptIds = sc.parallelize(Seq(1, 2), 2).mapPartitions { iter =>
-      Seq(TaskContext.get().attemptNumber).iterator
+      Seq(TaskContext.get().attemptNumber()).iterator
     }.collect()
     assert(attemptIds.toSet === Set(0))
 
     // Test a job with failed tasks
     val attemptIdsWithFailedTask = sc.parallelize(Seq(1, 2), 2).mapPartitions { iter =>
-      val attemptId = TaskContext.get().attemptNumber
+      val attemptId = TaskContext.get().attemptNumber()
       if (iter.next() == 1 && attemptId == 0) {
         throw new Exception("First execution of task failed")
       }
@@ -385,7 +385,7 @@
     for (numPartitions <- 1 to 10) {
       val numPartitionsFromContext = sc.parallelize(1 to 1000, numPartitions)
         .mapPartitions { _ =>
-          Seq(TaskContext.get.numPartitions()).iterator
+          Seq(TaskContext.get().numPartitions()).iterator
         }.collect()
       assert(numPartitionsFromContext.toSet === Set(numPartitions),
         s"numPartitions = $numPartitions")
@@ -394,7 +394,7 @@
     for (numPartitions <- 1 to 10) {
       val numPartitionsFromContext = sc.parallelize(1 to 1000, 2).repartition(numPartitions)
         .mapPartitions { _ =>
-          Seq(TaskContext.get.numPartitions()).iterator
+          Seq(TaskContext.get().numPartitions()).iterator
         }.collect()
       assert(numPartitionsFromContext.toSet === Set(numPartitions),
         s"numPartitions = $numPartitions")
@@ -411,7 +411,7 @@
     sc.parallelize(1 to 10, 10).map { i =>
       acc1.add(1)
       acc2.add(1)
-      if (TaskContext.get.attemptNumber() <= 2) {
+      if (TaskContext.get().attemptNumber() <= 2) {
         throw new Exception("you did something wrong")
       } else {
         0
diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala
index 3ea0843..5a8722a 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/TaskResultGetterSuite.scala
@@ -99,7 +99,7 @@
   extends TaskResultGetter(env, scheduler) {
 
   // Use the current thread so we can access its results synchronously
-  protected override val getTaskResultExecutor = ThreadUtils.sameThreadExecutorService
+  protected override val getTaskResultExecutor = ThreadUtils.sameThreadExecutorService()
 
   // DirectTaskResults that we receive from the executors
   private val _taskResults = new ArrayBuffer[DirectTaskResult[_]]
diff --git a/core/src/test/scala/org/apache/spark/serializer/KryoIteratorBenchmark.scala b/core/src/test/scala/org/apache/spark/serializer/KryoIteratorBenchmark.scala
index 5de1a12..f526428 100644
--- a/core/src/test/scala/org/apache/spark/serializer/KryoIteratorBenchmark.scala
+++ b/core/src/test/scala/org/apache/spark/serializer/KryoIteratorBenchmark.scala
@@ -99,15 +99,15 @@
       }
     }
 
-    createCase("int", 1, Random.nextInt)
-    createCase("int", 10, Random.nextInt)
-    createCase("int", 100, Random.nextInt)
+    createCase("int", 1, Random.nextInt())
+    createCase("int", 10, Random.nextInt())
+    createCase("int", 100, Random.nextInt())
     createCase("string", 1, Random.nextString(5))
     createCase("string", 10, Random.nextString(5))
     createCase("string", 100, Random.nextString(5))
-    createCase("Array[int]", 1, Array.fill(10)(Random.nextInt))
-    createCase("Array[int]", 10, Array.fill(10)(Random.nextInt))
-    createCase("Array[int]", 100, Array.fill(10)(Random.nextInt))
+    createCase("Array[int]", 1, Array.fill(10)(Random.nextInt()))
+    createCase("Array[int]", 10, Array.fill(10)(Random.nextInt()))
+    createCase("Array[int]", 100, Array.fill(10)(Random.nextInt()))
   }
 
   def createSerializer(): SerializerInstance = {
diff --git a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
index 40319e1..86dc6c8 100644
--- a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
@@ -290,11 +290,11 @@
   }
 
   test("kryo with parallelize for specialized tuples") {
-    assert(sc.parallelize(Seq((1, 11), (2, 22), (3, 33))).count === 3)
+    assert(sc.parallelize(Seq((1, 11), (2, 22), (3, 33))).count() === 3)
   }
 
   test("kryo with parallelize for primitive arrays") {
-    assert(sc.parallelize(Array(1, 2, 3)).count === 3)
+    assert(sc.parallelize(Array(1, 2, 3)).count() === 3)
   }
 
   test("kryo with collect for specialized tuples") {
@@ -425,11 +425,11 @@
 
   test("getAutoReset") {
     val ser = new KryoSerializer(new SparkConf).newInstance().asInstanceOf[KryoSerializerInstance]
-    assert(ser.getAutoReset)
+    assert(ser.getAutoReset())
     val conf = new SparkConf().set(KRYO_USER_REGISTRATORS,
       Seq(classOf[RegistratorWithoutAutoReset].getName))
     val ser2 = new KryoSerializer(conf).newInstance().asInstanceOf[KryoSerializerInstance]
-    assert(!ser2.getAutoReset)
+    assert(!ser2.getAutoReset())
   }
 
   test("SPARK-25176 ClassCastException when writing a Map after previously " +
diff --git a/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala b/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala
index f1e987a..4d75f5d 100644
--- a/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala
@@ -206,7 +206,7 @@
     val s1Tasks = createTasks(4, execIds)
     s1Tasks.foreach { task =>
       listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId,
-        stages.head.attemptNumber,
+        stages.head.attemptNumber(),
         task))
     }
 
@@ -225,7 +225,7 @@
       check[TaskDataWrapper](task.taskId) { wrapper =>
         assert(wrapper.taskId === task.taskId)
         assert(wrapper.stageId === stages.head.stageId)
-        assert(wrapper.stageAttemptId === stages.head.attemptNumber)
+        assert(wrapper.stageAttemptId === stages.head.attemptNumber())
         assert(wrapper.index === task.index)
         assert(wrapper.attempt === task.attemptNumber)
         assert(wrapper.launchTime === task.launchTime)
@@ -246,7 +246,7 @@
           Some(value), None, true, false, None)
         listener.onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate(
           task.executorId,
-          Seq((task.taskId, stages.head.stageId, stages.head.attemptNumber, Seq(accum)))))
+          Seq((task.taskId, stages.head.stageId, stages.head.attemptNumber(), Seq(accum)))))
       }
 
       check[StageDataWrapper](key(stages.head)) { stage =>
@@ -268,7 +268,7 @@
       executorId = execIds.head,
       taskFailures = 2,
       stageId = stages.head.stageId,
-      stageAttemptId = stages.head.attemptNumber))
+      stageAttemptId = stages.head.attemptNumber()))
 
     val executorStageSummaryWrappers =
       KVUtils.viewToSeq(store.view(classOf[ExecutorStageSummaryWrapper]).index("stage")
@@ -296,7 +296,7 @@
       hostId = "2.example.com", // this is where the second executor is hosted
       executorFailures = 1,
       stageId = stages.head.stageId,
-      stageAttemptId = stages.head.attemptNumber))
+      stageAttemptId = stages.head.attemptNumber()))
 
     val executorStageSummaryWrappersForNode =
       KVUtils.viewToSeq(store.view(classOf[ExecutorStageSummaryWrapper]).index("stage")
@@ -314,12 +314,12 @@
     // Fail one of the tasks, re-start it.
     time += 1
     s1Tasks.head.markFinished(TaskState.FAILED, time)
-    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber(),
       "taskType", TaskResultLost, s1Tasks.head, new ExecutorMetrics, null))
 
     time += 1
     val reattempt = newAttempt(s1Tasks.head, nextTaskId())
-    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber(),
       reattempt))
 
     assert(store.count(classOf[TaskDataWrapper]) === s1Tasks.size + 1)
@@ -354,7 +354,7 @@
     val killed = s1Tasks.drop(1).head
     killed.finishTime = time
     killed.failed = true
-    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber(),
       "taskType", TaskKilled("killed"), killed, new ExecutorMetrics, null))
 
     check[JobDataWrapper](1) { job =>
@@ -376,13 +376,13 @@
     time += 1
     val denied = newAttempt(killed, nextTaskId())
     val denyReason = TaskCommitDenied(1, 1, 1)
-    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber(),
       denied))
 
     time += 1
     denied.finishTime = time
     denied.failed = true
-    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber(),
       "taskType", denyReason, denied, new ExecutorMetrics, null))
 
     check[JobDataWrapper](1) { job =>
@@ -402,7 +402,7 @@
 
     // Start a new attempt.
     val reattempt2 = newAttempt(denied, nextTaskId())
-    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber,
+    listener.onTaskStart(SparkListenerTaskStart(stages.head.stageId, stages.head.attemptNumber(),
       reattempt2))
 
     // Succeed all tasks in stage 1.
@@ -415,7 +415,7 @@
     time += 1
     pending.foreach { task =>
       task.markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber,
+      listener.onTaskEnd(SparkListenerTaskEnd(stages.head.stageId, stages.head.attemptNumber(),
         "taskType", Success, task, new ExecutorMetrics, s1Metrics))
     }
 
@@ -492,7 +492,7 @@
       hostId = "1.example.com",
       executorFailures = 1,
       stageId = stages.last.stageId,
-      stageAttemptId = stages.last.attemptNumber))
+      stageAttemptId = stages.last.attemptNumber()))
 
     check[ExecutorSummaryWrapper](execIds.head) { exec =>
       assert(exec.info.blacklistedInStages === Set(stages.last.stageId))
@@ -504,14 +504,14 @@
     val s2Tasks = createTasks(4, execIds)
     s2Tasks.foreach { task =>
       listener.onTaskStart(SparkListenerTaskStart(stages.last.stageId,
-        stages.last.attemptNumber,
+        stages.last.attemptNumber(),
         task))
     }
 
     time += 1
     s2Tasks.foreach { task =>
       task.markFinished(TaskState.FAILED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stages.last.stageId, stages.last.attemptNumber,
+      listener.onTaskEnd(SparkListenerTaskEnd(stages.last.stageId, stages.last.attemptNumber(),
         "taskType", TaskResultLost, task, new ExecutorMetrics, null))
     }
 
@@ -546,7 +546,7 @@
 
     // - Re-submit stage 2, all tasks, and succeed them and the stage.
     val oldS2 = stages.last
-    val newS2 = new StageInfo(oldS2.stageId, oldS2.attemptNumber + 1, oldS2.name, oldS2.numTasks,
+    val newS2 = new StageInfo(oldS2.stageId, oldS2.attemptNumber() + 1, oldS2.name, oldS2.numTasks,
       oldS2.rddInfos, oldS2.parentIds, oldS2.details, oldS2.taskMetrics,
       resourceProfileId = ResourceProfile.DEFAULT_RESOURCE_PROFILE_ID)
 
@@ -558,13 +558,13 @@
     val newS2Tasks = createTasks(4, execIds)
 
     newS2Tasks.foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(newS2.stageId, newS2.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(newS2.stageId, newS2.attemptNumber(), task))
     }
 
     time += 1
     newS2Tasks.foreach { task =>
       task.markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(newS2.stageId, newS2.attemptNumber, "taskType",
+      listener.onTaskEnd(SparkListenerTaskEnd(newS2.stageId, newS2.attemptNumber(), "taskType",
         Success, task, new ExecutorMetrics, null))
     }
 
@@ -617,14 +617,14 @@
 
     j2s2Tasks.foreach { task =>
       listener.onTaskStart(SparkListenerTaskStart(j2Stages.last.stageId,
-        j2Stages.last.attemptNumber,
+        j2Stages.last.attemptNumber(),
         task))
     }
 
     time += 1
     j2s2Tasks.foreach { task =>
       task.markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(j2Stages.last.stageId, j2Stages.last.attemptNumber,
+      listener.onTaskEnd(SparkListenerTaskEnd(j2Stages.last.stageId, j2Stages.last.attemptNumber(),
         "taskType", Success, task, new ExecutorMetrics, null))
     }
 
@@ -1077,17 +1077,17 @@
     // task end event.
     time += 1
     val task = createTasks(1, Array("1")).head
-    listener.onTaskStart(SparkListenerTaskStart(dropped.stageId, dropped.attemptNumber, task))
+    listener.onTaskStart(SparkListenerTaskStart(dropped.stageId, dropped.attemptNumber(), task))
 
     time += 1
     task.markFinished(TaskState.FINISHED, time)
     val metrics = TaskMetrics.empty
     metrics.setExecutorRunTime(42L)
-    listener.onTaskEnd(SparkListenerTaskEnd(dropped.stageId, dropped.attemptNumber,
+    listener.onTaskEnd(SparkListenerTaskEnd(dropped.stageId, dropped.attemptNumber(),
       "taskType", Success, task, new ExecutorMetrics, metrics))
 
     new AppStatusStore(store)
-      .taskSummary(dropped.stageId, dropped.attemptNumber, Array(0.25d, 0.50d, 0.75d))
+      .taskSummary(dropped.stageId, dropped.attemptNumber(), Array(0.25d, 0.50d, 0.75d))
     assert(store.count(classOf[CachedQuantile], "stage", key(dropped)) === 3)
 
     stages.drop(1).foreach { s =>
@@ -1123,13 +1123,13 @@
     time += 1
     val tasks = createTasks(2, Array("1"))
     tasks.foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(attempt2.stageId, attempt2.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(attempt2.stageId, attempt2.attemptNumber(), task))
     }
     assert(store.count(classOf[TaskDataWrapper]) === 2)
 
     // Start a 3rd task. The finished tasks should be deleted.
     createTasks(1, Array("1")).foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(attempt2.stageId, attempt2.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(attempt2.stageId, attempt2.attemptNumber(), task))
     }
     assert(store.count(classOf[TaskDataWrapper]) === 2)
     intercept[NoSuchElementException] {
@@ -1138,7 +1138,7 @@
 
     // Start a 4th task. The first task should be deleted, even if it's still running.
     createTasks(1, Array("1")).foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(attempt2.stageId, attempt2.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(attempt2.stageId, attempt2.attemptNumber(), task))
     }
     assert(store.count(classOf[TaskDataWrapper]) === 2)
     intercept[NoSuchElementException] {
@@ -1258,23 +1258,23 @@
     // Start task 1 and task 2
     val tasks = createTasks(3, Array("1"))
     tasks.take(2).foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(stage1.stageId, stage1.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(stage1.stageId, stage1.attemptNumber(), task))
     }
 
     // Stop task 2 before task 1
     time += 1
     tasks(1).markFinished(TaskState.FINISHED, time)
     listener.onTaskEnd(SparkListenerTaskEnd(
-      stage1.stageId, stage1.attemptNumber, "taskType", Success, tasks(1),
+      stage1.stageId, stage1.attemptNumber(), "taskType", Success, tasks(1),
       new ExecutorMetrics, null))
     time += 1
     tasks(0).markFinished(TaskState.FINISHED, time)
     listener.onTaskEnd(SparkListenerTaskEnd(
-      stage1.stageId, stage1.attemptNumber, "taskType", Success, tasks(0),
+      stage1.stageId, stage1.attemptNumber(), "taskType", Success, tasks(0),
       new ExecutorMetrics, null))
 
     // Start task 3 and task 2 should be evicted.
-    listener.onTaskStart(SparkListenerTaskStart(stage1.stageId, stage1.attemptNumber, tasks(2)))
+    listener.onTaskStart(SparkListenerTaskStart(stage1.stageId, stage1.attemptNumber(), tasks(2)))
     assert(store.count(classOf[TaskDataWrapper]) === 2)
     intercept[NoSuchElementException] {
       store.read(classOf[TaskDataWrapper], tasks(1).id)
@@ -1335,14 +1335,14 @@
     // Start 2 Tasks
     val tasks = createTasks(2, Array("1"))
     tasks.foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(stage1.stageId, stage1.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(stage1.stageId, stage1.attemptNumber(), task))
     }
 
     // Task 1 Finished
     time += 1
     tasks(0).markFinished(TaskState.FINISHED, time)
     listener.onTaskEnd(SparkListenerTaskEnd(
-      stage1.stageId, stage1.attemptNumber, "taskType", Success, tasks(0),
+      stage1.stageId, stage1.attemptNumber(), "taskType", Success, tasks(0),
       new ExecutorMetrics, null))
 
     // Stage 1 Completed
@@ -1357,7 +1357,7 @@
     time += 1
     tasks(1).markFinished(TaskState.FINISHED, time)
     listener.onTaskEnd(
-      SparkListenerTaskEnd(stage1.stageId, stage1.attemptNumber, "taskType",
+      SparkListenerTaskEnd(stage1.stageId, stage1.attemptNumber(), "taskType",
         TaskKilled(reason = "Killed"), tasks(1), new ExecutorMetrics, null))
 
     // Ensure killed task metrics are updated
@@ -1395,16 +1395,16 @@
 
       val tasks = createTasks(4, Array("1", "2"))
       tasks.foreach { task =>
-        listener.onTaskStart(SparkListenerTaskStart(stage.stageId, stage.attemptNumber, task))
+        listener.onTaskStart(SparkListenerTaskStart(stage.stageId, stage.attemptNumber(), task))
       }
 
       time += 1
       tasks(0).markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
         Success, tasks(0), new ExecutorMetrics, null))
       time += 1
       tasks(1).markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
         Success, tasks(1), new ExecutorMetrics, null))
 
       stage.failureReason = Some("Failed")
@@ -1415,12 +1415,12 @@
 
       time += 1
       tasks(2).markFinished(TaskState.FAILED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
         ExecutorLostFailure("1", true, Some("Lost executor")), tasks(2), new ExecutorMetrics,
         null))
       time += 1
       tasks(3).markFinished(TaskState.FAILED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
         ExecutorLostFailure("2", true, Some("Lost executor")), tasks(3), new ExecutorMetrics,
         null))
 
@@ -1865,38 +1865,38 @@
 
     val tasks = createTasks(2, Array("1", "2"))
     tasks.foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(stage.stageId, stage.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(stage.stageId, stage.attemptNumber(), task))
     }
 
     time += 1
     tasks(0).markFinished(TaskState.FINISHED, time)
-    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
       Success, tasks(0), new ExecutorMetrics, null))
 
     // executor lost, success task will be resubmitted
     time += 1
-    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
       Resubmitted, tasks(0), new ExecutorMetrics, null))
 
     // executor lost, running task will be failed and rerun
     time += 1
     tasks(1).markFinished(TaskState.FAILED, time)
-    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
       ExecutorLostFailure("1", true, Some("Lost executor")), tasks(1), new ExecutorMetrics,
       null))
 
     tasks.foreach { task =>
-      listener.onTaskStart(SparkListenerTaskStart(stage.stageId, stage.attemptNumber, task))
+      listener.onTaskStart(SparkListenerTaskStart(stage.stageId, stage.attemptNumber(), task))
     }
 
     time += 1
     tasks(0).markFinished(TaskState.FINISHED, time)
-    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
       Success, tasks(0), new ExecutorMetrics, null))
 
     time += 1
     tasks(1).markFinished(TaskState.FINISHED, time)
-    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber, "taskType",
+    listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(), "taskType",
       Success, tasks(1), new ExecutorMetrics, null))
 
     listener.onStageCompleted(SparkListenerStageCompleted(stage))
@@ -1930,7 +1930,7 @@
     assert(job.numActiveStages == 0)
   }
 
-  private def key(stage: StageInfo): Array[Int] = Array(stage.stageId, stage.attemptNumber)
+  private def key(stage: StageInfo): Array[Int] = Array(stage.stageId, stage.attemptNumber())
 
   private def check[T: ClassTag](key: Any)(fn: T => Unit): Unit = {
     val value = store.read(classTag[T].runtimeClass, key).asInstanceOf[T]
diff --git a/core/src/test/scala/org/apache/spark/status/ListenerEventsTestHelper.scala b/core/src/test/scala/org/apache/spark/status/ListenerEventsTestHelper.scala
index f93c2bc..e7d78cb 100644
--- a/core/src/test/scala/org/apache/spark/status/ListenerEventsTestHelper.scala
+++ b/core/src/test/scala/org/apache/spark/status/ListenerEventsTestHelper.scala
@@ -177,7 +177,7 @@
 
     s1Tasks.foreach { task =>
       task.markFinished(TaskState.FINISHED, time)
-      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber,
+      listener.onTaskEnd(SparkListenerTaskEnd(stage.stageId, stage.attemptNumber(),
         "taskType", Success, task, new ExecutorMetrics, s1Metrics))
     }
 
diff --git a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala
index 2af0f9c..a5e9a58 100644
--- a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala
@@ -2212,7 +2212,7 @@
     val sortedBlocks = blocks.sortBy(b => (b.shuffleId, b.mapId))
 
     val resolver = mock(classOf[MigratableResolver])
-    when(resolver.getStoredShuffles).thenReturn(blocks)
+    when(resolver.getStoredShuffles()).thenReturn(blocks)
 
     val bm = mock(classOf[BlockManager])
     when(bm.migratableResolver).thenReturn(resolver)
diff --git a/core/src/test/scala/org/apache/spark/storage/DiskBlockManagerSuite.scala b/core/src/test/scala/org/apache/spark/storage/DiskBlockManagerSuite.scala
index 48610cb..eacd1ee 100644
--- a/core/src/test/scala/org/apache/spark/storage/DiskBlockManagerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/storage/DiskBlockManagerSuite.scala
@@ -83,7 +83,7 @@
     val ids = (1 to 100).map(i => TestBlockId("test_" + i))
     val files = ids.map(id => diskBlockManager.getFile(id))
     files.foreach(file => writeToFile(file, 10))
-    assert(diskBlockManager.getAllBlocks.toSet === ids.toSet)
+    assert(diskBlockManager.getAllBlocks().toSet === ids.toSet)
   }
 
   test("SPARK-22227: non-block files are skipped") {
diff --git a/core/src/test/scala/org/apache/spark/storage/MemoryStoreSuite.scala b/core/src/test/scala/org/apache/spark/storage/MemoryStoreSuite.scala
index fd99a03..d4f04e8 100644
--- a/core/src/test/scala/org/apache/spark/storage/MemoryStoreSuite.scala
+++ b/core/src/test/scala/org/apache/spark/storage/MemoryStoreSuite.scala
@@ -609,7 +609,7 @@
     assert(putIteratorAsValues("b1", nativeObjIterator, ClassTag.Any).isRight)
     assert(putIteratorAsValues("b2", nativeObjIterator, ClassTag.Any).isRight)
 
-    memoryStore.clear
+    memoryStore.clear()
     // Check if allocator was cleared.
     while (allocator.getAllocatedMemory > 0) {
       Thread.sleep(500)
diff --git a/core/src/test/scala/org/apache/spark/ui/RealBrowserUISeleniumSuite.scala b/core/src/test/scala/org/apache/spark/ui/RealBrowserUISeleniumSuite.scala
index 185d91e..b0f1fca 100644
--- a/core/src/test/scala/org/apache/spark/ui/RealBrowserUISeleniumSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ui/RealBrowserUISeleniumSuite.scala
@@ -57,7 +57,7 @@
     withSpark(newSparkContext()) { sc =>
       sc.setLocalProperty(CallSite.LONG_FORM, "collect at <console>:25")
       sc.setLocalProperty(CallSite.SHORT_FORM, "collect at <console>:25")
-      sc.parallelize(1 to 10).collect
+      sc.parallelize(1 to 10).collect()
 
       eventually(timeout(10.seconds), interval(50.milliseconds)) {
         goToUi(sc, "/jobs")
@@ -81,7 +81,7 @@
 
   test("SPARK-31882: Link URL for Stage DAGs should not depend on paged table.") {
     withSpark(newSparkContext()) { sc =>
-      sc.parallelize(1 to 100).map(v => (v, v)).repartition(10).reduceByKey(_ + _).collect
+      sc.parallelize(1 to 100).map(v => (v, v)).repartition(10).reduceByKey(_ + _).collect()
 
       eventually(timeout(10.seconds), interval(50.microseconds)) {
         val pathWithPagedTable =
@@ -103,7 +103,7 @@
 
   test("SPARK-31886: Color barrier execution mode RDD correctly") {
     withSpark(newSparkContext()) { sc =>
-      sc.parallelize(1 to 10).barrier.mapPartitions(identity).repartition(1).collect()
+      sc.parallelize(1 to 10).barrier().mapPartitions(identity).repartition(1).collect()
 
       eventually(timeout(10.seconds), interval(50.milliseconds)) {
         goToUi(sc, "/jobs/job/?id=0")
@@ -131,7 +131,7 @@
 
   test("Search text for paged tables should not be saved") {
     withSpark(newSparkContext()) { sc =>
-      sc.parallelize(1 to 10).collect
+      sc.parallelize(1 to 10).collect()
 
       eventually(timeout(10.seconds), interval(1.seconds)) {
         val taskSearchBox = "$(\"input[aria-controls='active-tasks-table']\")"
diff --git a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala
index 7e74cc9..a2d1293 100644
--- a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala
@@ -340,7 +340,7 @@
         data.dependencies.head.asInstanceOf[ShuffleDependency[_, _, _]].shuffleHandle
       // Simulate fetch failures:
       val mappedData = data.map { x =>
-        val taskContext = TaskContext.get
+        val taskContext = TaskContext.get()
         if (taskContext.taskAttemptId() == 1) {
           // Cause the post-shuffle stage to fail on its first attempt with a single task failure
           val env = SparkEnv.get
@@ -820,10 +820,10 @@
 
   test("description for empty jobs") {
     withSpark(newSparkContext()) { sc =>
-      sc.emptyRDD[Int].collect
+      sc.emptyRDD[Int].collect()
       val description = "This is my job"
       sc.setJobDescription(description)
-      sc.emptyRDD[Int].collect
+      sc.emptyRDD[Int].collect()
 
       eventually(timeout(10.seconds), interval(50.milliseconds)) {
         goToUi(sc, "/jobs")
diff --git a/core/src/test/scala/org/apache/spark/ui/env/EnvironmentPageSuite.scala b/core/src/test/scala/org/apache/spark/ui/env/EnvironmentPageSuite.scala
index 9279187..a318e08 100644
--- a/core/src/test/scala/org/apache/spark/ui/env/EnvironmentPageSuite.scala
+++ b/core/src/test/scala/org/apache/spark/ui/env/EnvironmentPageSuite.scala
@@ -43,8 +43,8 @@
     when(info.classpathEntries).thenReturn(Seq.empty)
 
     val store = mock(classOf[AppStatusStore])
-    when(store.environmentInfo).thenReturn(info)
-    when(store.resourceProfileInfo).thenReturn(Seq.empty)
+    when(store.environmentInfo()).thenReturn(info)
+    when(store.resourceProfileInfo()).thenReturn(Seq.empty)
 
     val environmentPage = new EnvironmentPage(environmentTab, new SparkConf, store)
     val request = mock(classOf[HttpServletRequest])
diff --git a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala
index 5a6c332..3defd4b 100644
--- a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala
@@ -164,7 +164,7 @@
       .resource("gpu", 2, "myscript")
       .resource("myCustomResource", amount = Int.MaxValue + 1L, discoveryScript = "myscript2")
     rprofBuilder.require(taskReq).require(execReq)
-    val resourceProfile = rprofBuilder.build
+    val resourceProfile = rprofBuilder.build()
     resourceProfile.setResourceProfileId(21)
     val resourceProfileAdded = SparkListenerResourceProfileAdded(resourceProfile)
     testEvent(stageSubmitted, stageSubmittedJsonString)
diff --git a/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala b/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala
index 4909d5f..efa0da4 100644
--- a/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/NextIteratorSuite.scala
@@ -30,7 +30,7 @@
   test("one iteration") {
     val i = new StubIterator(Buffer(1))
     i.hasNext should be (true)
-    i.next should be (1)
+    i.next() should be (1)
     i.hasNext should be (false)
     intercept[NoSuchElementException] { i.next() }
   }
@@ -38,9 +38,9 @@
   test("two iterations") {
     val i = new StubIterator(Buffer(1, 2))
     i.hasNext should be (true)
-    i.next should be (1)
+    i.next() should be (1)
     i.hasNext should be (true)
-    i.next should be (2)
+    i.next() should be (2)
     i.hasNext should be (false)
     intercept[NoSuchElementException] { i.next() }
   }
@@ -60,8 +60,8 @@
 
   test("close is called once for non-empty iterations") {
     val i = new StubIterator(Buffer(1, 2))
-    i.next should be (1)
-    i.next should be (2)
+    i.next() should be (1)
+    i.next() should be (2)
     // close isn't called until we check for the next element
     i.closeCalled should be (0)
     i.hasNext should be (false)
diff --git a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
index 58ce15c..25f48c7 100644
--- a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala
@@ -1253,7 +1253,7 @@
     assert(isErrorOccurred)
     // if the try, catch and finally blocks don't throw exceptions
     Utils.tryWithSafeFinallyAndFailureCallbacks {}(catchBlock = {}, finallyBlock = {})
-    TaskContext.unset
+    TaskContext.unset()
   }
 
   test("load extensions") {
diff --git a/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala
index 4b63f1d..fb15028 100644
--- a/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/collection/ExternalAppendOnlyMapSuite.scala
@@ -451,7 +451,7 @@
     }
 
     val first50Keys = for ( _ <- 0 until 50) yield {
-      val (k, vs) = it.next
+      val (k, vs) = it.next()
       val sortedVs = vs.sorted
       assert(sortedVs.seq == (0 until 10).map(10 * k + _))
       k
@@ -472,7 +472,7 @@
 
 
     val next50Keys = for ( _ <- 0 until 50) yield {
-      val (k, vs) = it.next
+      val (k, vs) = it.next()
       val sortedVs = vs.sorted
       assert(sortedVs.seq == (0 until 10).map(10 * k + _))
       k
diff --git a/core/src/test/scala/org/apache/spark/util/collection/PercentileHeapSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/PercentileHeapSuite.scala
index fd1208c..20def45 100644
--- a/core/src/test/scala/org/apache/spark/util/collection/PercentileHeapSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/collection/PercentileHeapSuite.scala
@@ -26,7 +26,7 @@
   test("When PercentileHeap is empty, NoSuchElementException is thrown.") {
     val medianHeap = new PercentileHeap(0.5)
     intercept[NoSuchElementException] {
-      medianHeap.percentile
+      medianHeap.percentile()
     }
   }
 
@@ -38,8 +38,8 @@
   private def testPercentileFor(nums: Seq[Int], percentage: Double) = {
     val h = new PercentileHeap(percentage)
     Random.shuffle(nums).foreach(h.insert(_))
-    assert(h.size == nums.length)
-    assert(h.percentile == percentile(nums, percentage))
+    assert(h.size() == nums.length)
+    assert(h.percentile() == percentile(nums, percentage))
   }
 
   private val tests = Seq(
@@ -68,7 +68,7 @@
       val h = new PercentileHeap(0.95)
       shuffled.foreach { x =>
         h.insert(x)
-        for (_ <- 0 until h.size) h.percentile
+        for (_ <- 0 until h.size()) h.percentile()
       }
       System.nanoTime() - start
     }
diff --git a/core/src/test/scala/org/apache/spark/util/collection/unsafe/sort/RadixSortSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/unsafe/sort/RadixSortSuite.scala
index d33ac97..f5d417f 100644
--- a/core/src/test/scala/org/apache/spark/util/collection/unsafe/sort/RadixSortSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/collection/unsafe/sort/RadixSortSuite.scala
@@ -136,7 +136,7 @@
   def randomBitMask(rand: Random): Long = {
     var tmp = ~0L
     for (i <- 0 to rand.nextInt(5)) {
-      tmp &= rand.nextLong
+      tmp &= rand.nextLong()
     }
     tmp
   }
diff --git a/core/src/test/scala/org/apache/spark/util/random/RandomSamplerSuite.scala b/core/src/test/scala/org/apache/spark/util/random/RandomSamplerSuite.scala
index eb1aab6..8fcbfd9 100644
--- a/core/src/test/scala/org/apache/spark/util/random/RandomSamplerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/util/random/RandomSamplerSuite.scala
@@ -731,7 +731,7 @@
     val s1 = sampler.sample(data.iterator).toArray
     s1.length should be > 0
 
-    sampler = base.cloneComplement
+    sampler = base.cloneComplement()
     sampler.setSeed(seed)
     val s2 = sampler.sample(data.iterator).toArray
     s2.length should be > 0
diff --git a/examples/src/main/scala/org/apache/spark/examples/DFSReadWriteTest.scala b/examples/src/main/scala/org/apache/spark/examples/DFSReadWriteTest.scala
index 323bab4..5dfb8ec 100644
--- a/examples/src/main/scala/org/apache/spark/examples/DFSReadWriteTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/DFSReadWriteTest.scala
@@ -103,7 +103,7 @@
 
     println("Creating SparkSession")
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("DFS Read Write Test")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ExceptionHandlingTest.scala b/examples/src/main/scala/org/apache/spark/examples/ExceptionHandlingTest.scala
index 6e95318..ae55048 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ExceptionHandlingTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ExceptionHandlingTest.scala
@@ -22,12 +22,12 @@
 object ExceptionHandlingTest {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("ExceptionHandlingTest")
       .getOrCreate()
 
     spark.sparkContext.parallelize(0 until spark.sparkContext.defaultParallelism).foreach { i =>
-      if (math.random > 0.75) {
+      if (math.random() > 0.75) {
         throw new Exception("Testing exception handling")
       }
     }
diff --git a/examples/src/main/scala/org/apache/spark/examples/GroupByTest.scala b/examples/src/main/scala/org/apache/spark/examples/GroupByTest.scala
index c07c1af..8368fca 100644
--- a/examples/src/main/scala/org/apache/spark/examples/GroupByTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/GroupByTest.scala
@@ -28,7 +28,7 @@
 object GroupByTest {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("GroupBy Test")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/HdfsTest.scala b/examples/src/main/scala/org/apache/spark/examples/HdfsTest.scala
index 4869867..6443bbe 100644
--- a/examples/src/main/scala/org/apache/spark/examples/HdfsTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/HdfsTest.scala
@@ -32,7 +32,7 @@
       System.exit(1)
     }
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("HdfsTest")
       .getOrCreate()
     val file = spark.read.text(args(0)).rdd
diff --git a/examples/src/main/scala/org/apache/spark/examples/LocalALS.scala b/examples/src/main/scala/org/apache/spark/examples/LocalALS.scala
index 87c2f68..06c9173 100644
--- a/examples/src/main/scala/org/apache/spark/examples/LocalALS.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/LocalALS.scala
@@ -134,10 +134,10 @@
   }
 
   private def randomVector(n: Int): RealVector =
-    new ArrayRealVector(Array.fill(n)(math.random))
+    new ArrayRealVector(Array.fill(n)(math.random()))
 
   private def randomMatrix(rows: Int, cols: Int): RealMatrix =
-    new Array2DRowRealMatrix(Array.fill(rows, cols)(math.random))
+    new Array2DRowRealMatrix(Array.fill(rows, cols)(math.random()))
 
 }
 // scalastyle:on println
diff --git a/examples/src/main/scala/org/apache/spark/examples/LocalPi.scala b/examples/src/main/scala/org/apache/spark/examples/LocalPi.scala
index 7660ffd..c77d99c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/LocalPi.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/LocalPi.scala
@@ -24,8 +24,8 @@
   def main(args: Array[String]): Unit = {
     var count = 0
     for (i <- 1 to 100000) {
-      val x = random * 2 - 1
-      val y = random * 2 - 1
+      val x = random() * 2 - 1
+      val y = random() * 2 - 1
       if (x*x + y*y <= 1) count += 1
     }
     println(s"Pi is roughly ${4 * count / 100000.0}")
diff --git a/examples/src/main/scala/org/apache/spark/examples/MiniReadWriteTest.scala b/examples/src/main/scala/org/apache/spark/examples/MiniReadWriteTest.scala
index aa88cd5..c003dc8 100644
--- a/examples/src/main/scala/org/apache/spark/examples/MiniReadWriteTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/MiniReadWriteTest.scala
@@ -96,7 +96,7 @@
 
     println("Creating SparkSession")
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("Mini Read Write Test")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/MultiBroadcastTest.scala b/examples/src/main/scala/org/apache/spark/examples/MultiBroadcastTest.scala
index 0692c51..d6427cd 100644
--- a/examples/src/main/scala/org/apache/spark/examples/MultiBroadcastTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/MultiBroadcastTest.scala
@@ -29,7 +29,7 @@
   def main(args: Array[String]): Unit = {
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("Multi-Broadcast Test")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala b/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala
index 2bd7c3e..086a004 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SimpleSkewedGroupByTest.scala
@@ -28,7 +28,7 @@
 object SimpleSkewedGroupByTest {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SimpleSkewedGroupByTest")
       .getOrCreate()
 
@@ -50,16 +50,16 @@
           result(i) = (offset, byteArr)
         } else {
           // generate a key for one of the other reducers
-          val key = 1 + ranGen.nextInt(numReducers-1) + offset
+          val key = 1 + ranGen.nextInt(numReducers - 1) + offset
           result(i) = (key, byteArr)
         }
       }
       result
-    }.cache
+    }.cache()
     // Enforce that everything has been calculated and in cache
-    pairs1.count
+    pairs1.count()
 
-    println(s"RESULT: ${pairs1.groupByKey(numReducers).count}")
+    println(s"RESULT: ${pairs1.groupByKey(numReducers).count()}")
 
     spark.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/SkewedGroupByTest.scala b/examples/src/main/scala/org/apache/spark/examples/SkewedGroupByTest.scala
index 2e7abd6..9001ab0 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SkewedGroupByTest.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SkewedGroupByTest.scala
@@ -28,7 +28,7 @@
 object SkewedGroupByTest {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("GroupBy Test")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkALS.scala b/examples/src/main/scala/org/apache/spark/examples/SparkALS.scala
index 651f022..42cc0a8 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkALS.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkALS.scala
@@ -109,7 +109,7 @@
     println(s"Running with M=$M, U=$U, F=$F, iters=$ITERATIONS")
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SparkALS")
       .getOrCreate()
 
@@ -141,10 +141,10 @@
   }
 
   private def randomVector(n: Int): RealVector =
-    new ArrayRealVector(Array.fill(n)(math.random))
+    new ArrayRealVector(Array.fill(n)(math.random()))
 
   private def randomMatrix(rows: Int, cols: Int): RealMatrix =
-    new Array2DRowRealMatrix(Array.fill(rows, cols)(math.random))
+    new Array2DRowRealMatrix(Array.fill(rows, cols)(math.random()))
 
 }
 // scalastyle:on println
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
index 8c09ce6..7bbe594 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
@@ -67,7 +67,7 @@
     showWarning()
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SparkHdfsLR")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala b/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala
index e0ab07a..a6e1de7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkKMeans.scala
@@ -67,7 +67,7 @@
     showWarning()
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SparkKMeans")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala b/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala
index deb6668..469e429 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkLR.scala
@@ -64,7 +64,7 @@
     showWarning()
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SparkLR")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkPageRank.scala b/examples/src/main/scala/org/apache/spark/examples/SparkPageRank.scala
index 3bd475c..27e1d46 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkPageRank.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkPageRank.scala
@@ -56,7 +56,7 @@
     showWarning()
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SparkPageRank")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
index a8eec6a..468bc91 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkPi.scala
@@ -26,14 +26,14 @@
 object SparkPi {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("Spark Pi")
       .getOrCreate()
     val slices = if (args.length > 0) args(0).toInt else 2
     val n = math.min(100000L * slices, Int.MaxValue).toInt // avoid overflow
     val count = spark.sparkContext.parallelize(1 until n, slices).map { i =>
-      val x = random * 2 - 1
-      val y = random * 2 - 1
+      val x = random() * 2 - 1
+      val y = random() * 2 - 1
       if (x*x + y*y <= 1) 1 else 0
     }.reduce(_ + _)
     println(s"Pi is roughly ${4.0 * count / (n - 1)}")
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkTC.scala b/examples/src/main/scala/org/apache/spark/examples/SparkTC.scala
index 7a6fa9a..11f730c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkTC.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkTC.scala
@@ -43,7 +43,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SparkTC")
       .getOrCreate()
     val slices = if (args.length > 0) args(0).toInt else 2
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/AggregateMessagesExample.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/AggregateMessagesExample.scala
index 8441b5a..33f7156 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/AggregateMessagesExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/AggregateMessagesExample.scala
@@ -37,7 +37,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession.
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     val sc = spark.sparkContext
@@ -63,7 +63,7 @@
       olderFollowers.mapValues( (id, value) =>
         value match { case (count, totalAge) => totalAge / count } )
     // Display the results
-    avgAgeOfOlderFollowers.collect.foreach(println(_))
+    avgAgeOfOlderFollowers.collect().foreach(println(_))
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
index 0726fe9..a1e6b03 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
@@ -89,8 +89,8 @@
           vertexStorageLevel = vertexStorageLevel).cache()
         val graph = partitionStrategy.foldLeft(unpartitionedGraph)(_.partitionBy(_))
 
-        println(s"GRAPHX: Number of vertices ${graph.vertices.count}")
-        println(s"GRAPHX: Number of edges ${graph.edges.count}")
+        println(s"GRAPHX: Number of vertices ${graph.vertices.count()}")
+        println(s"GRAPHX: Number of edges ${graph.edges.count()}")
 
         val pr = (numIterOpt match {
           case Some(numIter) => PageRank.run(graph, numIter)
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/ComprehensiveExample.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/ComprehensiveExample.scala
index 6598863..314739a 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/ComprehensiveExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/ComprehensiveExample.scala
@@ -39,7 +39,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession.
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     val sc = spark.sparkContext
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/ConnectedComponentsExample.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/ConnectedComponentsExample.scala
index 5377ddb..db99dde 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/ConnectedComponentsExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/ConnectedComponentsExample.scala
@@ -41,7 +41,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession.
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     val sc = spark.sparkContext
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/PageRankExample.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/PageRankExample.scala
index 9e9affc..772b9e3 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/PageRankExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/PageRankExample.scala
@@ -34,7 +34,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession.
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     val sc = spark.sparkContext
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/SSSPExample.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/SSSPExample.scala
index 5e8b196..0a888a7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/SSSPExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/SSSPExample.scala
@@ -36,7 +36,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession.
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     val sc = spark.sparkContext
@@ -60,7 +60,7 @@
       },
       (a, b) => math.min(a, b) // Merge Message
     )
-    println(sssp.vertices.collect.mkString("\n"))
+    println(sssp.vertices.collect().mkString("\n"))
     // $example off$
 
     spark.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala
index 8bc9c0a..6ba0371 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/SynthBenchmark.scala
@@ -116,7 +116,7 @@
       println(s"Total PageRank = $totalPR")
     } else if (app == "cc") {
       println("Running Connected Components")
-      val numComponents = graph.connectedComponents.vertices.map(_._2).distinct().count()
+      val numComponents = graph.connectedComponents().vertices.map(_._2).distinct().count()
       println(s"Number of components = $numComponents")
     }
     val runTime = System.currentTimeMillis() - startTime
diff --git a/examples/src/main/scala/org/apache/spark/examples/graphx/TriangleCountingExample.scala b/examples/src/main/scala/org/apache/spark/examples/graphx/TriangleCountingExample.scala
index b9bff69..1cb82f0 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/TriangleCountingExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/TriangleCountingExample.scala
@@ -42,7 +42,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession.
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     val sc = spark.sparkContext
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/AFTSurvivalRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/AFTSurvivalRegressionExample.scala
index cdb33f4..999555f 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/AFTSurvivalRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/AFTSurvivalRegressionExample.scala
@@ -35,7 +35,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("AFTSurvivalRegressionExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala
index 354e65c..82b4136 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala
@@ -44,7 +44,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("ALSExample")
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/BinarizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/BinarizerExample.scala
index c2852aa..38e7eca 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/BinarizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/BinarizerExample.scala
@@ -26,7 +26,7 @@
 object BinarizerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("BinarizerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/BisectingKMeansExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/BisectingKMeansExample.scala
index 14e13df..7dc4c5e 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/BisectingKMeansExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/BisectingKMeansExample.scala
@@ -37,7 +37,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("BisectingKMeansExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/BucketedRandomProjectionLSHExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/BucketedRandomProjectionLSHExample.scala
index 58f9fb3..b287a9d 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/BucketedRandomProjectionLSHExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/BucketedRandomProjectionLSHExample.scala
@@ -34,7 +34,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("BucketedRandomProjectionLSHExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/BucketizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/BucketizerExample.scala
index 7e65f9c..185a9f3 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/BucketizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/BucketizerExample.scala
@@ -32,7 +32,7 @@
 object BucketizerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("BucketizerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ChiSqSelectorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ChiSqSelectorExample.scala
index 1a67a6e..7d23cbe 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ChiSqSelectorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ChiSqSelectorExample.scala
@@ -27,7 +27,7 @@
 object ChiSqSelectorExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("ChiSqSelectorExample")
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala
index 5146fd0..3748c50 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ChiSquareTestExample.scala
@@ -35,7 +35,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("ChiSquareTestExample")
       .getOrCreate()
     import spark.implicits._
@@ -51,7 +51,7 @@
     )
 
     val df = data.toDF("label", "features")
-    val chi = ChiSquareTest.test(df, "features", "label").head
+    val chi = ChiSquareTest.test(df, "features", "label").head()
     println(s"pValues = ${chi.getAs[Vector](0)}")
     println(s"degreesOfFreedom ${chi.getSeq[Int](1).mkString("[", ",", "]")}")
     println(s"statistics ${chi.getAs[Vector](2)}")
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
index d7f1fc8..994fe34 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/CorrelationExample.scala
@@ -36,7 +36,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("CorrelationExample")
       .getOrCreate()
     import spark.implicits._
@@ -50,10 +50,10 @@
     )
 
     val df = data.map(Tuple1.apply).toDF("features")
-    val Row(coeff1: Matrix) = Correlation.corr(df, "features").head
+    val Row(coeff1: Matrix) = Correlation.corr(df, "features").head()
     println(s"Pearson correlation matrix:\n $coeff1")
 
-    val Row(coeff2: Matrix) = Correlation.corr(df, "features", "spearman").head
+    val Row(coeff2: Matrix) = Correlation.corr(df, "features", "spearman").head()
     println(s"Spearman correlation matrix:\n $coeff2")
     // $example off$
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/CountVectorizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/CountVectorizerExample.scala
index 947ca5f..e5921ae 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/CountVectorizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/CountVectorizerExample.scala
@@ -26,7 +26,7 @@
 object CountVectorizerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("CountVectorizerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DCTExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DCTExample.scala
index 3383171..89fadd3 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DCTExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DCTExample.scala
@@ -27,7 +27,7 @@
 object DCTExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("DCTExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
index 4377efd..e0ec905 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DataFrameExample.scala
@@ -62,7 +62,7 @@
 
   def run(params: Params): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"DataFrameExample with $params")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala
index 7f65fa3..e0c029e 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeClassificationExample.scala
@@ -30,7 +30,7 @@
 object DecisionTreeClassificationExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("DecisionTreeClassificationExample")
       .getOrCreate()
     // $example on$
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeExample.scala
index ef38163..9795e52 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeExample.scala
@@ -166,7 +166,7 @@
       algo: String,
       fracTest: Double): (DataFrame, DataFrame) = {
     val spark = SparkSession
-      .builder
+      .builder()
       .getOrCreate()
 
     // Load training data
@@ -199,7 +199,7 @@
 
   def run(params: Params): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"DecisionTreeExample with $params")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala
index aaaecae..39122c9 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DecisionTreeRegressionExample.scala
@@ -30,7 +30,7 @@
 object DecisionTreeRegressionExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("DecisionTreeRegressionExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
index bfee330..46216e9 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
@@ -39,7 +39,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("DeveloperApiExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ElementwiseProductExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ElementwiseProductExample.scala
index c0ffc01..91f1320 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ElementwiseProductExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ElementwiseProductExample.scala
@@ -27,7 +27,7 @@
 object ElementwiseProductExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("ElementwiseProductExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala
index e5d91f1..56a4cd2 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/EstimatorTransformerParamExample.scala
@@ -30,7 +30,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("EstimatorTransformerParamExample")
       .getOrCreate()
 
@@ -58,7 +58,7 @@
     // we can view the parameters it used during fit().
     // This prints the parameter (name: value) pairs, where names are unique IDs for this
     // LogisticRegression instance.
-    println(s"Model 1 was fit using parameters: ${model1.parent.extractParamMap}")
+    println(s"Model 1 was fit using parameters: ${model1.parent.extractParamMap()}")
 
     // We may alternatively specify parameters using a ParamMap,
     // which supports several methods for specifying parameters.
@@ -73,7 +73,7 @@
     // Now learn a new model using the paramMapCombined parameters.
     // paramMapCombined overrides all parameters set earlier via lr.set* methods.
     val model2 = lr.fit(training, paramMapCombined)
-    println(s"Model 2 was fit using parameters: ${model2.parent.extractParamMap}")
+    println(s"Model 2 was fit using parameters: ${model2.parent.extractParamMap()}")
 
     // Prepare test data.
     val test = spark.createDataFrame(Seq(
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/FMClassifierExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/FMClassifierExample.scala
index 612a76fd..6b83224 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/FMClassifierExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/FMClassifierExample.scala
@@ -29,7 +29,7 @@
 object FMClassifierExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("FMClassifierExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/FMRegressorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/FMRegressorExample.scala
index 6bb06ea..0144188 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/FMRegressorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/FMRegressorExample.scala
@@ -29,7 +29,7 @@
 object FMRegressorExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("FMRegressorExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/FPGrowthExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/FPGrowthExample.scala
index bece0d9..b3c9a58 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/FPGrowthExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/FPGrowthExample.scala
@@ -33,7 +33,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/FeatureHasherExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/FeatureHasherExample.scala
index 1aed10b..a39cefc 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/FeatureHasherExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/FeatureHasherExample.scala
@@ -25,7 +25,7 @@
 object FeatureHasherExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("FeatureHasherExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GBTExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GBTExample.scala
index ca4235d..5a9a526 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GBTExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GBTExample.scala
@@ -136,7 +136,7 @@
 
   def run(params: Params): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"GBTExample with $params")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GaussianMixtureExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GaussianMixtureExample.scala
index 5e4bea4..bf8542d 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GaussianMixtureExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GaussianMixtureExample.scala
@@ -34,7 +34,7 @@
 object GaussianMixtureExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-        .builder
+      .builder()
         .appName(s"${this.getClass.getSimpleName}")
         .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GeneralizedLinearRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GeneralizedLinearRegressionExample.scala
index 1b86d7c..5be5c72 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GeneralizedLinearRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GeneralizedLinearRegressionExample.scala
@@ -35,7 +35,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("GeneralizedLinearRegressionExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala
index a6d078d..1a0a86d 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeClassifierExample.scala
@@ -29,7 +29,7 @@
 object GradientBoostedTreeClassifierExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("GradientBoostedTreeClassifierExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
index 3feb234..d53f152 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/GradientBoostedTreeRegressorExample.scala
@@ -29,7 +29,7 @@
 object GradientBoostedTreeRegressorExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("GradientBoostedTreeRegressorExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ImputerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ImputerExample.scala
index 49e98d0..0d2a797 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ImputerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ImputerExample.scala
@@ -30,7 +30,7 @@
 object ImputerExample {
 
   def main(args: Array[String]): Unit = {
-    val spark = SparkSession.builder
+    val spark = SparkSession.builder()
       .appName("ImputerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/IndexToStringExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/IndexToStringExample.scala
index b3642c0..5b04fe5 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/IndexToStringExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/IndexToStringExample.scala
@@ -27,7 +27,7 @@
 object IndexToStringExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("IndexToStringExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/InteractionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/InteractionExample.scala
index 8113c99..6eed747 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/InteractionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/InteractionExample.scala
@@ -27,7 +27,7 @@
 object InteractionExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("InteractionExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/IsotonicRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/IsotonicRegressionExample.scala
index 9bac16e..05f72c8 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/IsotonicRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/IsotonicRegressionExample.scala
@@ -34,7 +34,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/KMeansExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/KMeansExample.scala
index 2bc8184..18ed687 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/KMeansExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/KMeansExample.scala
@@ -36,7 +36,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LDAExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LDAExample.scala
index 4215d37..8b83105 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/LDAExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/LDAExample.scala
@@ -34,7 +34,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionExample.scala
index 370c6fd..bf21da9 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionExample.scala
@@ -102,7 +102,7 @@
 
   def run(params: Params): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"LinearRegressionExample with $params")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionWithElasticNetExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionWithElasticNetExample.scala
index 4540a8d..566cf8c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionWithElasticNetExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/LinearRegressionWithElasticNetExample.scala
@@ -27,7 +27,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("LinearRegressionWithElasticNetExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LinearSVCExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LinearSVCExample.scala
index 5f43e65..1ffdb10 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/LinearSVCExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/LinearSVCExample.scala
@@ -27,7 +27,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("LinearSVCExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala
index b64ab479..27f892b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionExample.scala
@@ -110,7 +110,7 @@
 
   def run(params: Params): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"LogisticRegressionExample with $params")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionSummaryExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionSummaryExample.scala
index 0368dcb..e7c8a93 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionSummaryExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionSummaryExample.scala
@@ -28,7 +28,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("LogisticRegressionSummaryExample")
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionWithElasticNetExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionWithElasticNetExample.scala
index 1847104..0d4fe3e 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionWithElasticNetExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/LogisticRegressionWithElasticNetExample.scala
@@ -27,7 +27,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("LogisticRegressionWithElasticNetExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/MaxAbsScalerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/MaxAbsScalerExample.scala
index 85d0713..7437308 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/MaxAbsScalerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/MaxAbsScalerExample.scala
@@ -26,7 +26,7 @@
 object MaxAbsScalerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("MaxAbsScalerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/MinHashLSHExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/MinHashLSHExample.scala
index 8515821..091c197 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/MinHashLSHExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/MinHashLSHExample.scala
@@ -34,7 +34,7 @@
   def main(args: Array[String]): Unit = {
     // Creates a SparkSession
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("MinHashLSHExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/MinMaxScalerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/MinMaxScalerExample.scala
index 9ee6d9b..bc1502c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/MinMaxScalerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/MinMaxScalerExample.scala
@@ -27,7 +27,7 @@
 object MinMaxScalerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("MinMaxScalerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaCrossValidationExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaCrossValidationExample.scala
index 87d96dd..4c9be6c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaCrossValidationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaCrossValidationExample.scala
@@ -42,7 +42,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("ModelSelectionViaCrossValidationExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaTrainValidationSplitExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaTrainValidationSplitExample.scala
index 71e41e7..43aab94 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaTrainValidationSplitExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/ModelSelectionViaTrainValidationSplitExample.scala
@@ -36,7 +36,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("ModelSelectionViaTrainValidationSplitExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala
index 1f7dbdd..4c0d145 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/MulticlassLogisticRegressionWithElasticNetExample.scala
@@ -27,7 +27,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("MulticlassLogisticRegressionWithElasticNetExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala
index 646f46a..cc9c99b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/MultilayerPerceptronClassifierExample.scala
@@ -31,7 +31,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("MultilayerPerceptronClassifierExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/NGramExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/NGramExample.scala
index d2183d6..0a11ba1 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/NGramExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/NGramExample.scala
@@ -26,7 +26,7 @@
 object NGramExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("NGramExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala
index 50c70c6..3f8074e 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/NaiveBayesExample.scala
@@ -27,7 +27,7 @@
 object NaiveBayesExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("NaiveBayesExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/NormalizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/NormalizerExample.scala
index 989d250..8affc3b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/NormalizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/NormalizerExample.scala
@@ -27,7 +27,7 @@
 object NormalizerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("NormalizerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/OneHotEncoderExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/OneHotEncoderExample.scala
index 742f3cd..e9c08fc 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/OneHotEncoderExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/OneHotEncoderExample.scala
@@ -26,7 +26,7 @@
 object OneHotEncoderExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("OneHotEncoderExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/OneVsRestExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/OneVsRestExample.scala
index 86e70e8a..2b837fb 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/OneVsRestExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/OneVsRestExample.scala
@@ -36,7 +36,7 @@
 object OneVsRestExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"OneVsRestExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/PCAExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/PCAExample.scala
index 4e1d7cd..4a0fd2b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/PCAExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/PCAExample.scala
@@ -27,7 +27,7 @@
 object PCAExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("PCAExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/PipelineExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/PipelineExample.scala
index 12f8663..7556d82 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/PipelineExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/PipelineExample.scala
@@ -31,7 +31,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("PipelineExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/PolynomialExpansionExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/PolynomialExpansionExample.scala
index f117b03..2dbfe6c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/PolynomialExpansionExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/PolynomialExpansionExample.scala
@@ -27,7 +27,7 @@
 object PolynomialExpansionExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("PolynomialExpansionExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/PowerIterationClusteringExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/PowerIterationClusteringExample.scala
index ca8f7af..34bb703 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/PowerIterationClusteringExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/PowerIterationClusteringExample.scala
@@ -26,7 +26,7 @@
 object PowerIterationClusteringExample {
    def main(args: Array[String]): Unit = {
      val spark = SparkSession
-       .builder
+       .builder()
        .appName(s"${this.getClass.getSimpleName}")
        .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/PrefixSpanExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/PrefixSpanExample.scala
index b4e0811..e65b9e7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/PrefixSpanExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/PrefixSpanExample.scala
@@ -33,7 +33,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"${this.getClass.getSimpleName}")
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
index 55823fe..3e022d2 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/QuantileDiscretizerExample.scala
@@ -25,7 +25,7 @@
 object QuantileDiscretizerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("QuantileDiscretizerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/RFormulaExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/RFormulaExample.scala
index 3498fa8..dc6cc7d68 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/RFormulaExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/RFormulaExample.scala
@@ -26,7 +26,7 @@
 object RFormulaExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("RFormulaExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala
index 778a8ef..b4021cd 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestClassifierExample.scala
@@ -29,7 +29,7 @@
 object RandomForestClassifierExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("RandomForestClassifierExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestExample.scala
index 6ba14bc..39ba1c7 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestExample.scala
@@ -142,7 +142,7 @@
 
   def run(params: Params): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName(s"RandomForestExample with $params")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala
index 2679fcb..2493dca 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/RandomForestRegressorExample.scala
@@ -29,7 +29,7 @@
 object RandomForestRegressorExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("RandomForestRegressorExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/RobustScalerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/RobustScalerExample.scala
index 4f40c90..f0cf0af 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/RobustScalerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/RobustScalerExample.scala
@@ -26,7 +26,7 @@
 object RobustScalerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("RobustScalerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/SQLTransformerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/SQLTransformerExample.scala
index bf6a484..1137504 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/SQLTransformerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/SQLTransformerExample.scala
@@ -26,7 +26,7 @@
 object SQLTransformerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SQLTransformerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/StandardScalerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/StandardScalerExample.scala
index 4d668e8..77a63c5 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/StandardScalerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/StandardScalerExample.scala
@@ -26,7 +26,7 @@
 object StandardScalerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StandardScalerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/StopWordsRemoverExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/StopWordsRemoverExample.scala
index 369a6ff..510a806 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/StopWordsRemoverExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/StopWordsRemoverExample.scala
@@ -26,7 +26,7 @@
 object StopWordsRemoverExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StopWordsRemoverExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/StringIndexerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/StringIndexerExample.scala
index 63f273e..bcfd1a8 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/StringIndexerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/StringIndexerExample.scala
@@ -26,7 +26,7 @@
 object StringIndexerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StringIndexerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/SummarizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/SummarizerExample.scala
index 2f54d1d..552f686 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/SummarizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/SummarizerExample.scala
@@ -27,7 +27,7 @@
 object SummarizerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("SummarizerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/TfIdfExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/TfIdfExample.scala
index 6121c81..c3c9df5 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/TfIdfExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/TfIdfExample.scala
@@ -27,7 +27,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("TfIdfExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/TokenizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/TokenizerExample.scala
index 1547776..b29e965 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/TokenizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/TokenizerExample.scala
@@ -27,7 +27,7 @@
 object TokenizerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("TokenizerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/UnivariateFeatureSelectorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/UnivariateFeatureSelectorExample.scala
index e4932db..4288bd5 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/UnivariateFeatureSelectorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/UnivariateFeatureSelectorExample.scala
@@ -34,7 +34,7 @@
 object UnivariateFeatureSelectorExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("UnivariateFeatureSelectorExample")
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/VarianceThresholdSelectorExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/VarianceThresholdSelectorExample.scala
index e418526..6a40bb3 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/VarianceThresholdSelectorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/VarianceThresholdSelectorExample.scala
@@ -34,7 +34,7 @@
 object VarianceThresholdSelectorExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("VarianceThresholdSelectorExample")
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/VectorAssemblerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/VectorAssemblerExample.scala
index 3d5c7ef..b7b2f5c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/VectorAssemblerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/VectorAssemblerExample.scala
@@ -27,7 +27,7 @@
 object VectorAssemblerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("VectorAssemblerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
index 96bb8ea..222b17d 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/VectorIndexerExample.scala
@@ -26,7 +26,7 @@
 object VectorIndexerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("VectorIndexerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/VectorSizeHintExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/VectorSizeHintExample.scala
index 688731a..b2e562a 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/VectorSizeHintExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/VectorSizeHintExample.scala
@@ -27,7 +27,7 @@
 object VectorSizeHintExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("VectorSizeHintExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/VectorSlicerExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/VectorSlicerExample.scala
index 9a0af5d..1272782 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/VectorSlicerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/VectorSlicerExample.scala
@@ -31,7 +31,7 @@
 object VectorSlicerExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("VectorSlicerExample")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/Word2VecExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/Word2VecExample.scala
index 8ff0e8c..42f6fb0 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/Word2VecExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/Word2VecExample.scala
@@ -28,7 +28,7 @@
 object Word2VecExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("Word2Vec example")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala
index a606cc4..3f9ec1a 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/BinaryClassificationMetricsExample.scala
@@ -46,7 +46,7 @@
       .run(training)
 
     // Clear the prediction threshold so the model will return probabilities
-    model.clearThreshold
+    model.clearThreshold()
 
     // Compute raw scores on the test set
     val predictionAndLabels = test.map { case LabeledPoint(label, features) =>
@@ -58,44 +58,44 @@
     val metrics = new BinaryClassificationMetrics(predictionAndLabels)
 
     // Precision by threshold
-    val precision = metrics.precisionByThreshold
-    precision.collect.foreach { case (t, p) =>
+    val precision = metrics.precisionByThreshold()
+    precision.collect().foreach { case (t, p) =>
       println(s"Threshold: $t, Precision: $p")
     }
 
     // Recall by threshold
-    val recall = metrics.recallByThreshold
-    recall.collect.foreach { case (t, r) =>
+    val recall = metrics.recallByThreshold()
+    recall.collect().foreach { case (t, r) =>
       println(s"Threshold: $t, Recall: $r")
     }
 
     // Precision-Recall Curve
-    val PRC = metrics.pr
+    val PRC = metrics.pr()
 
     // F-measure
-    val f1Score = metrics.fMeasureByThreshold
-    f1Score.collect.foreach { case (t, f) =>
+    val f1Score = metrics.fMeasureByThreshold()
+    f1Score.collect().foreach { case (t, f) =>
       println(s"Threshold: $t, F-score: $f, Beta = 1")
     }
 
     val beta = 0.5
     val fScore = metrics.fMeasureByThreshold(beta)
-    fScore.collect.foreach { case (t, f) =>
+    fScore.collect().foreach { case (t, f) =>
       println(s"Threshold: $t, F-score: $f, Beta = 0.5")
     }
 
     // AUPRC
-    val auPRC = metrics.areaUnderPR
+    val auPRC = metrics.areaUnderPR()
     println(s"Area under precision-recall curve = $auPRC")
 
     // Compute thresholds used in ROC and PR curves
     val thresholds = precision.map(_._1)
 
     // ROC Curve
-    val roc = metrics.roc
+    val roc = metrics.roc()
 
     // AUROC
-    val auROC = metrics.areaUnderROC
+    val auROC = metrics.areaUnderROC()
     println(s"Area under ROC = $auROC")
     // $example off$
     sc.stop()
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/ChiSqSelectorExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/ChiSqSelectorExample.scala
index 6ed59a3..d68443d 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/ChiSqSelectorExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/ChiSqSelectorExample.scala
@@ -53,7 +53,7 @@
     // $example off$
 
     println("filtered data: ")
-    filteredData.collect.foreach(x => println(x))
+    filteredData.collect().foreach(x => println(x))
 
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/ElementwiseProductExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/ElementwiseProductExample.scala
index d6ec678..e69e0dc 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/ElementwiseProductExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/ElementwiseProductExample.scala
@@ -45,10 +45,10 @@
     // $example off$
 
     println("transformedData: ")
-    transformedData.collect.foreach(x => println(x))
+    transformedData.collect().foreach(x => println(x))
 
     println("transformedData2: ")
-    transformedData2.collect.foreach(x => println(x))
+    transformedData2.collect().foreach(x => println(x))
 
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
index 3c56e19..ebfd772 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/GradientBoostingClassificationExample.scala
@@ -53,7 +53,7 @@
       val prediction = model.predict(point.features)
       (point.label, prediction)
     }
-    val testErr = labelAndPreds.filter(r => r._1 != r._2).count.toDouble / testData.count()
+    val testErr = labelAndPreds.filter(r => r._1 != r._2).count().toDouble / testData.count()
     println(s"Test Error = $testErr")
     println(s"Learned classification GBT model:\n ${model.toDebugString}")
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LDAExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LDAExample.scala
index d80f54d..c00f89b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/LDAExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LDAExample.scala
@@ -193,7 +193,7 @@
       stopwordFile: String): (RDD[(Long, Vector)], Array[String], Long) = {
 
     val spark = SparkSession
-      .builder
+      .builder()
       .sparkContext(sc)
       .getOrCreate()
     import spark.implicits._
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
index 55a45b3..e3465f1 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LatentDirichletAllocationExample.scala
@@ -36,7 +36,7 @@
     val data = sc.textFile("data/mllib/sample_lda_data.txt")
     val parsedData = data.map(s => Vectors.dense(s.trim.split(' ').map(_.toDouble)))
     // Index documents with unique IDs
-    val corpus = parsedData.zipWithIndex.map(_.swap).cache()
+    val corpus = parsedData.zipWithIndex().map(_.swap).cache()
 
     // Cluster the documents into three topics using LDA
     val ldaModel = new LDA().setK(3).run(corpus)
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/NormalizerExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/NormalizerExample.scala
index b1cad7b..2b33a7e 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/NormalizerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/NormalizerExample.scala
@@ -46,10 +46,10 @@
     // $example off$
 
     println("data1: ")
-    data1.collect.foreach(x => println(x))
+    data1.collect().foreach(x => println(x))
 
     println("data2: ")
-    data2.collect.foreach(x => println(x))
+    data2.collect().foreach(x => println(x))
 
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala
index 96deafd..3ba8eea 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala
@@ -41,7 +41,7 @@
     val clusters = KMeans.train(parsedData, numClusters, numIterations)
 
     // Export to PMML to a String in PMML format
-    println(s"PMML Model:\n ${clusters.toPMML}")
+    println(s"PMML Model:\n ${clusters.toPMML()}")
 
     // Export the model to a local file in PMML format
     clusters.toPMML("/tmp/kmeans.xml")
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
index 246e71d..ce2b9ab 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/RandomForestClassificationExample.scala
@@ -54,7 +54,7 @@
       val prediction = model.predict(point.features)
       (point.label, prediction)
     }
-    val testErr = labelAndPreds.filter(r => r._1 != r._2).count.toDouble / testData.count()
+    val testErr = labelAndPreds.filter(r => r._1 != r._2).count().toDouble / testData.count()
     println(s"Test Error = $testErr")
     println(s"Learned classification forest model:\n ${model.toDebugString}")
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/RankingMetricsExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/RankingMetricsExample.scala
index 7a7501e..ece6afb 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/RankingMetricsExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/RankingMetricsExample.scala
@@ -27,7 +27,7 @@
 object RankingMetricsExample {
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("RankingMetricsExample")
       .getOrCreate()
     // $example on$
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/StandardScalerExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/StandardScalerExample.scala
index 66a608c..38a8be4 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/StandardScalerExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/StandardScalerExample.scala
@@ -49,10 +49,10 @@
     // $example off$
 
     println("data1: ")
-    data1.collect.foreach(x => println(x))
+    data1.collect().foreach(x => println(x))
 
     println("data2: ")
-    data2.collect.foreach(x => println(x))
+    data2.collect().foreach(x => println(x))
 
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/TFIDFExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/TFIDFExample.scala
index 14b2a20..dae1f4c 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/TFIDFExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/TFIDFExample.scala
@@ -55,10 +55,10 @@
     // $example off$
 
     println("tfidf: ")
-    tfidf.collect.foreach(x => println(x))
+    tfidf.collect().foreach(x => println(x))
 
     println("tfidfIgnore: ")
-    tfidfIgnore.collect.foreach(x => println(x))
+    tfidfIgnore.collect().foreach(x => println(x))
 
     sc.stop()
   }
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
index 4fd482d..9c33e87 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
@@ -31,7 +31,7 @@
   def main(args: Array[String]): Unit = {
     // $example on:init_session$
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("Spark Examples")
       .config("spark.some.config.option", "some-value")
       .getOrCreate()
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/SimpleTypedAggregator.scala b/examples/src/main/scala/org/apache/spark/examples/sql/SimpleTypedAggregator.scala
index 5d11fb2..7aabd18 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/SimpleTypedAggregator.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/SimpleTypedAggregator.scala
@@ -25,7 +25,7 @@
 
   def main(args: Array[String]): Unit = {
     val spark = SparkSession
-      .builder
+      .builder()
       .master("local")
       .appName("common typed aggregator implementations")
       .getOrCreate()
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredComplexSessionization.scala b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredComplexSessionization.scala
index f25ba29..4b228de 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredComplexSessionization.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredComplexSessionization.scala
@@ -102,7 +102,7 @@
     val port = args(1).toInt
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StructuredComplexSessionization")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKafkaWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKafkaWordCount.scala
index 2aab49c..b2755f8 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKafkaWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKafkaWordCount.scala
@@ -60,7 +60,7 @@
       if (args.length > 3) args(3) else "/tmp/temporary-" + UUID.randomUUID.toString
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StructuredKafkaWordCount")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKerberizedKafkaWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKerberizedKafkaWordCount.scala
index 1f7d2c7..013a3c8 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKerberizedKafkaWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredKerberizedKafkaWordCount.scala
@@ -99,7 +99,7 @@
       if (args.length > 3) args(3) else "/tmp/temporary-" + UUID.randomUUID.toString
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StructuredKerberizedKafkaWordCount")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCount.scala
index 6dbc70b..3e14e14 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCount.scala
@@ -44,7 +44,7 @@
     val port = args(1).toInt
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StructuredNetworkWordCount")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCountWindowed.scala b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCountWindowed.scala
index 4ba2c6b..8301e92 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCountWindowed.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCountWindowed.scala
@@ -66,7 +66,7 @@
     val slideDuration = s"$slideSize seconds"
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StructuredNetworkWordCountWindowed")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredSessionization.scala b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredSessionization.scala
index 5d99738..14af172 100644
--- a/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredSessionization.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredSessionization.scala
@@ -47,7 +47,7 @@
     val port = args(1).toInt
 
     val spark = SparkSession
-      .builder
+      .builder()
       .appName("StructuredSessionization")
       .getOrCreate()
 
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
index 626f4b4..c88a907 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/CustomReceiver.scala
@@ -87,7 +87,7 @@
      val reader = new BufferedReader(
        new InputStreamReader(socket.getInputStream(), StandardCharsets.UTF_8))
      userInput = reader.readLine()
-     while(!isStopped && userInput != null) {
+     while(!isStopped() && userInput != null) {
        store(userInput)
        userInput = reader.readLine()
      }
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
index 7daa001..64da35f 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/SqlNetworkWordCount.scala
@@ -94,7 +94,7 @@
   def getInstance(sparkConf: SparkConf): SparkSession = {
     if (instance == null) {
       instance = SparkSession
-        .builder
+        .builder()
         .config(sparkConf)
         .getOrCreate()
     }
diff --git a/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala
index 8a5fcda..05f111b 100644
--- a/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala
@@ -60,7 +60,7 @@
     // Update the cumulative count using mapWithState
     // This will give a DStream made of state (which is the cumulative count of the words)
     val mappingFunc = (word: String, one: Option[Int], state: State[Int]) => {
-      val sum = one.getOrElse(0) + state.getOption.getOrElse(0)
+      val sum = one.getOrElse(0) + state.getOption().getOrElse(0)
       val output = (word, sum)
       state.update(sum)
       output
diff --git a/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala b/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala
index a07c2e1..ab40fcf 100644
--- a/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala
+++ b/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala
@@ -277,7 +277,7 @@
         if (Random.nextDouble() < probability) { Some(vidVvals._1) }
         else { None }
       }
-      if (selectedVertices.count > 0) {
+      if (selectedVertices.count() > 0) {
         found = true
         val collectedVertices = selectedVertices.collect()
         retVal = collectedVertices(Random.nextInt(collectedVertices.length))
diff --git a/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala b/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala
index 4a79087..21fb284 100644
--- a/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala
+++ b/graphx/src/main/scala/org/apache/spark/graphx/impl/GraphImpl.scala
@@ -321,7 +321,7 @@
 
     // Convert the vertex partitions in edges to the correct type
     val newEdges = edges.asInstanceOf[EdgeRDDImpl[ED, _]]
-      .mapEdgePartitions((pid, part) => part.withoutVertexAttributes[VD])
+      .mapEdgePartitions((pid, part) => part.withoutVertexAttributes[VD]())
       .cache()
 
     GraphImpl.fromExistingRDDs(vertices, newEdges)
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/EdgeRDDSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/EdgeRDDSuite.scala
index 8fd3e6f..bc23714 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/EdgeRDDSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/EdgeRDDSuite.scala
@@ -63,11 +63,11 @@
   test("count") {
     withSpark { sc =>
       val empty = EdgeRDD.fromEdges(sc.emptyRDD[Edge[Int]])
-      assert(empty.count === 0)
+      assert(empty.count() === 0)
 
       val edges = List(Edge(0, 1, ()), Edge(1, 2, ()), Edge(2, 0, ()))
       val nonempty = EdgeRDD.fromEdges(sc.parallelize(edges))
-      assert(nonempty.count === edges.size)
+      assert(nonempty.count() === edges.size)
     }
   }
 }
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/GraphLoaderSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/GraphLoaderSuite.scala
index e55b05f..60c5621 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/GraphLoaderSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/GraphLoaderSuite.scala
@@ -39,7 +39,7 @@
         val neighborAttrSums = graph.aggregateMessages[Int](
           ctx => ctx.sendToDst(ctx.srcAttr),
           _ + _)
-        assert(neighborAttrSums.collect.toSet === Set((0: VertexId, 100)))
+        assert(neighborAttrSums.collect().toSet === Set((0: VertexId, 100)))
       } finally {
         Utils.deleteRecursively(tmpDir)
       }
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/GraphOpsSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/GraphOpsSuite.scala
index 3298171..3d4dde9 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/GraphOpsSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/GraphOpsSuite.scala
@@ -41,10 +41,10 @@
     withSpark { sc =>
       val graph = getCycleGraph(sc, 100)
       val nbrs = graph.collectNeighborIds(EdgeDirection.Either).cache()
-      assert(nbrs.count === 100)
-      assert(graph.numVertices === nbrs.count)
-      nbrs.collect.foreach { case (vid, nbrs) => assert(nbrs.size === 2) }
-      nbrs.collect.foreach {
+      assert(nbrs.count() === 100)
+      assert(graph.numVertices === nbrs.count())
+      nbrs.collect().foreach { case (vid, nbrs) => assert(nbrs.size === 2) }
+      nbrs.collect().foreach {
         case (vid, nbrs) =>
           val s = nbrs.toSet
           assert(s.contains((vid + 1) % 100))
@@ -62,7 +62,7 @@
       val correctEdges = edgeArray.filter { case (a, b) => a != b }.toSet
       val graph = Graph.fromEdgeTuples(sc.parallelize(edgeArray), 1)
       val canonicalizedEdges = graph.removeSelfEdges().edges.map(e => (e.srcId, e.dstId))
-        .collect
+        .collect()
       assert(canonicalizedEdges.toSet.size === canonicalizedEdges.size)
       assert(canonicalizedEdges.toSet === correctEdges)
     }
@@ -110,9 +110,9 @@
     withSpark { sc =>
       val graph = getCycleGraph(sc, 100)
       val edges = graph.collectEdges(EdgeDirection.Out).cache()
-      assert(edges.count == 100)
-      edges.collect.foreach { case (vid, edges) => assert(edges.size == 1) }
-      edges.collect.foreach {
+      assert(edges.count() == 100)
+      edges.collect().foreach { case (vid, edges) => assert(edges.size == 1) }
+      edges.collect().foreach {
         case (vid, edges) =>
           val s = edges.toSet
           val edgeDstIds = s.map(e => e.dstId)
@@ -125,9 +125,9 @@
     withSpark { sc =>
       val graph = getCycleGraph(sc, 100)
       val edges = graph.collectEdges(EdgeDirection.In).cache()
-      assert(edges.count == 100)
-      edges.collect.foreach { case (vid, edges) => assert(edges.size == 1) }
-      edges.collect.foreach {
+      assert(edges.count() == 100)
+      edges.collect().foreach { case (vid, edges) => assert(edges.size == 1) }
+      edges.collect().foreach {
         case (vid, edges) =>
           val s = edges.toSet
           val edgeSrcIds = s.map(e => e.srcId)
@@ -140,9 +140,9 @@
     withSpark { sc =>
       val graph = getCycleGraph(sc, 100)
       val edges = graph.collectEdges(EdgeDirection.Either).cache()
-      assert(edges.count == 100)
-      edges.collect.foreach { case (vid, edges) => assert(edges.size == 2) }
-      edges.collect.foreach {
+      assert(edges.count() == 100)
+      edges.collect().foreach { case (vid, edges) => assert(edges.size == 2) }
+      edges.collect().foreach {
         case (vid, edges) =>
           val s = edges.toSet
           val edgeIds = s.map(e => if (vid != e.srcId) e.srcId else e.dstId)
@@ -156,9 +156,9 @@
     withSpark { sc =>
       val graph = getChainGraph(sc, 50)
       val edges = graph.collectEdges(EdgeDirection.Out).cache()
-      assert(edges.count == 49)
-      edges.collect.foreach { case (vid, edges) => assert(edges.size == 1) }
-      edges.collect.foreach {
+      assert(edges.count() == 49)
+      edges.collect().foreach { case (vid, edges) => assert(edges.size == 1) }
+      edges.collect().foreach {
         case (vid, edges) =>
           val s = edges.toSet
           val edgeDstIds = s.map(e => e.dstId)
@@ -173,9 +173,9 @@
       val edges = graph.collectEdges(EdgeDirection.In).cache()
       // We expect only 49 because collectEdges does not return vertices that do
       // not have any edges in the specified direction.
-      assert(edges.count == 49)
-      edges.collect.foreach { case (vid, edges) => assert(edges.size == 1) }
-      edges.collect.foreach {
+      assert(edges.count() == 49)
+      edges.collect().foreach { case (vid, edges) => assert(edges.size == 1) }
+      edges.collect().foreach {
         case (vid, edges) =>
           val s = edges.toSet
           val edgeDstIds = s.map(e => e.srcId)
@@ -190,15 +190,15 @@
       val edges = graph.collectEdges(EdgeDirection.Either).cache()
       // We expect only 49 because collectEdges does not return vertices that do
       // not have any edges in the specified direction.
-      assert(edges.count === 50)
-      edges.collect.foreach {
+      assert(edges.count() === 50)
+      edges.collect().foreach {
         case (vid, edges) => if (vid > 0 && vid < 49) {
           assert(edges.size == 2)
         } else {
           assert(edges.size == 1)
         }
       }
-      edges.collect.foreach {
+      edges.collect().foreach {
         case (vid, edges) =>
           val s = edges.toSet
           val edgeIds = s.map(e => if (vid != e.srcId) e.srcId else e.dstId)
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala
index 459cddb..a0f2c32 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/GraphSuite.scala
@@ -94,18 +94,18 @@
 
       // The two edges start out in different partitions
       for (edges <- List(identicalEdges, canonicalEdges, sameSrcEdges)) {
-        assert(nonemptyParts(mkGraph(edges)).count === 2)
+        assert(nonemptyParts(mkGraph(edges)).count() === 2)
       }
       // partitionBy(RandomVertexCut) puts identical edges in the same partition
-      assert(nonemptyParts(mkGraph(identicalEdges).partitionBy(RandomVertexCut)).count === 1)
+      assert(nonemptyParts(mkGraph(identicalEdges).partitionBy(RandomVertexCut)).count() === 1)
       // partitionBy(EdgePartition1D) puts same-source edges in the same partition
-      assert(nonemptyParts(mkGraph(sameSrcEdges).partitionBy(EdgePartition1D)).count === 1)
+      assert(nonemptyParts(mkGraph(sameSrcEdges).partitionBy(EdgePartition1D)).count() === 1)
       // partitionBy(CanonicalRandomVertexCut) puts edges that are identical modulo direction into
       // the same partition
       assert(
-        nonemptyParts(mkGraph(canonicalEdges).partitionBy(CanonicalRandomVertexCut)).count === 1)
+        nonemptyParts(mkGraph(canonicalEdges).partitionBy(CanonicalRandomVertexCut)).count() === 1)
       // partitionBy(EdgePartition2D) puts identical edges in the same partition
-      assert(nonemptyParts(mkGraph(identicalEdges).partitionBy(EdgePartition2D)).count === 1)
+      assert(nonemptyParts(mkGraph(identicalEdges).partitionBy(EdgePartition2D)).count() === 1)
 
       // partitionBy(EdgePartition2D) ensures that vertices need only be replicated to 2 * sqrt(p)
       // partitions
@@ -122,7 +122,7 @@
       val partitionSets = partitionedGraph.edges.partitionsRDD.mapPartitions { iter =>
         val part = iter.next()._2
         Iterator((part.iterator.flatMap(e => Iterator(e.srcId, e.dstId))).toSet)
-      }.collect
+      }.collect()
       if (!verts.forall(id => partitionSets.count(_.contains(id)) <= bound)) {
         val numFailures = verts.count(id => partitionSets.count(_.contains(id)) > bound)
         val failure = verts.maxBy(id => partitionSets.count(_.contains(id)))
@@ -134,7 +134,7 @@
       val partitionSetsUnpartitioned = graph.edges.partitionsRDD.mapPartitions { iter =>
         val part = iter.next()._2
         Iterator((part.iterator.flatMap(e => Iterator(e.srcId, e.dstId))).toSet)
-      }.collect
+      }.collect()
       assert(verts.exists(id => partitionSetsUnpartitioned.count(_.contains(id)) > bound))
 
       // Forming triplets view
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/PregelSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/PregelSuite.scala
index 90a9ac6..c8e50e5 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/PregelSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/PregelSuite.scala
@@ -30,7 +30,7 @@
         (vid, attr, msg) => attr,
         et => Iterator.empty,
         (a: Int, b: Int) => throw new Exception("mergeMsg run unexpectedly"))
-      assert(result.vertices.collect.toSet === star.vertices.collect.toSet)
+      assert(result.vertices.collect().toSet === star.vertices.collect().toSet)
     }
   }
 
@@ -40,16 +40,16 @@
       val chain = Graph.fromEdgeTuples(
         sc.parallelize((1 until n).map(x => (x: VertexId, x + 1: VertexId)), 3),
         0).cache()
-      assert(chain.vertices.collect.toSet === (1 to n).map(x => (x: VertexId, 0)).toSet)
+      assert(chain.vertices.collect().toSet === (1 to n).map(x => (x: VertexId, 0)).toSet)
       val chainWithSeed = chain.mapVertices { (vid, attr) => if (vid == 1) 1 else 0 }.cache()
-      assert(chainWithSeed.vertices.collect.toSet ===
+      assert(chainWithSeed.vertices.collect().toSet ===
         Set((1: VertexId, 1)) ++ (2 to n).map(x => (x: VertexId, 0)).toSet)
       val result = Pregel(chainWithSeed, 0)(
         (vid, attr, msg) => math.max(msg, attr),
         et => if (et.dstAttr != et.srcAttr) Iterator((et.dstId, et.srcAttr)) else Iterator.empty,
         (a: Int, b: Int) => math.max(a, b))
-      assert(result.vertices.collect.toSet ===
-        chain.vertices.mapValues { (vid, attr) => attr + 1 }.collect.toSet)
+      assert(result.vertices.collect().toSet ===
+        chain.vertices.mapValues { (vid, attr) => attr + 1 }.collect().toSet)
     }
   }
 }
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala
index 434e6a8..0a5dcf8 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/VertexRDDSuite.scala
@@ -33,7 +33,7 @@
       val n = 100
       val verts = vertices(sc, n)
       val evens = verts.filter(q => ((q._2 % 2) == 0))
-      assert(evens.count === (0 to n).count(_ % 2 == 0))
+      assert(evens.count() === (0 to n).count(_ % 2 == 0))
     }
   }
 
@@ -42,7 +42,7 @@
       val n = 100
       val verts = vertices(sc, n)
       val negatives = verts.mapValues(x => -x).cache() // Allow joining b with a derived RDD of b
-      assert(negatives.count === n + 1)
+      assert(negatives.count() === n + 1)
     }
   }
 
@@ -227,11 +227,11 @@
   test("count") {
     withSpark { sc =>
       val empty = VertexRDD(sc.emptyRDD[(Long, Unit)])
-      assert(empty.count === 0)
+      assert(empty.count() === 0)
 
       val n = 100
       val nonempty = vertices(sc, n)
-      assert(nonempty.count === n + 1)
+      assert(nonempty.count() === n + 1)
     }
   }
 }
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/LabelPropagationSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/LabelPropagationSuite.scala
index 808877f..95f85d9 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/lib/LabelPropagationSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/LabelPropagationSuite.scala
@@ -33,9 +33,9 @@
       val labels = LabelPropagation.run(graph, n * 4).cache()
 
       // All vertices within a clique should have the same label
-      val clique1Labels = labels.vertices.filter(_._1 < n).map(_._2).collect.toArray
+      val clique1Labels = labels.vertices.filter(_._1 < n).map(_._2).collect().toArray
       assert(clique1Labels.forall(_ == clique1Labels(0)))
-      val clique2Labels = labels.vertices.filter(_._1 >= n).map(_._2).collect.toArray
+      val clique2Labels = labels.vertices.filter(_._1 >= n).map(_._2).collect().toArray
       assert(clique2Labels.forall(_ == clique2Labels(0)))
       // The two cliques should have different labels
       assert(clique1Labels(0) != clique2Labels(0))
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/SVDPlusPlusSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/SVDPlusPlusSuite.scala
index da0457c..da139ce 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/lib/SVDPlusPlusSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/SVDPlusPlusSuite.scala
@@ -45,8 +45,8 @@
       val edges = sc.emptyRDD[Edge[Double]]
       val conf = new SVDPlusPlus.Conf(10, 2, 0.0, 5.0, 0.007, 0.007, 0.005, 0.015) // 2 iterations
       val (graph, _) = SVDPlusPlus.run(edges, conf)
-      assert(graph.vertices.count == 0)
-      assert(graph.edges.count == 0)
+      assert(graph.vertices.count() == 0)
+      assert(graph.edges.count() == 0)
     }
   }
 }
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/ShortestPathsSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/ShortestPathsSuite.scala
index f909b70..527187d 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/lib/ShortestPathsSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/ShortestPathsSuite.scala
@@ -33,7 +33,7 @@
       val edges = sc.parallelize(edgeSeq).map { case (v1, v2) => (v1.toLong, v2.toLong) }
       val graph = Graph.fromEdgeTuples(edges, 1)
       val landmarks = Seq(1, 4).map(_.toLong)
-      val results = ShortestPaths.run(graph, landmarks).vertices.collect.map {
+      val results = ShortestPaths.run(graph, landmarks).vertices.collect().map {
         case (v, spMap) => (v, spMap.mapValues(i => i).toMap)
       }
       assert(results.toSet === shortestPaths)
diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/TriangleCountSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/TriangleCountSuite.scala
index abbd89b..2454e9b 100644
--- a/graphx/src/test/scala/org/apache/spark/graphx/lib/TriangleCountSuite.scala
+++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/TriangleCountSuite.scala
@@ -30,7 +30,7 @@
       val graph = Graph.fromEdgeTuples(rawEdges, true).cache()
       val triangleCount = graph.triangleCount()
       val verts = triangleCount.vertices
-      verts.collect.foreach { case (vid, count) => assert(count === 1) }
+      verts.collect().foreach { case (vid, count) => assert(count === 1) }
     }
   }
 
@@ -80,7 +80,7 @@
       val graph = Graph.fromEdgeTuples(rawEdges, true, uniqueEdges = Some(RandomVertexCut)).cache()
       val triangleCount = graph.triangleCount()
       val verts = triangleCount.vertices
-      verts.collect.foreach { case (vid, count) => assert(count === 1) }
+      verts.collect().foreach { case (vid, count) => assert(count === 1) }
     }
   }
 
diff --git a/hadoop-cloud/src/test/scala/org/apache/spark/internal/io/cloud/CommitterBindingSuite.scala b/hadoop-cloud/src/test/scala/org/apache/spark/internal/io/cloud/CommitterBindingSuite.scala
index 984c7db..2a2d25a 100644
--- a/hadoop-cloud/src/test/scala/org/apache/spark/internal/io/cloud/CommitterBindingSuite.scala
+++ b/hadoop-cloud/src/test/scala/org/apache/spark/internal/io/cloud/CommitterBindingSuite.scala
@@ -62,7 +62,7 @@
     StubPathOutputCommitterBinding.bindWithDynamicPartitioning(conf, "http")
     val tContext: TaskAttemptContext = new TaskAttemptContextImpl(conf, taskAttemptId0)
     val parquet = new BindingParquetOutputCommitter(path, tContext)
-    val inner = parquet.boundCommitter.asInstanceOf[StubPathOutputCommitterWithDynamicPartioning]
+    val inner = parquet.boundCommitter().asInstanceOf[StubPathOutputCommitterWithDynamicPartioning]
     parquet.setupJob(tContext)
     assert(inner.jobSetup, s"$inner job not setup")
     parquet.setupTask(tContext)
diff --git a/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala b/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
index 827ca3f..016a836 100644
--- a/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
+++ b/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
@@ -806,7 +806,7 @@
         s += 1
       }
     }
-    new SparseVector(ns, indexBuff.result, valueBuff.result)
+    new SparseVector(ns, indexBuff.result(), valueBuff.result())
   }
 
   private[spark] override def iterator: Iterator[(Int, Double)] = {
diff --git a/mllib-local/src/test/scala/org/apache/spark/ml/linalg/BLASBenchmark.scala b/mllib-local/src/test/scala/org/apache/spark/ml/linalg/BLASBenchmark.scala
index 6d98f60..81c43f7 100644
--- a/mllib-local/src/test/scala/org/apache/spark/ml/linalg/BLASBenchmark.scala
+++ b/mllib-local/src/test/scala/org/apache/spark/ml/linalg/BLASBenchmark.scala
@@ -56,7 +56,7 @@
     val iters = 1e2.toInt
     val rnd = new scala.util.Random(0)
 
-    val f2jBLAS = getF2jBLAS.getOrElse(throw new RuntimeException("can't load F2jBLAS"))
+    val f2jBLAS = getF2jBLAS().getOrElse(throw new RuntimeException("can't load F2jBLAS"))
     val javaBLAS = BLAS.javaBLAS
     val nativeBLAS = BLAS.nativeBLAS
 
@@ -91,9 +91,9 @@
 
     runBenchmark("daxpy") {
       val n = 1e8.toInt
-      val alpha = rnd.nextDouble
-      val x = Array.fill(n) { rnd.nextDouble }
-      val y = Array.fill(n) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val x = Array.fill(n) { rnd.nextDouble() }
+      val y = Array.fill(n) { rnd.nextDouble() }
 
       runBLASBenchmark("daxpy", n) { impl =>
         impl.daxpy(n, alpha, x, 1, y.clone, 1)
@@ -102,9 +102,9 @@
 
     runBenchmark("saxpy") {
       val n = 1e8.toInt
-      val alpha = rnd.nextFloat
-      val x = Array.fill(n) { rnd.nextFloat }
-      val y = Array.fill(n) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val x = Array.fill(n) { rnd.nextFloat() }
+      val y = Array.fill(n) { rnd.nextFloat() }
 
       runBLASBenchmark("saxpy", n) { impl =>
         impl.saxpy(n, alpha, x, 1, y.clone, 1)
@@ -113,7 +113,7 @@
 
     runBenchmark("dcopy") {
       val n = 1e8.toInt
-      val x = Array.fill(n) { rnd.nextDouble }
+      val x = Array.fill(n) { rnd.nextDouble() }
       val y = Array.fill(n) { 0.0 }
 
       runBLASBenchmark("dcopy", n) { impl =>
@@ -123,7 +123,7 @@
 
     runBenchmark("scopy") {
       val n = 1e8.toInt
-      val x = Array.fill(n) { rnd.nextFloat }
+      val x = Array.fill(n) { rnd.nextFloat() }
       val y = Array.fill(n) { 0.0f }
 
       runBLASBenchmark("scopy", n) { impl =>
@@ -133,8 +133,8 @@
 
     runBenchmark("ddot") {
       val n = 1e8.toInt
-      val x = Array.fill(n) { rnd.nextDouble }
-      val y = Array.fill(n) { rnd.nextDouble }
+      val x = Array.fill(n) { rnd.nextDouble() }
+      val y = Array.fill(n) { rnd.nextDouble() }
 
       runBLASBenchmark("ddot", n) { impl =>
         impl.ddot(n, x, 1, y, 1)
@@ -143,8 +143,8 @@
 
     runBenchmark("sdot") {
       val n = 1e8.toInt
-      val x = Array.fill(n) { rnd.nextFloat }
-      val y = Array.fill(n) { rnd.nextFloat }
+      val x = Array.fill(n) { rnd.nextFloat() }
+      val y = Array.fill(n) { rnd.nextFloat() }
 
       runBLASBenchmark("sdot", n) { impl =>
         impl.sdot(n, x, 1, y, 1)
@@ -153,7 +153,7 @@
 
     runBenchmark("dnrm2") {
       val n = 1e8.toInt
-      val x = Array.fill(n) { rnd.nextDouble }
+      val x = Array.fill(n) { rnd.nextDouble() }
 
       runBLASBenchmark("dnrm2", n) { impl =>
         impl.dnrm2(n, x, 1)
@@ -162,7 +162,7 @@
 
     runBenchmark("snrm2") {
       val n = 1e8.toInt
-      val x = Array.fill(n) { rnd.nextFloat }
+      val x = Array.fill(n) { rnd.nextFloat() }
 
       runBLASBenchmark("snrm2", n) { impl =>
         impl.snrm2(n, x, 1)
@@ -171,8 +171,8 @@
 
     runBenchmark("dscal") {
       val n = 1e8.toInt
-      val alpha = rnd.nextDouble
-      val x = Array.fill(n) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val x = Array.fill(n) { rnd.nextDouble() }
 
       runBLASBenchmark("dscal", n) { impl =>
         impl.dscal(n, alpha, x.clone, 1)
@@ -181,8 +181,8 @@
 
     runBenchmark("sscal") {
       val n = 1e8.toInt
-      val alpha = rnd.nextFloat
-      val x = Array.fill(n) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val x = Array.fill(n) { rnd.nextFloat() }
 
       runBLASBenchmark("sscal", n) { impl =>
         impl.sscal(n, alpha, x.clone, 1)
@@ -192,12 +192,12 @@
     runBenchmark("dgemv[N]") {
       val m = 1e4.toInt
       val n = 1e4.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(m * n) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(m * n) { rnd.nextDouble() }
       val lda = m
-      val x = Array.fill(n) { rnd.nextDouble }
-      val beta = rnd.nextDouble
-      val y = Array.fill(m) { rnd.nextDouble }
+      val x = Array.fill(n) { rnd.nextDouble() }
+      val beta = rnd.nextDouble()
+      val y = Array.fill(m) { rnd.nextDouble() }
 
       runBLASBenchmark("dgemv[N]", m * n) { impl =>
         impl.dgemv("N", m, n, alpha, a, lda, x, 1, beta, y.clone, 1)
@@ -207,12 +207,12 @@
     runBenchmark("dgemv[T]") {
       val m = 1e4.toInt
       val n = 1e4.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(m * n) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(m * n) { rnd.nextDouble() }
       val lda = m
-      val x = Array.fill(m) { rnd.nextDouble }
-      val beta = rnd.nextDouble
-      val y = Array.fill(n) { rnd.nextDouble }
+      val x = Array.fill(m) { rnd.nextDouble() }
+      val beta = rnd.nextDouble()
+      val y = Array.fill(n) { rnd.nextDouble() }
 
       runBLASBenchmark("dgemv[T]", m * n) { impl =>
         impl.dgemv("T", m, n, alpha, a, lda, x, 1, beta, y.clone, 1)
@@ -222,12 +222,12 @@
     runBenchmark("sgemv[N]") {
       val m = 1e4.toInt
       val n = 1e4.toInt
-      val alpha = rnd.nextFloat
-      val a = Array.fill(m * n) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val a = Array.fill(m * n) { rnd.nextFloat() }
       val lda = m
-      val x = Array.fill(n) { rnd.nextFloat }
-      val beta = rnd.nextFloat
-      val y = Array.fill(m) { rnd.nextFloat }
+      val x = Array.fill(n) { rnd.nextFloat() }
+      val beta = rnd.nextFloat()
+      val y = Array.fill(m) { rnd.nextFloat() }
 
       runBLASBenchmark("sgemv[N]", m * n) { impl =>
         impl.sgemv("N", m, n, alpha, a, lda, x, 1, beta, y.clone, 1)
@@ -237,12 +237,12 @@
     runBenchmark("sgemv[T]") {
       val m = 1e4.toInt
       val n = 1e4.toInt
-      val alpha = rnd.nextFloat
-      val a = Array.fill(m * n) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val a = Array.fill(m * n) { rnd.nextFloat() }
       val lda = m
-      val x = Array.fill(m) { rnd.nextFloat }
-      val beta = rnd.nextFloat
-      val y = Array.fill(n) { rnd.nextFloat }
+      val x = Array.fill(m) { rnd.nextFloat() }
+      val beta = rnd.nextFloat()
+      val y = Array.fill(n) { rnd.nextFloat() }
 
       runBLASBenchmark("sgemv[T]", m * n) { impl =>
         impl.sgemv("T", m, n, alpha, a, lda, x, 1, beta, y.clone, 1)
@@ -252,12 +252,12 @@
     runBenchmark("dger") {
       val m = 1e4.toInt
       val n = 1e4.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(m * n) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(m * n) { rnd.nextDouble() }
       val lda = m
-      val x = Array.fill(n) { rnd.nextDouble }
-      val beta = rnd.nextDouble
-      val y = Array.fill(m) { rnd.nextDouble }
+      val x = Array.fill(n) { rnd.nextDouble() }
+      val beta = rnd.nextDouble()
+      val y = Array.fill(m) { rnd.nextDouble() }
 
       runBLASBenchmark("dger", m * n) { impl =>
         impl.dger(m, n, alpha, x, 1, y, 1, a.clone(), m)
@@ -266,11 +266,11 @@
 
     runBenchmark("dspmv[U]") {
       val n = 1e4.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(n * (n + 1) / 2) { rnd.nextDouble }
-      val x = Array.fill(n) { rnd.nextDouble }
-      val beta = rnd.nextDouble
-      val y = Array.fill(n) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(n * (n + 1) / 2) { rnd.nextDouble() }
+      val x = Array.fill(n) { rnd.nextDouble() }
+      val beta = rnd.nextDouble()
+      val y = Array.fill(n) { rnd.nextDouble() }
 
       runBLASBenchmark("dspmv[U]", n * (n + 1) / 2) { impl =>
         impl.dspmv("U", n, alpha, a, x, 1, beta, y.clone, 1)
@@ -279,9 +279,9 @@
 
     runBenchmark("dspr[U]") {
       val n = 1e4.toInt
-      val alpha = rnd.nextDouble
-      val x = Array.fill(n) { rnd.nextDouble }
-      val a = Array.fill(n * (n + 1) / 2) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val x = Array.fill(n) { rnd.nextDouble() }
+      val a = Array.fill(n * (n + 1) / 2) { rnd.nextDouble() }
 
       runBLASBenchmark("dspr[U]", n * (n + 1) / 2) { impl =>
         impl.dspr("U", n, alpha, x, 1, a.clone)
@@ -290,9 +290,9 @@
 
     runBenchmark("dsyr[U]") {
       val n = 1e4.toInt
-      val alpha = rnd.nextDouble
-      val x = Array.fill(n) { rnd.nextDouble }
-      val a = Array.fill(n * n) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val x = Array.fill(n) { rnd.nextDouble() }
+      val a = Array.fill(n * n) { rnd.nextDouble() }
 
       runBLASBenchmark("dsyr[U]", n * (n + 1) / 2) { impl =>
         impl.dsyr("U", n, alpha, x, 1, a.clone, n)
@@ -303,13 +303,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(m * k) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(m * k) { rnd.nextDouble() }
       val lda = m
-      val b = Array.fill(k * n) { rnd.nextDouble }
+      val b = Array.fill(k * n) { rnd.nextDouble() }
       val ldb = k
-      val beta = rnd.nextDouble
-      val c = Array.fill(m * n) { rnd.nextDouble }
+      val beta = rnd.nextDouble()
+      val c = Array.fill(m * n) { rnd.nextDouble() }
       val ldc = m
 
       runBLASBenchmark("dgemm[N,N]", m * n * k) { impl =>
@@ -321,13 +321,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(m * k) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(m * k) { rnd.nextDouble() }
       val lda = m
-      val b = Array.fill(k * n) { rnd.nextDouble }
+      val b = Array.fill(k * n) { rnd.nextDouble() }
       val ldb = n
-      val beta = rnd.nextDouble
-      val c = Array.fill(m * n) { rnd.nextDouble }
+      val beta = rnd.nextDouble()
+      val c = Array.fill(m * n) { rnd.nextDouble() }
       val ldc = m
 
       runBLASBenchmark("dgemm[N,T]", m * n * k) { impl =>
@@ -339,13 +339,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(m * k) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(m * k) { rnd.nextDouble() }
       val lda = k
-      val b = Array.fill(k * n) { rnd.nextDouble }
+      val b = Array.fill(k * n) { rnd.nextDouble() }
       val ldb = k
-      val beta = rnd.nextDouble
-      val c = Array.fill(m * n) { rnd.nextDouble }
+      val beta = rnd.nextDouble()
+      val c = Array.fill(m * n) { rnd.nextDouble() }
       val ldc = m
 
       runBLASBenchmark("dgemm[T,N]", m * n * k) { impl =>
@@ -357,13 +357,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextDouble
-      val a = Array.fill(m * k) { rnd.nextDouble }
+      val alpha = rnd.nextDouble()
+      val a = Array.fill(m * k) { rnd.nextDouble() }
       val lda = k
-      val b = Array.fill(k * n) { rnd.nextDouble }
+      val b = Array.fill(k * n) { rnd.nextDouble() }
       val ldb = n
-      val beta = rnd.nextDouble
-      val c = Array.fill(m * n) { rnd.nextDouble }
+      val beta = rnd.nextDouble()
+      val c = Array.fill(m * n) { rnd.nextDouble() }
       val ldc = m
 
       runBLASBenchmark("dgemm[T,T]", m * n * k) { impl =>
@@ -375,13 +375,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextFloat
-      val a = Array.fill(m * k) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val a = Array.fill(m * k) { rnd.nextFloat() }
       val lda = m
-      val b = Array.fill(k * n) { rnd.nextFloat }
+      val b = Array.fill(k * n) { rnd.nextFloat() }
       val ldb = k
-      val beta = rnd.nextFloat
-      val c = Array.fill(m * n) { rnd.nextFloat }
+      val beta = rnd.nextFloat()
+      val c = Array.fill(m * n) { rnd.nextFloat() }
       val ldc = m
 
       runBLASBenchmark("sgemm[N,N]", m * n * k) { impl =>
@@ -393,13 +393,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextFloat
-      val a = Array.fill(m * k) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val a = Array.fill(m * k) { rnd.nextFloat() }
       val lda = m
-      val b = Array.fill(k * n) { rnd.nextFloat }
+      val b = Array.fill(k * n) { rnd.nextFloat() }
       val ldb = n
-      val beta = rnd.nextFloat
-      val c = Array.fill(m * n) { rnd.nextFloat }
+      val beta = rnd.nextFloat()
+      val c = Array.fill(m * n) { rnd.nextFloat() }
       val ldc = m
 
       runBLASBenchmark("sgemm[N,T]", m * n * k) { impl =>
@@ -411,13 +411,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextFloat
-      val a = Array.fill(m * k) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val a = Array.fill(m * k) { rnd.nextFloat() }
       val lda = k
-      val b = Array.fill(k * n) { rnd.nextFloat }
+      val b = Array.fill(k * n) { rnd.nextFloat() }
       val ldb = k
-      val beta = rnd.nextFloat
-      val c = Array.fill(m * n) { rnd.nextFloat }
+      val beta = rnd.nextFloat()
+      val c = Array.fill(m * n) { rnd.nextFloat() }
       val ldc = m
 
       runBLASBenchmark("sgemm[T,N]", m * n * k) { impl =>
@@ -429,13 +429,13 @@
       val m = 1e3.toInt
       val n = 1e3.toInt
       val k = 1e3.toInt
-      val alpha = rnd.nextFloat
-      val a = Array.fill(m * k) { rnd.nextFloat }
+      val alpha = rnd.nextFloat()
+      val a = Array.fill(m * k) { rnd.nextFloat() }
       val lda = k
-      val b = Array.fill(k * n) { rnd.nextFloat }
+      val b = Array.fill(k * n) { rnd.nextFloat() }
       val ldb = n
-      val beta = rnd.nextFloat
-      val c = Array.fill(m * n) { rnd.nextFloat }
+      val beta = rnd.nextFloat()
+      val c = Array.fill(m * n) { rnd.nextFloat() }
       val ldc = m
 
       runBLASBenchmark("sgemm[T,T]", m * n * k) { impl =>
diff --git a/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala b/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
index f086697..f991f35 100644
--- a/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
+++ b/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
@@ -234,11 +234,11 @@
       val nnz = random.nextInt(m)
 
       val indices1 = random.shuffle(0 to m - 1).slice(0, nnz).sorted.toArray
-      val values1 = Array.fill(nnz)(random.nextDouble)
+      val values1 = Array.fill(nnz)(random.nextDouble())
       val sparseVector1 = Vectors.sparse(m, indices1, values1)
 
       val indices2 = random.shuffle(0 to m - 1).slice(0, nnz).sorted.toArray
-      val values2 = Array.fill(nnz)(random.nextDouble)
+      val values2 = Array.fill(nnz)(random.nextDouble())
       val sparseVector2 = Vectors.sparse(m, indices2, values2)
 
       val denseVector1 = Vectors.dense(sparseVector1.toArray)
@@ -454,8 +454,8 @@
         valuesBuilder += v
       }
       val (indices, values) = vec.activeIterator.toArray.unzip
-      assert(indicesBuilder.result === indices)
-      assert(valuesBuilder.result === values)
+      assert(indicesBuilder.result() === indices)
+      assert(valuesBuilder.result() === values)
     }
   }
 
@@ -475,8 +475,8 @@
         }
       }
       val (indices, values) = vec.nonZeroIterator.toArray.unzip
-      assert(indicesBuilder.result === indices)
-      assert(valuesBuilder.result === values)
+      assert(indicesBuilder.result() === indices)
+      assert(valuesBuilder.result() === values)
     }
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
index f35c6e0..b342027 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala
@@ -307,7 +307,7 @@
   override def transform(dataset: Dataset[_]): DataFrame = instrumented(instr =>
       instr.withTransformEvent(this, dataset) {
     transformSchema(dataset.schema, logging = true)
-    stages.foldLeft(dataset.toDF)((cur, transformer) =>
+    stages.foldLeft(dataset.toDF())((cur, transformer) =>
       instr.withTransformEvent(transformer, cur)(transformer.transform(cur)))
   })
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/Predictor.scala b/mllib/src/main/scala/org/apache/spark/ml/Predictor.scala
index 9c6eb88..41f3946 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/Predictor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/Predictor.scala
@@ -194,7 +194,7 @@
     } else {
       this.logWarning(s"$uid: Predictor.transform() does nothing" +
         " because no output columns were set.")
-      dataset.toDF
+      dataset.toDF()
     }
   }
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala b/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala
index 91dd6ab..992e91e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/attribute/AttributeGroup.scala
@@ -179,7 +179,7 @@
     sum
   }
 
-  override def toString: String = toMetadata.toString
+  override def toString: String = toMetadata().toString
 }
 
 /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala
index c46be17..e12c68f 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala
@@ -152,7 +152,7 @@
       logWarning(s"$uid: ClassificationModel.transform() does nothing" +
         " because no output columns were set.")
     }
-    outputData.toDF
+    outputData.toDF()
   }
 
   final override def transformImpl(dataset: Dataset[_]): DataFrame =
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala
index 54f3c1e..13898a3 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LinearSVC.scala
@@ -342,7 +342,7 @@
       val adapt = BLAS.javaBLAS.ddot(numFeatures, solution, 1, scaledMean, 1)
       solution(numFeatures) -= adapt
     }
-    (solution, arrayBuilder.result)
+    (solution, arrayBuilder.result())
   }
 }
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index adf77eb..0efa57e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -1036,7 +1036,7 @@
         solution(numFeatures) -= adapt
       }
     }
-    (solution, arrayBuilder.result)
+    (solution, arrayBuilder.result())
   }
 
   @Since("1.4.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
index cf94c9f..52106f4 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
@@ -182,7 +182,7 @@
     if (getPredictionCol.isEmpty && getRawPredictionCol.isEmpty) {
       logWarning(s"$uid: OneVsRestModel.transform() does nothing" +
         " because no output columns were set.")
-      return dataset.toDF
+      return dataset.toDF()
     }
 
     val isProbModel = models.head.isInstanceOf[ProbabilisticClassificationModel[_, _]]
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
index 1caaecc..460f239 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
@@ -157,7 +157,7 @@
       this.logWarning(s"$uid: ProbabilisticClassificationModel.transform() does nothing" +
         " because no output columns were set.")
     }
-    outputData.toDF
+    outputData.toDF()
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
index 0331555..98ab5fa 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
@@ -145,7 +145,7 @@
       this.logWarning(s"$uid: GaussianMixtureModel.transform() does nothing" +
         " because no output columns were set.")
     }
-    outputData.toDF
+    outputData.toDF()
   }
 
   @Since("2.0.0")
@@ -441,7 +441,7 @@
       instances.mapPartitions { iter =>
         if (iter.nonEmpty) {
           val agg = new ExpectationAggregator(numFeatures, bcWeights, bcGaussians)
-          while (iter.hasNext) { agg.add(iter.next) }
+          while (iter.hasNext) { agg.add(iter.next()) }
           // sum of weights in this partition
           val ws = agg.weights.sum
           if (iteration == 0) weightSumAccum.add(ws)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/PowerIterationClustering.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/PowerIterationClustering.scala
index d4c8781..8b2ee95 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/PowerIterationClustering.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/PowerIterationClustering.scala
@@ -178,7 +178,7 @@
       .setMaxIterations($(maxIter))
     val model = algorithm.run(rdd)
 
-    model.assignments.toDF
+    model.assignments.toDF()
   }
 
   @Since("2.4.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala
index 143e26f..85242e4 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/ClusteringEvaluator.scala
@@ -106,7 +106,7 @@
     val metrics = getMetrics(dataset)
 
     $(metricName) match {
-      case ("silhouette") => metrics.silhouette
+      case ("silhouette") => metrics.silhouette()
       case (other) =>
         throw new IllegalArgumentException(s"No support for metric $other")
     }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala
index 16d7111..e073e41 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSH.scala
@@ -179,7 +179,7 @@
     inputDim: Int): BucketedRandomProjectionLSHModel = {
     val rng = new Random($(seed))
     val localNumHashTables = $(numHashTables)
-    val values = Array.fill(localNumHashTables * inputDim)(rng.nextGaussian)
+    val values = Array.fill(localNumHashTables * inputDim)(rng.nextGaussian())
     var i = 0
     while (i < localNumHashTables) {
       val offset = i * inputDim
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala
index ca03409..74be13a 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala
@@ -194,7 +194,7 @@
       if (dataset.storageLevel == StorageLevel.NONE) {
         input.persist(StorageLevel.MEMORY_AND_DISK)
       }
-      Some(input.count)
+      Some(input.count())
     } else {
       None
     }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala
index 5254762..2515365 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala
@@ -142,13 +142,13 @@
           var s = new QuantileSummaries(
             QuantileSummaries.defaultCompressThreshold, relativeError)
           while (iter.hasNext) {
-            val row = iter.next
+            val row = iter.next()
             if (!row.isNullAt(0)) {
               val v = row.getDouble(0)
               if (!v.isNaN) s = s.insert(v)
             }
           }
-          Iterator.single(s.compress)
+          Iterator.single(s.compress())
         } else Iterator.empty
       }.treeReduce((s1, s2) => s1.merge(s2))
       val count = summary.count
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala
index d189edc..cdedcc2 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/MinHashLSH.scala
@@ -79,8 +79,8 @@
       return 1.0
     }
 
-    var xIndex = xIter.next
-    var yIndex = yIter.next
+    var xIndex = xIter.next()
+    var yIndex = yIter.next()
     var xSize = 1
     var ySize = 1
     var intersectionSize = 0
@@ -88,12 +88,12 @@
     while (xIndex != -1 && yIndex != -1) {
       if (xIndex == yIndex) {
         intersectionSize += 1
-        xIndex = if (xIter.hasNext) { xSize += 1; xIter.next } else -1
-        yIndex = if (yIter.hasNext) { ySize += 1; yIter.next } else -1
+        xIndex = if (xIter.hasNext) { xSize += 1; xIter.next() } else -1
+        yIndex = if (yIter.hasNext) { ySize += 1; yIter.next() } else -1
       } else if (xIndex > yIndex) {
-        yIndex = if (yIter.hasNext) { ySize += 1; yIter.next } else -1
+        yIndex = if (yIter.hasNext) { ySize += 1; yIter.next() } else -1
       } else {
-        xIndex = if (xIter.hasNext) { xSize += 1; xIter.next } else -1
+        xIndex = if (xIter.hasNext) { xSize += 1; xIter.next() } else -1
       }
     }
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
index 08fe750..9387ab3 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
@@ -386,7 +386,7 @@
   private def transformLabel(dataset: Dataset[_]): DataFrame = {
     val labelName = resolvedFormula.label
     if (labelName.isEmpty || hasLabelCol(dataset.schema)) {
-      dataset.toDF
+      dataset.toDF()
     } else if (dataset.schema.exists(_.name == labelName)) {
       dataset.schema(labelName).dataType match {
         case _: NumericType | BooleanType =>
@@ -397,7 +397,7 @@
     } else {
       // Ignore the label field. This is a hack so that this transformer can also work on test
       // datasets in a Pipeline.
-      dataset.toDF
+      dataset.toDF()
     }
   }
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala
index 85352d6..df6e54c 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/RobustScaler.scala
@@ -190,10 +190,10 @@
           val summaries = Array.fill(numFeatures)(
             new QuantileSummaries(QuantileSummaries.defaultCompressThreshold, relativeError))
           while (iter.hasNext) {
-            val vec = iter.next
+            val vec = iter.next()
             vec.foreach { (i, v) => if (!v.isNaN) summaries(i) = summaries(i).insert(v) }
           }
-          Iterator.tabulate(numFeatures)(i => (i, summaries(i).compress))
+          Iterator.tabulate(numFeatures)(i => (i, summaries(i).compress()))
         } else Iterator.empty
       }.reduceByKey { (s1, s2) => s1.merge(s2) }
     } else {
@@ -206,9 +206,9 @@
       }.aggregateByKey(
         new QuantileSummaries(QuantileSummaries.defaultCompressThreshold, relativeError))(
         seqOp = (s, v) => s.insert(v),
-        combOp = (s1, s2) => s1.compress.merge(s2.compress)
+        combOp = (s1, s2) => s1.compress().merge(s2.compress())
       ).map { case ((_, i), s) => (i, s)
-      }.reduceByKey { (s1, s2) => s1.compress.merge(s2.compress) }
+      }.reduceByKey { (s1, s2) => s1.compress().merge(s2.compress()) }
     }
   }
 
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Selector.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Selector.scala
index 1afab32..8ff880b 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Selector.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Selector.scala
@@ -207,7 +207,7 @@
     import spark.implicits._
 
     val numFeatures = DatasetUtils.getNumFeatures(dataset, $(featuresCol))
-    val resultDF = getSelectionTestResult(dataset.toDF)
+    val resultDF = getSelectionTestResult(dataset.toDF())
 
     def getTopIndices(k: Int): Array[Int] = {
       resultDF.sort("pValue", "featureIndex")
@@ -233,7 +233,7 @@
         val maxIndex = resultDF.sort("pValue", "featureIndex")
           .select("pValue")
           .as[Double].rdd
-          .zipWithIndex
+          .zipWithIndex()
           .flatMap { case (pValue, index) =>
             if (pValue <= f * (index + 1)) {
               Iterator.single(index.toInt)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
index 4f11c58..7f8850b 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
@@ -199,7 +199,7 @@
 
     val selectedCols = getSelectedCols(dataset, inputCols)
     dataset.select(selectedCols: _*)
-      .toDF
+      .toDF()
       .agg(aggregator.toColumn)
       .as[Array[OpenHashMap[String, Long]]]
       .collect()(0)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/UnivariateFeatureSelector.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/UnivariateFeatureSelector.scala
index 3b43404..6142447 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/UnivariateFeatureSelector.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/UnivariateFeatureSelector.scala
@@ -179,11 +179,11 @@
 
     val resultDF = ($(featureType), $(labelType)) match {
       case ("categorical", "categorical") =>
-        ChiSquareTest.test(dataset.toDF, getFeaturesCol, getLabelCol, true)
+        ChiSquareTest.test(dataset.toDF(), getFeaturesCol, getLabelCol, true)
       case ("continuous", "categorical") =>
-        ANOVATest.test(dataset.toDF, getFeaturesCol, getLabelCol, true)
+        ANOVATest.test(dataset.toDF(), getFeaturesCol, getLabelCol, true)
       case ("continuous", "continuous") =>
-        FValueTest.test(dataset.toDF, getFeaturesCol, getLabelCol, true)
+        FValueTest.test(dataset.toDF(), getFeaturesCol, getLabelCol, true)
       case _ =>
         throw new IllegalArgumentException(s"Unsupported combination:" +
           s" featureType=${$(featureType)}, labelType=${$(labelType)}")
@@ -227,7 +227,7 @@
         val maxIndex = resultDF.sort("pValue", "featureIndex")
           .select("pValue")
           .as[Double].rdd
-          .zipWithIndex
+          .zipWithIndex()
           .flatMap { case (pValue, index) =>
             if (pValue <= f * (index + 1)) {
               Iterator.single(index.toInt)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala
index fd44b1c..5687ba8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorSlicer.scala
@@ -153,7 +153,7 @@
     }
     val numFeaturesSelected = $(indices).length + $(names).length
     val outputAttr = new AttributeGroup($(outputCol), numFeaturesSelected)
-    SchemaUtils.appendColumn(schema, outputAttr.toStructField)
+    SchemaUtils.appendColumn(schema, outputAttr.toStructField())
   }
 
   @Since("1.5.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
index 3b988fb..e9abcb0 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
@@ -343,7 +343,7 @@
       val adapt = BLAS.getBLAS(numFeatures).ddot(numFeatures, solution, 1, scaledMean, 1)
       solution(numFeatures) -= adapt
     }
-    (solution, arrayBuilder.result)
+    (solution, arrayBuilder.result())
   }
 
   @Since("1.6.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
index 1520220..6e26a78 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
@@ -1077,7 +1077,7 @@
       this.logWarning(s"$uid: GeneralizedLinearRegressionModel.transform() does nothing" +
         " because no output columns were set.")
     }
-    outputData.toDF
+    outputData.toDF()
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
index 7295ce6..9638eee 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
@@ -612,7 +612,7 @@
       val adapt = BLAS.javaBLAS.ddot(numFeatures, solution, 1, scaledMean, 1)
       solution(numFeatures) -= adapt
     }
-    (solution, arrayBuilder.result)
+    (solution, arrayBuilder.result())
   }
 
   private def createModel(
diff --git a/mllib/src/main/scala/org/apache/spark/ml/stat/FValueTest.scala b/mllib/src/main/scala/org/apache/spark/ml/stat/FValueTest.scala
index 800c68d..89579df 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/stat/FValueTest.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/stat/FValueTest.scala
@@ -124,7 +124,7 @@
         if (iter.hasNext) {
           val array = Array.ofDim[Double](numFeatures)
           while (iter.hasNext) {
-            val (label, features) = iter.next
+            val (label, features) = iter.next()
             val yDiff = label - yMean
             if (yDiff != 0) {
               features.iterator.zip(xMeans.iterator)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala
index 19ea7e4..8cf19f2 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala
@@ -317,7 +317,7 @@
     // Prepare periodic checkpointers
     // Note: this is checkpointing the unweighted training error
     val predErrorCheckpointer = new PeriodicRDDCheckpointer[(Double, Double)](
-      treeStrategy.getCheckpointInterval, sc, StorageLevel.MEMORY_AND_DISK)
+      treeStrategy.getCheckpointInterval(), sc, StorageLevel.MEMORY_AND_DISK)
 
     timer.stop("init")
 
@@ -393,7 +393,7 @@
       validatePredError = computeInitialPredictionAndError(
         validationTreePoints, firstTreeWeight, firstTreeModel, loss, bcSplits)
       validatePredErrorCheckpointer = new PeriodicRDDCheckpointer[(Double, Double)](
-        treeStrategy.getCheckpointInterval, sc, StorageLevel.MEMORY_AND_DISK)
+        treeStrategy.getCheckpointInterval(), sc, StorageLevel.MEMORY_AND_DISK)
       validatePredErrorCheckpointer.update(validatePredError)
       bestValidateError = computeWeightedError(validationTreePoints, validatePredError)
       timer.stop("init validation")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala
index de6c935..012e942 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala
@@ -163,7 +163,7 @@
       // At first, all the rows belong to the root nodes (node Id == 1).
       nodeIds = baggedInput.map { _ => Array.fill(numTrees)(1) }
       nodeIdCheckpointer = new PeriodicRDDCheckpointer[Array[Int]](
-        strategy.getCheckpointInterval, sc, StorageLevel.MEMORY_AND_DISK)
+        strategy.getCheckpointInterval(), sc, StorageLevel.MEMORY_AND_DISK)
       nodeIdCheckpointer.update(nodeIds)
     }
 
@@ -232,7 +232,7 @@
         if (strategy.algo == OldAlgo.Classification) {
           topNodes.map { rootNode =>
             new DecisionTreeClassificationModel(uid, rootNode.toNode(prune), numFeatures,
-              strategy.getNumClasses)
+              strategy.getNumClasses())
           }
         } else {
           topNodes.map { rootNode =>
@@ -243,7 +243,7 @@
         if (strategy.algo == OldAlgo.Classification) {
           topNodes.map { rootNode =>
             new DecisionTreeClassificationModel(rootNode.toNode(prune), numFeatures,
-              strategy.getNumClasses)
+              strategy.getNumClasses())
           }
         } else {
           topNodes.map(rootNode =>
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
index 4e9dadd..f186b24 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
@@ -158,10 +158,10 @@
 
     // Compute metrics for each model over each split
     val (splits, schemaWithoutFold) = if ($(foldCol) == "") {
-      (MLUtils.kFold(dataset.toDF.rdd, $(numFolds), $(seed)), schema)
+      (MLUtils.kFold(dataset.toDF().rdd, $(numFolds), $(seed)), schema)
     } else {
       val filteredSchema = StructType(schema.filter(_.name != $(foldCol)).toArray)
-      (MLUtils.kFold(dataset.toDF, $(numFolds), $(foldCol)), filteredSchema)
+      (MLUtils.kFold(dataset.toDF(), $(numFolds), $(foldCol)), filteredSchema)
     }
     val metrics = splits.zipWithIndex.map { case ((training, validation), splitIndex) =>
       val trainingDataset = sparkSession.createDataFrame(training, schemaWithoutFold).cache()
diff --git a/mllib/src/main/scala/org/apache/spark/ml/util/DatasetUtils.scala b/mllib/src/main/scala/org/apache/spark/ml/util/DatasetUtils.scala
index 130790a..08ecdaf 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/util/DatasetUtils.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/util/DatasetUtils.scala
@@ -215,7 +215,7 @@
    */
   private[ml] def getNumFeatures(dataset: Dataset[_], vectorCol: String): Int = {
     MetadataUtils.getNumFeatures(dataset.schema(vectorCol)).getOrElse {
-      dataset.select(columnToVector(dataset, vectorCol)).head.getAs[Vector](0).size
+      dataset.select(columnToVector(dataset, vectorCol)).head().getAs[Vector](0).size
     }
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala b/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala
index c08d7e8..e3f93b3 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/util/SchemaUtils.scala
@@ -120,7 +120,7 @@
       size: Int): StructType = {
     require(size > 0)
     val attrGroup = new AttributeGroup(colName, size)
-    val field = attrGroup.toStructField
+    val field = attrGroup.toStructField()
     updateField(schema, field, true)
   }
 
@@ -138,7 +138,7 @@
     val attr = NominalAttribute.defaultAttr
       .withName(colName)
       .withNumValues(numValues)
-    val field = attr.toStructField
+    val field = attr.toStructField()
     updateField(schema, field, true)
   }
 
@@ -153,7 +153,7 @@
       colName: String): StructType = {
     val attr = NumericAttribute.defaultAttr
       .withName(colName)
-    val field = attr.toStructField
+    val field = attr.toStructField()
     updateField(schema, field, true)
   }
 
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeans.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeans.scala
index 6be32ab..a53581e 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/BisectingKMeans.scala
@@ -157,7 +157,7 @@
       instances: RDD[(Vector, Double)],
       handlePersistence: Boolean,
       instr: Option[Instrumentation]): BisectingKMeansModel = {
-    val d = instances.map(_._1.size).first
+    val d = instances.map(_._1.size).first()
     logInfo(s"Feature dimension: $d.")
 
     val dMeasure = DistanceMeasure.decodeFromString(this.distanceMeasure)
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/DistanceMeasure.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/DistanceMeasure.scala
index e4c29a7..5b0fb5e 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/DistanceMeasure.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/DistanceMeasure.scala
@@ -101,7 +101,7 @@
             } else Iterator.empty
           }
         }
-      }.collect.foreach { case (i, j, s) =>
+      }.collect().foreach { case (i, j, s) =>
         val index = indexUpperTriangular(k, i, j)
         packedValues(index) = s
         if (s < diagValues(i)) diagValues(i) = s
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala
index 32471b0..ea548b2 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala
@@ -39,7 +39,7 @@
    */
   private def toPMML(streamResult: StreamResult): Unit = {
     val pmmlModelExport = PMMLModelExportFactory.createPMMLModelExport(this)
-    JAXBUtil.marshalPMML(pmmlModelExport.getPmml, streamResult)
+    JAXBUtil.marshalPMML(pmmlModelExport.getPmml(), streamResult)
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala
index eb83f9a..94848cb 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/StreamingLinearAlgorithm.scala
@@ -88,7 +88,7 @@
       throw new IllegalArgumentException("Model must be initialized before starting training.")
     }
     data.foreachRDD { (rdd, time) =>
-      if (!rdd.isEmpty) {
+      if (!rdd.isEmpty()) {
         model = Some(algorithm.run(rdd, model.get.weights))
         logInfo(s"Model updated at time ${time.toString}")
         val display = model.get.weights.size match {
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala
index de21db8..f6f5edb 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala
@@ -95,7 +95,7 @@
 
     // optionally add gaussian noise
     if (noise) {
-      trainData.map(x => (x._1, x._2, x._3 + rand.nextGaussian * sigma))
+      trainData.map(x => (x._1, x._2, x._3 + rand.nextGaussian() * sigma))
     }
 
     trainData.map(x => x._1 + "," + x._2 + "," + x._3).saveAsTextFile(outputPath)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/FunctionsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/FunctionsSuite.scala
index 1f10808..d166b4b 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/FunctionsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/FunctionsSuite.scala
@@ -52,7 +52,7 @@
     for ((colName, valType) <- Seq(
         ("vec", "null"), ("oldVec", "null"), ("label", "java.lang.Integer"))) {
       val thrown1 = intercept[SparkException] {
-        df2.select(vector_to_array(col(colName))).count
+        df2.select(vector_to_array(col(colName))).count()
       }
       assert(thrown1.getCause.getMessage.contains(
         "function vector_to_array requires a non-null input argument and input type must be " +
diff --git a/mllib/src/test/scala/org/apache/spark/ml/MLEventsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/MLEventsSuite.scala
index d58c938..e28b260 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/MLEventsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/MLEventsSuite.scala
@@ -88,11 +88,11 @@
     val dataset4 = mock[DataFrame]
     val dataset5 = mock[DataFrame]
 
-    when(dataset1.toDF).thenReturn(dataset1)
-    when(dataset2.toDF).thenReturn(dataset2)
-    when(dataset3.toDF).thenReturn(dataset3)
-    when(dataset4.toDF).thenReturn(dataset4)
-    when(dataset5.toDF).thenReturn(dataset5)
+    when(dataset1.toDF()).thenReturn(dataset1)
+    when(dataset2.toDF()).thenReturn(dataset2)
+    when(dataset3.toDF()).thenReturn(dataset3)
+    when(dataset4.toDF()).thenReturn(dataset4)
+    when(dataset5.toDF()).thenReturn(dataset5)
 
     when(estimator1.fit(meq(dataset1))).thenReturn(model1)
     when(model1.transform(meq(dataset1))).thenReturn(dataset2)
@@ -153,10 +153,10 @@
     val dataset2 = mock[DataFrame]
     val dataset3 = mock[DataFrame]
     val dataset4 = mock[DataFrame]
-    when(dataset1.toDF).thenReturn(dataset1)
-    when(dataset2.toDF).thenReturn(dataset2)
-    when(dataset3.toDF).thenReturn(dataset3)
-    when(dataset4.toDF).thenReturn(dataset4)
+    when(dataset1.toDF()).thenReturn(dataset1)
+    when(dataset2.toDF()).thenReturn(dataset2)
+    when(dataset3.toDF()).thenReturn(dataset3)
+    when(dataset4.toDF()).thenReturn(dataset4)
 
     val transformer1 = mock[Transformer]
     val model = mock[MyModel]
diff --git a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
index e9c08f0..3bf339f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
@@ -53,11 +53,11 @@
     val dataset3 = mock[DataFrame]
     val dataset4 = mock[DataFrame]
 
-    when(dataset0.toDF).thenReturn(dataset0)
-    when(dataset1.toDF).thenReturn(dataset1)
-    when(dataset2.toDF).thenReturn(dataset2)
-    when(dataset3.toDF).thenReturn(dataset3)
-    when(dataset4.toDF).thenReturn(dataset4)
+    when(dataset0.toDF()).thenReturn(dataset0)
+    when(dataset1.toDF()).thenReturn(dataset1)
+    when(dataset2.toDF()).thenReturn(dataset2)
+    when(dataset3.toDF()).thenReturn(dataset3)
+    when(dataset4.toDF()).thenReturn(dataset4)
 
     when(estimator0.copy(any[ParamMap])).thenReturn(estimator0)
     when(model0.copy(any[ParamMap])).thenReturn(model0)
@@ -247,7 +247,7 @@
 
   override def write: MLWriter = new DefaultParamsWriter(this)
 
-  override def transform(dataset: Dataset[_]): DataFrame = dataset.toDF
+  override def transform(dataset: Dataset[_]): DataFrame = dataset.toDF()
 
   override def transformSchema(schema: StructType): StructType = schema
 }
@@ -270,7 +270,7 @@
 
   override def copy(extra: ParamMap): UnWritableStage = defaultCopy(extra)
 
-  override def transform(dataset: Dataset[_]): DataFrame = dataset.toDF
+  override def transform(dataset: Dataset[_]): DataFrame = dataset.toDF()
 
   override def transformSchema(schema: StructType): StructType = schema
 }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
index 8a4fea2..0994465 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
@@ -369,13 +369,13 @@
       .setMaxDepth(2)
       .setMaxIter(3)
       .setLossType("logistic")
-    val model3 = gbt.fit(trainData.toDF)
+    val model3 = gbt.fit(trainData.toDF())
     val model1 = new GBTClassificationModel("gbt-cls-model-test1",
       model3.trees.take(1), model3.treeWeights.take(1), model3.numFeatures, model3.numClasses)
     val model2 = new GBTClassificationModel("gbt-cls-model-test2",
       model3.trees.take(2), model3.treeWeights.take(2), model3.numFeatures, model3.numClasses)
 
-    val evalArr = model3.evaluateEachIteration(validationData.toDF)
+    val evalArr = model3.evaluateEachIteration(validationData.toDF())
     val remappedValidationData = validationData.map {
       case LabeledPoint(label, features) =>
         Instance(label * 2 - 1, 1.0, features)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
index afc57a3..50d8bcb 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
@@ -2587,7 +2587,7 @@
       blorModel.evaluate(smallBinaryDataset).asInstanceOf[BinaryLogisticRegressionSummary]
     assert(blorSummary.areaUnderROC === sameBlorSummary.areaUnderROC)
     assert(blorSummary.roc.collect() === sameBlorSummary.roc.collect())
-    assert(blorSummary.pr.collect === sameBlorSummary.pr.collect())
+    assert(blorSummary.pr.collect() === sameBlorSummary.pr.collect())
     assert(
       blorSummary.fMeasureByThreshold.collect() === sameBlorSummary.fMeasureByThreshold.collect())
     assert(
@@ -3143,7 +3143,7 @@
         for (i <- 0 until nClasses) {
           if (p < probs(i)) {
             y = i
-            break
+            break()
           }
         }
       }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/ClusteringEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/ClusteringEvaluatorSuite.scala
index baeebfb..0077e03 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/ClusteringEvaluatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/ClusteringEvaluatorSuite.scala
@@ -152,13 +152,13 @@
       .setPredictionCol("label")
 
     val metrics1 = evaluator.getMetrics(irisDataset)
-    val silhouetteScoreEuclidean = metrics1.silhouette
+    val silhouetteScoreEuclidean = metrics1.silhouette()
 
     assert(evaluator.evaluate(irisDataset) == silhouetteScoreEuclidean)
 
     evaluator.setDistanceMeasure("cosine")
     val metrics2 = evaluator.getMetrics(irisDataset)
-    val silhouetteScoreCosin = metrics2.silhouette
+    val silhouetteScoreCosin = metrics2.silhouette()
 
     assert(evaluator.evaluate(irisDataset) == silhouetteScoreCosin)
   }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala
index 8f8365a..bac605c 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala
@@ -34,14 +34,14 @@
   import testImplicits._
 
   test("forward transform of discrete cosine matches jTransforms result") {
-    val data = Vectors.dense((0 until 128).map(_ => 2D * math.random - 1D).toArray)
+    val data = Vectors.dense((0 until 128).map(_ => 2D * math.random() - 1D).toArray)
     val inverse = false
 
     testDCT(data, inverse)
   }
 
   test("inverse transform of discrete cosine matches jTransforms result") {
-    val data = Vectors.dense((0 until 128).map(_ => 2D * math.random - 1D).toArray)
+    val data = Vectors.dense((0 until 128).map(_ => 2D * math.random() - 1D).toArray)
     val inverse = true
 
     testDCT(data, inverse)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/QuantileDiscretizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/QuantileDiscretizerSuite.scala
index 682b87a..542eb17 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/QuantileDiscretizerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/QuantileDiscretizerSuite.scala
@@ -72,7 +72,7 @@
     val model = discretizer.fit(df)
     testTransformerByGlobalCheckFunc[(Double)](df, model, "result") { rows =>
       val result = rows.map { r => Tuple1(r.getDouble(0)) }.toDF("result")
-      val observedNumBuckets = result.select("result").distinct.count
+      val observedNumBuckets = result.select("result").distinct().count()
       assert(observedNumBuckets == expectedNumBuckets,
         s"Observed number of buckets are not correct." +
           s" Expected $expectedNumBuckets but found $observedNumBuckets")
@@ -130,8 +130,8 @@
     val model = discretizer.fit(trainDF)
     testTransformerByGlobalCheckFunc[(Double)](testDF, model, "result") { rows =>
       val result = rows.map { r => Tuple1(r.getDouble(0)) }.toDF("result")
-      val firstBucketSize = result.filter(result("result") === 0.0).count
-      val lastBucketSize = result.filter(result("result") === 4.0).count
+      val firstBucketSize = result.filter(result("result") === 0.0).count()
+      val lastBucketSize = result.filter(result("result") === 4.0).count()
 
       assert(firstBucketSize === 30L,
         s"Size of first bucket ${firstBucketSize} did not equal expected value of 30.")
@@ -221,7 +221,7 @@
       val result =
         rows.map { r => Tuple2(r.getDouble(0), r.getDouble(1)) }.toDF("result1", "result2")
       for (i <- 1 to 2) {
-        val observedNumBuckets = result.select("result" + i).distinct.count
+        val observedNumBuckets = result.select("result" + i).distinct().count()
         assert(observedNumBuckets == expectedNumBucket,
           s"Observed number of buckets are not correct." +
             s" Expected $expectedNumBucket but found ($observedNumBuckets")
@@ -508,7 +508,7 @@
     val model = discretizer.fit(df)
     val result = model.transform(df)
 
-    val observedNumBuckets = result.select(discretizer.getOutputCol).distinct.count
+    val observedNumBuckets = result.select(discretizer.getOutputCol).distinct().count()
     assert(observedNumBuckets === numBuckets,
       "Observed number of buckets does not equal expected number of buckets.")
   }
@@ -517,7 +517,7 @@
     import scala.util.Random
     val rng = new Random(3)
 
-    val a1 = Array.tabulate(200)(_ => rng.nextDouble * 2.0 - 1.0) ++
+    val a1 = Array.tabulate(200)(_ => rng.nextDouble() * 2.0 - 1.0) ++
       Array.fill(20)(0.0) ++ Array.fill(20)(-0.0)
 
     val df1 = sc.parallelize(a1, 2).toDF("id")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/UnivariateFeatureSelectorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/UnivariateFeatureSelectorSuite.scala
index 84868dc..e83d0f6 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/UnivariateFeatureSelectorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/UnivariateFeatureSelectorSuite.scala
@@ -506,8 +506,8 @@
     val dataset_f_classification2 =
       spark.createDataFrame(data_f_classif2).toDF("label", "features", "topFeature")
 
-    val resultDF1 = ANOVATest.test(dataset_f_classification1.toDF, "features", "label", true)
-    val resultDF2 = ANOVATest.test(dataset_f_classification2.toDF, "features", "label", true)
+    val resultDF1 = ANOVATest.test(dataset_f_classification1.toDF(), "features", "label", true)
+    val resultDF2 = ANOVATest.test(dataset_f_classification2.toDF(), "features", "label", true)
     val selector = new UnivariateFeatureSelector()
       .setOutputCol("filtered")
       .setFeatureType("continuous")
@@ -632,8 +632,8 @@
     val dataset_f_regression2 =
       spark.createDataFrame(data_f_regression2).toDF("label", "features", "topFeature")
 
-    val resultDF1 = FValueTest.test(dataset_f_regression1.toDF, "features", "label", true)
-    val resultDF2 = FValueTest.test(dataset_f_regression2.toDF, "features", "label", true)
+    val resultDF1 = FValueTest.test(dataset_f_regression1.toDF(), "features", "label", true)
+    val resultDF2 = FValueTest.test(dataset_f_regression2.toDF(), "features", "label", true)
     val selector = new UnivariateFeatureSelector()
       .setOutputCol("filtered")
       .setFeatureType("continuous")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSizeHintSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSizeHintSuite.scala
index d89d10b..14faa81 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSizeHintSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSizeHintSuite.scala
@@ -198,7 +198,7 @@
     val b = Vectors.sparse(4, Array(0, 3), Array(3, 6))
 
     val stream = MemoryStream[(Vector, Vector)]
-    val streamingDF = stream.toDS.toDF("a", "b")
+    val streamingDF = stream.toDS().toDF("a", "b")
     val sizeHintA = new VectorSizeHint()
       .setSize(3)
       .setInputCol("a")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala
index 6d14350..2ae5498 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala
@@ -116,7 +116,7 @@
 
     var idx = 0
     for (fitIntercept <- Seq(false, true)) {
-      val yMean = instances2.map(_.label).mean
+      val yMean = instances2.map(_.label).mean()
       val newInstances = instances2.map { instance =>
         val mu = (instance.label + yMean) / 2.0
         val eta = math.log(mu)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/BinaryLogisticBlockAggregatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/BinaryLogisticBlockAggregatorSuite.scala
index f5ae22d..9ece1da 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/BinaryLogisticBlockAggregatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/BinaryLogisticBlockAggregatorSuite.scala
@@ -113,8 +113,8 @@
   test("check sizes") {
     val rng = new scala.util.Random
     val numFeatures = instances.head.features.size
-    val coefWithIntercept = Vectors.dense(Array.fill(numFeatures + 1)(rng.nextDouble))
-    val coefWithoutIntercept = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble))
+    val coefWithIntercept = Vectors.dense(Array.fill(numFeatures + 1)(rng.nextDouble()))
+    val coefWithoutIntercept = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble()))
     val block = InstanceBlock.fromInstances(instances)
 
     val aggIntercept = getNewAggregator(instances, coefWithIntercept,
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HingeBlockAggregatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HingeBlockAggregatorSuite.scala
index 029911a..f0167a6 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HingeBlockAggregatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HingeBlockAggregatorSuite.scala
@@ -112,8 +112,8 @@
   test("check sizes") {
     val rng = new scala.util.Random
     val numFeatures = instances.head.features.size
-    val coefWithIntercept = Vectors.dense(Array.fill(numFeatures + 1)(rng.nextDouble))
-    val coefWithoutIntercept = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble))
+    val coefWithIntercept = Vectors.dense(Array.fill(numFeatures + 1)(rng.nextDouble()))
+    val coefWithoutIntercept = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble()))
     val block = InstanceBlock.fromInstances(instances)
 
     val aggIntercept = getNewAggregator(instances, coefWithIntercept, fitIntercept = true)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HuberBlockAggregatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HuberBlockAggregatorSuite.scala
index df1a1d3..4bad50f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HuberBlockAggregatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/HuberBlockAggregatorSuite.scala
@@ -114,8 +114,8 @@
   test("check sizes") {
     val rng = new scala.util.Random
     val numFeatures = instances.head.features.size
-    val coefWithIntercept = Vectors.dense(Array.fill(numFeatures + 1)(rng.nextDouble))
-    val coefWithoutIntercept = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble))
+    val coefWithIntercept = Vectors.dense(Array.fill(numFeatures + 1)(rng.nextDouble()))
+    val coefWithoutIntercept = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble()))
     val block = InstanceBlock.fromInstances(instances)
 
     val aggIntercept = getNewAggregator(instances, coefWithIntercept,
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LeastSquaresBlockAggregatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LeastSquaresBlockAggregatorSuite.scala
index b71951c..11020eda 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LeastSquaresBlockAggregatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/LeastSquaresBlockAggregatorSuite.scala
@@ -110,7 +110,7 @@
   test("check sizes") {
     val rng = new scala.util.Random
     val numFeatures = instances.head.features.size
-    val coefVec = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble))
+    val coefVec = Vectors.dense(Array.fill(numFeatures)(rng.nextDouble()))
     val block = InstanceBlock.fromInstances(instances)
 
     val agg = getNewAggregator(instances, coefVec, fitIntercept = true)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/MultinomialLogisticBlockAggregatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/MultinomialLogisticBlockAggregatorSuite.scala
index d00fdac..8200085 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/MultinomialLogisticBlockAggregatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/aggregator/MultinomialLogisticBlockAggregatorSuite.scala
@@ -115,9 +115,9 @@
     val numFeatures = instances.head.features.size
     val numClasses = instances.map(_.label).distinct.size
     val coefWithIntercept = Vectors.dense(
-      Array.fill(numClasses * (numFeatures + 1))(rng.nextDouble))
+      Array.fill(numClasses * (numFeatures + 1))(rng.nextDouble()))
     val coefWithoutIntercept = Vectors.dense(
-      Array.fill(numClasses * numFeatures)(rng.nextDouble))
+      Array.fill(numClasses * numFeatures)(rng.nextDouble()))
     val block = InstanceBlock.fromInstances(instances)
 
     val aggIntercept = getNewAggregator(instances, coefWithIntercept,
diff --git a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
index 7ad26c0..d206b5f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
@@ -778,7 +778,7 @@
     import org.apache.spark.sql.functions._
 
     val (ratings, _) = genExplicitTestData(numUsers = 4, numItems = 4, rank = 1)
-    val data = ratings.toDF
+    val data = ratings.toDF()
     val knownUser = data.select(max("user")).as[Int].first()
     val unknownUser = knownUser + 10
     val knownItem = data.select(max("item")).as[Int].first()
@@ -815,7 +815,7 @@
     val spark = this.spark
     import spark.implicits._
     val (ratings, _) = genExplicitTestData(numUsers = 2, numItems = 2, rank = 1)
-    val data = ratings.toDF
+    val data = ratings.toDF()
     val model = new ALS().fit(data)
     Seq("nan", "NaN", "Nan", "drop", "DROP", "Drop").foreach { s =>
       testTransformer[Rating[Int]](data, model.setColdStartStrategy(s), "prediction") { _ => }
@@ -845,8 +845,8 @@
 
   test("recommendForAllUsers with k <, = and > num_items") {
     val model = getALSModel
-    val numUsers = model.userFactors.count
-    val numItems = model.itemFactors.count
+    val numUsers = model.userFactors.count()
+    val numItems = model.itemFactors.count()
     val expected = Map(
       0 -> Seq((3, 54f), (4, 44f), (5, 42f), (6, 28f)),
       1 -> Seq((3, 39f), (5, 33f), (4, 26f), (6, 16f)),
@@ -865,8 +865,8 @@
 
   test("recommendForAllItems with k <, = and > num_users") {
     val model = getALSModel
-    val numUsers = model.userFactors.count
-    val numItems = model.itemFactors.count
+    val numUsers = model.userFactors.count()
+    val numItems = model.itemFactors.count()
     val expected = Map(
       3 -> Seq((0, 54f), (2, 51f), (1, 39f)),
       4 -> Seq((0, 44f), (2, 30f), (1, 26f)),
@@ -888,13 +888,13 @@
     val spark = this.spark
     import spark.implicits._
     val model = getALSModel
-    val numItems = model.itemFactors.count
+    val numItems = model.itemFactors.count()
     val expected = Map(
       0 -> Seq((3, 54f), (4, 44f), (5, 42f), (6, 28f)),
       2 -> Seq((3, 51f), (5, 45f), (4, 30f), (6, 18f))
     )
     val userSubset = expected.keys.toSeq.toDF("user")
-    val numUsersSubset = userSubset.count
+    val numUsersSubset = userSubset.count()
 
     Seq(2, 4, 6).foreach { k =>
       val n = math.min(k, numItems).toInt
@@ -910,13 +910,13 @@
     val spark = this.spark
     import spark.implicits._
     val model = getALSModel
-    val numUsers = model.userFactors.count
+    val numUsers = model.userFactors.count()
     val expected = Map(
       3 -> Seq((0, 54f), (2, 51f), (1, 39f)),
       6 -> Seq((0, 28f), (2, 18f), (1, 16f))
     )
     val itemSubset = expected.keys.toSeq.toDF("item")
-    val numItemsSubset = itemSubset.count
+    val numItemsSubset = itemSubset.count()
 
     Seq(2, 3, 4).foreach { k =>
       val n = math.min(k, numUsers).toInt
@@ -939,7 +939,7 @@
     val singleUserRecs = model.recommendForUserSubset(users, k)
     val dupUserRecs = model.recommendForUserSubset(dupUsers, k)
       .as[(Int, Seq[(Int, Float)])].collect().toMap
-    assert(singleUserRecs.count == dupUserRecs.size)
+    assert(singleUserRecs.count() == dupUserRecs.size)
     checkRecommendations(singleUserRecs, dupUserRecs, "item")
 
     val items = Seq(3, 4, 5).toDF("item")
@@ -947,7 +947,7 @@
     val singleItemRecs = model.recommendForItemSubset(items, k)
     val dupItemRecs = model.recommendForItemSubset(dupItems, k)
       .as[(Int, Seq[(Int, Float)])].collect().toMap
-    assert(singleItemRecs.count == dupItemRecs.size)
+    assert(singleItemRecs.count() == dupItemRecs.size)
     checkRecommendations(singleItemRecs, dupItemRecs, "user")
   }
 
@@ -981,7 +981,7 @@
     val spark = this.spark
     import spark.implicits._
     val (ratings, _) = genExplicitTestData(numUsers = 2, numItems = 2, rank = 1)
-    val data = ratings.toDF
+    val data = ratings.toDF()
     val model = new ALS()
       .setMaxIter(2)
       .setImplicitPrefs(true)
@@ -1045,7 +1045,7 @@
         // Generate test data
         val (training, _) = ALSSuite.genImplicitTestData(sc, 20, 5, 1, 0.2, 0)
         // Implicitly test the cleaning of parents during ALS training
-        val spark = SparkSession.builder
+        val spark = SparkSession.builder()
           .sparkContext(sc)
           .getOrCreate()
         import spark.implicits._
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala
index 7e96281..6a745b6 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala
@@ -112,7 +112,7 @@
       .setMaxDepth(2)
       .setMaxIter(2)
     val model = gbt.fit(trainData.toDF())
-    testPredictionModelSinglePrediction(model, validationData.toDF)
+    testPredictionModelSinglePrediction(model, validationData.toDF())
   }
 
   test("Checkpointing") {
@@ -241,14 +241,14 @@
         .setMaxDepth(2)
         .setMaxIter(3)
         .setLossType(lossType)
-      val model3 = gbt.fit(trainData.toDF)
+      val model3 = gbt.fit(trainData.toDF())
       val model1 = new GBTRegressionModel("gbt-reg-model-test1",
         model3.trees.take(1), model3.treeWeights.take(1), model3.numFeatures)
       val model2 = new GBTRegressionModel("gbt-reg-model-test2",
         model3.trees.take(2), model3.treeWeights.take(2), model3.numFeatures)
 
       for (evalLossType <- GBTRegressor.supportedLossTypes) {
-        val evalArr = model3.evaluateEachIteration(validationData.toDF, evalLossType)
+        val evalArr = model3.evaluateEachIteration(validationData.toDF(), evalLossType)
         val lossErr1 = GradientBoostedTrees.computeWeightedError(validationData.map(_.toInstance),
           model1.trees, model1.treeWeights, model1.convertToOldLossType(evalLossType))
         val lossErr2 = GradientBoostedTrees.computeWeightedError(validationData.map(_.toInstance),
@@ -315,7 +315,7 @@
       .setMaxDepth(2)
       .setCheckpointInterval(5)
       .setSeed(123)
-    val model = gbt.fit(trainData.toDF)
+    val model = gbt.fit(trainData.toDF())
 
     model.trees.foreach (i => {
       assert(i.getMaxDepth === model.getMaxDepth)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
index 1836b07..df03848 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
@@ -1719,7 +1719,7 @@
     val conf = new SparkConf(false)
     val ser = new KryoSerializer(conf).newInstance()
     val trainer = new GeneralizedLinearRegression()
-    val model = trainer.fit(Seq(Instance(1.0, 1.0, Vectors.dense(1.0, 7.0))).toDF)
+    val model = trainer.fit(Seq(Instance(1.0, 1.0, Vectors.dense(1.0, 7.0))).toDF())
     ser.serialize[GeneralizedLinearRegressionModel](model)
   }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala
index 7981296..411e056 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala
@@ -45,17 +45,17 @@
     val rdd = sc.makeRDD(rows)
     val df = spark.createDataFrame(rdd, imageSchema)
 
-    assert(df.count === 2, "incorrect image count")
+    assert(df.count() === 2, "incorrect image count")
     assert(df.schema("image").dataType == columnSchema, "data do not fit ImageSchema")
   }
 
   // TODO(SPARK-40171): Re-enable the following flaky test case after being fixed.
   ignore("image datasource count test") {
     val df1 = spark.read.format("image").load(imagePath)
-    assert(df1.count === 9)
+    assert(df1.count() === 9)
 
     val df2 = spark.read.format("image").option("dropInvalid", true).load(imagePath)
-    assert(df2.count === 8)
+    assert(df2.count() === 8)
   }
 
   test("image datasource test: read jpg image") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
index 12e9a51..db685b6 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
@@ -173,8 +173,8 @@
 
   test("select features from libsvm relation") {
     val df = spark.read.format("libsvm").load(path)
-    df.select("features").rdd.map { case Row(d: Vector) => d }.first
-    df.select("features").collect
+    df.select("features").rdd.map { case Row(d: Vector) => d }.first()
+    df.select("features").collect()
   }
 
   test("create libsvmTable table without schema") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
index 3ca6816..274e5b0 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
@@ -96,7 +96,7 @@
         Array(6), Gini, QuantileStrategy.Sort,
         0, 0, 0.0, 0.0, 0, 0
       )
-      val featureSamples = Array.fill(10000)((1.0, math.random)).filter(_._2 != 0.0)
+      val featureSamples = Array.fill(10000)((1.0, math.random())).filter(_._2 != 0.0)
       val splits = RandomForest.findSplitsForContinuousFeature(featureSamples, fakeMetadata, 0)
       assert(splits.length === 5)
       assert(fakeMetadata.numSplits(0) === 5)
@@ -183,7 +183,7 @@
         Array(6), Gini, QuantileStrategy.Sort,
         0, 0, 0.0, 0.0, 0, 0
       )
-      val featureSamplesUnitWeight = Array.fill(10)((1.0, math.random))
+      val featureSamplesUnitWeight = Array.fill(10)((1.0, math.random()))
       val featureSamplesSmallWeight = featureSamplesUnitWeight.map { case (w, x) => (w * 0.001, x)}
       val featureSamplesLargeWeight = featureSamplesUnitWeight.map { case (w, x) => (w * 1000, x)}
       val splitsUnitWeight = RandomForest
diff --git a/mllib/src/test/scala/org/apache/spark/ml/util/PMMLReadWriteTest.scala b/mllib/src/test/scala/org/apache/spark/ml/util/PMMLReadWriteTest.scala
index 19e9fe4..a579684 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/util/PMMLReadWriteTest.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/util/PMMLReadWriteTest.scala
@@ -44,7 +44,7 @@
       instance.write.format("pmml").save(path)
     }
     instance.write.format("pmml").overwrite().save(path)
-    val pmmlStr = sc.textFile(path).collect.mkString("\n")
+    val pmmlStr = sc.textFile(path).collect().mkString("\n")
     val pmmlModel = PMMLUtils.loadFromString(pmmlStr)
     assert(pmmlModel.getHeader().getApplication().getName().startsWith("Apache Spark"))
     checkModelData(pmmlModel)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
index c4621c9..ee90c82 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala
@@ -143,7 +143,7 @@
         for (i <- 0 until nClasses) {
           if (p < probs(i)) {
             y = i
-            break
+            break()
           }
         }
       }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/DistanceMeasureSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/DistanceMeasureSuite.scala
index 73691c4..f8a1151 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/DistanceMeasureSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/DistanceMeasureSuite.scala
@@ -40,12 +40,12 @@
     val rng = new Random(seed)
 
     centers = Array.tabulate(k) { i =>
-      val values = Array.fill(dim)(rng.nextGaussian)
+      val values = Array.fill(dim)(rng.nextGaussian())
       new VectorWithNorm(Vectors.dense(values))
     }
 
     data = Array.tabulate(1000) { i =>
-      val values = Array.fill(dim)(rng.nextGaussian)
+      val values = Array.fill(dim)(rng.nextGaussian())
       new VectorWithNorm(Vectors.dense(values))
     }
   }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala
index e63ca70..1737a7f 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/clustering/KMeansSuite.scala
@@ -80,7 +80,8 @@
   test("unique cluster centers") {
     val rng = new Random(seed)
     val numDistinctPoints = 10
-    val points = (0 until numDistinctPoints).map(i => Vectors.dense(Array.fill(3)(rng.nextDouble)))
+    val points =
+      (0 until numDistinctPoints).map(i => Vectors.dense(Array.fill(3)(rng.nextDouble())))
     val data = sc.parallelize(points.flatMap(Array.fill(1 + rng.nextInt(3))(_)), 2)
     val normedData = data.map(new VectorWithNorm(_))
 
@@ -362,7 +363,7 @@
     val n = 200000
     val points = sc.parallelize(0 until m, 2).mapPartitionsWithIndex { (idx, iter) =>
       val random = new Random(idx)
-      iter.map(i => Vectors.dense(Array.fill(n)(random.nextDouble)))
+      iter.map(i => Vectors.dense(Array.fill(n)(random.nextDouble())))
     }.cache()
     for (initMode <- Seq(KMeans.RANDOM, KMeans.K_MEANS_PARALLEL)) {
       // If we serialize data directly in the task closure, the size of the serialized task would be
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
index ca452a8..19d424c 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
@@ -284,11 +284,11 @@
       val nnz = random.nextInt(m)
 
       val indices1 = random.shuffle(0 to m - 1).slice(0, nnz).sorted.toArray
-      val values1 = Array.fill(nnz)(random.nextDouble)
+      val values1 = Array.fill(nnz)(random.nextDouble())
       val sparseVector1 = Vectors.sparse(m, indices1, values1)
 
       val indices2 = random.shuffle(0 to m - 1).slice(0, nnz).sorted.toArray
-      val values2 = Array.fill(nnz)(random.nextDouble)
+      val values2 = Array.fill(nnz)(random.nextDouble())
       val sparseVector2 = Vectors.sparse(m, indices2, values2)
 
       val denseVector1 = Vectors.dense(sparseVector1.toArray)
@@ -578,8 +578,8 @@
         valuesBuilder += v
       }
       val (indices, values) = vec.activeIterator.toArray.unzip
-      assert(indicesBuilder.result === indices)
-      assert(valuesBuilder.result === values)
+      assert(indicesBuilder.result() === indices)
+      assert(valuesBuilder.result() === values)
     }
   }
 
@@ -599,8 +599,8 @@
         }
       }
       val (indices, values) = vec.nonZeroIterator.toArray.unzip
-      assert(indicesBuilder.result === indices)
-      assert(valuesBuilder.result === values)
+      assert(indicesBuilder.result() === indices)
+      assert(valuesBuilder.result() === values)
     }
   }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrixSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrixSuite.scala
index 0e78982..bc1ae86 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrixSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrixSuite.scala
@@ -136,9 +136,9 @@
     assert(rowMat.toBreeze() === gridBasedMat.toBreeze())
 
     // SPARK-15922: BlockMatrix to IndexedRowMatrix throws an error"
-    val bmat = rowMat.toBlockMatrix
-    val imat = bmat.toIndexedRowMatrix
-    imat.rows.collect
+    val bmat = rowMat.toBlockMatrix()
+    val imat = bmat.toIndexedRowMatrix()
+    imat.rows.collect()
 
     val rows = 1
     val cols = 10
@@ -155,7 +155,7 @@
     val rdd = sc.parallelize(vectors)
     val B = new BlockMatrix(rdd, rows, cols)
 
-    val C = B.toIndexedRowMatrix.rows.collect
+    val C = B.toIndexedRowMatrix().rows.collect()
 
     (C(0).vector.asBreeze, C(1).vector.asBreeze) match {
       case (denseVector: BDV[Double], sparseVector: BSV[Double]) =>
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala
index adc4eee..9bd6529 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala
@@ -293,7 +293,7 @@
       val calcR = result.R
       assert(closeToZero(abs(expected.q) - abs(calcQ.toBreeze())))
       assert(closeToZero(abs(expected.r) - abs(calcR.asBreeze.asInstanceOf[BDM[Double]])))
-      assert(closeToZero(calcQ.multiply(calcR).toBreeze - mat.toBreeze()))
+      assert(closeToZero(calcQ.multiply(calcR).toBreeze() - mat.toBreeze()))
       // Decomposition without computing Q
       val rOnly = mat.tallSkinnyQR(computeQ = false)
       assert(rOnly.Q == null)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/optimization/LBFGSSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/optimization/LBFGSSuite.scala
index 1318b23..48c5726 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/optimization/LBFGSSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/optimization/LBFGSSuite.scala
@@ -258,7 +258,7 @@
     val n = 200000
     val examples = sc.parallelize(0 until m, 2).mapPartitionsWithIndex { (idx, iter) =>
       val random = new Random(idx)
-      iter.map(i => (1.0, Vectors.dense(Array.fill(n)(random.nextDouble))))
+      iter.map(i => (1.0, Vectors.dense(Array.fill(n)(random.nextDouble()))))
     }.cache()
     val lbfgs = new LBFGS(new LogisticGradient, new SquaredL2Updater)
       .setNumCorrections(1)
@@ -268,6 +268,6 @@
     val random = new Random(0)
     // If we serialize data directly in the task closure, the size of the serialized task would be
     // greater than 1MB and hence Spark would throw an error.
-    val weights = lbfgs.optimize(examples, Vectors.dense(Array.fill(n)(random.nextDouble)))
+    val weights = lbfgs.optimize(examples, Vectors.dense(Array.fill(n)(random.nextDouble())))
   }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala
index 60a2781..7d672f7 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala
@@ -35,7 +35,7 @@
 
     // assert that the PMML format is as expected
     assert(logisticModelExport.isInstanceOf[PMMLModelExport])
-    val pmml = logisticModelExport.getPmml
+    val pmml = logisticModelExport.getPmml()
     assert(pmml.getHeader.getDescription === "logistic regression")
     // check that the number of fields match the weights size
     assert(pmml.getDataDictionary.getNumberOfFields === logisticRegressionModel.weights.size + 1)
@@ -62,7 +62,7 @@
 
     // assert that the PMML format is as expected
     assert(svmModelExport.isInstanceOf[PMMLModelExport])
-    val pmml = svmModelExport.getPmml
+    val pmml = svmModelExport.getPmml()
     assert(pmml.getHeader.getDescription
       === "linear SVM")
     // check that the number of fields match the weights size
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala
index bf1a0fd..b6494f3 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala
@@ -32,7 +32,7 @@
     val linearModelExport = PMMLModelExportFactory.createPMMLModelExport(linearRegressionModel)
     // assert that the PMML format is as expected
     assert(linearModelExport.isInstanceOf[PMMLModelExport])
-    val pmml = linearModelExport.getPmml
+    val pmml = linearModelExport.getPmml()
     assert(pmml.getHeader.getDescription === "linear regression")
     // check that the number of fields match the weights size
     assert(pmml.getDataDictionary.getNumberOfFields === linearRegressionModel.weights.size + 1)
@@ -51,7 +51,7 @@
     val ridgeModelExport = PMMLModelExportFactory.createPMMLModelExport(ridgeRegressionModel)
     // assert that the PMML format is as expected
     assert(ridgeModelExport.isInstanceOf[PMMLModelExport])
-    val pmml = ridgeModelExport.getPmml
+    val pmml = ridgeModelExport.getPmml()
     assert(pmml.getHeader.getDescription === "ridge regression")
     // check that the number of fields match the weights size
     assert(pmml.getDataDictionary.getNumberOfFields === ridgeRegressionModel.weights.size + 1)
@@ -69,7 +69,7 @@
     val lassoModelExport = PMMLModelExportFactory.createPMMLModelExport(lassoModel)
     // assert that the PMML format is as expected
     assert(lassoModelExport.isInstanceOf[PMMLModelExport])
-    val pmml = lassoModelExport.getPmml
+    val pmml = lassoModelExport.getPmml()
     assert(pmml.getHeader.getDescription === "lasso regression")
     // check that the number of fields match the weights size
     assert(pmml.getDataDictionary.getNumberOfFields === lassoModel.weights.size + 1)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala
index 0460b8a..70e6878 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala
@@ -36,7 +36,7 @@
 
     // assert that the PMML format is as expected
     assert(modelExport.isInstanceOf[PMMLModelExport])
-    val pmml = modelExport.getPmml
+    val pmml = modelExport.getPmml()
     assert(pmml.getHeader.getDescription === "k-means clustering")
     // check that the number of fields match the single vector size
     assert(pmml.getDataDictionary.getNumberOfFields === clusterCenters(0).size)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
index 470e101..c177ff5 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
@@ -56,7 +56,7 @@
       epsilon: Double = 0.01): Unit = {
     assert(expectedNumPartitions === rdd.partitions.size)
     val values = new ArrayBuffer[Double]()
-    rdd.collect.foreach { vector => {
+    rdd.collect().foreach { vector => {
       assert(vector.size === expectedColumns)
       values ++= vector.toArray
     }}
@@ -144,7 +144,7 @@
 
     // mock distribution to check that partitions have unique seeds
     val random = RandomRDDs.randomRDD(sc, new MockDistro(), 1000L, 1000, 0L)
-    assert(random.collect.size === random.collect.distinct.size)
+    assert(random.collect().size === random.collect().distinct.size)
   }
 
   test("randomVectorRDD for different distributions") {
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala b/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala
index 3a7040d..d61514b 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/util/MLlibTestSparkContext.scala
@@ -35,7 +35,7 @@
 
   override def beforeAll(): Unit = {
     super.beforeAll()
-    spark = SparkSession.builder
+    spark = SparkSession.builder()
       .master("local[2]")
       .appName("MLlibUnitTest")
       .getOrCreate()
diff --git a/pom.xml b/pom.xml
index 56ad7f4..da9245a 100644
--- a/pom.xml
+++ b/pom.xml
@@ -2972,7 +2972,16 @@
               -->
               <arg>-Wconf:msg=^(?=.*?method|value|type|object|trait|inheritance)(?=.*?deprecated)(?=.*?since 2.13).+$:s</arg>
               <arg>-Wconf:msg=^(?=.*?Widening conversion from)(?=.*?is deprecated because it loses precision).+$:s</arg>
-              <arg>-Wconf:msg=Auto-application to \`\(\)\` is deprecated:s</arg>
+              <!-- SPARK-45610 Convert "Auto-application to `()` is deprecated" to compile error, as it will become a compile error in Scala 3. -->
+              <arg>-Wconf:cat=deprecation&amp;msg=Auto-application to \`\(\)\` is deprecated:e</arg>
+              <!--
+                TODO(SPARK-45615): The issue described by https://github.com/scalatest/scalatest/issues/2297 can cause false positives.
+                  So SPARK-45610 added the following 4 suppression rules, which can be removed after upgrading scalatest to 3.2.18.
+              -->
+              <arg>-Wconf:cat=deprecation&amp;msg=Auto-application to \`\(\)\` is deprecated&amp;site=org.apache.spark.rdd.RDDSuite:s</arg>
+              <arg>-Wconf:cat=deprecation&amp;msg=Auto-application to \`\(\)\` is deprecated&amp;site=org.apache.spark.scheduler.TaskSetManagerSuite:s</arg>
+              <arg>-Wconf:cat=deprecation&amp;msg=Auto-application to \`\(\)\` is deprecated&amp;site=org.apache.spark.streaming.ReceiverInputDStreamSuite:s</arg>
+              <arg>-Wconf:cat=deprecation&amp;msg=Auto-application to \`\(\)\` is deprecated&amp;site=org.apache.spark.streaming.kafka010.KafkaRDDSuite:s</arg>
               <!--
                 SPARK-35574 Prevent the recurrence of compilation warnings related to
                 `procedure syntax is deprecated`
diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala
index d2c9771..82a263d 100644
--- a/project/SparkBuild.scala
+++ b/project/SparkBuild.scala
@@ -237,7 +237,14 @@
         //  fixed.
         "-Wconf:msg=^(?=.*?method|value|type|object|trait|inheritance)(?=.*?deprecated)(?=.*?since 2.13).+$:s",
         "-Wconf:msg=^(?=.*?Widening conversion from)(?=.*?is deprecated because it loses precision).+$:s",
-        "-Wconf:msg=Auto-application to \\`\\(\\)\\` is deprecated:s",
+        // SPARK-45610 Convert "Auto-application to `()` is deprecated" to compile error, as it will become a compile error in Scala 3.
+        "-Wconf:cat=deprecation&msg=Auto-application to \\`\\(\\)\\` is deprecated:e",
+        // TODO(SPARK-45615): The issue described by https://github.com/scalatest/scalatest/issues/2297 can cause false positives.
+        //  So SPARK-45610 added the following 4 suppression rules, which can be removed after upgrading scalatest to 3.2.18.
+        "-Wconf:cat=deprecation&msg=Auto-application to \\`\\(\\)\\` is deprecated&site=org.apache.spark.rdd.RDDSuite:s",
+        "-Wconf:cat=deprecation&msg=Auto-application to \\`\\(\\)\\` is deprecated&site=org.apache.spark.scheduler.TaskSetManagerSuite:s",
+        "-Wconf:cat=deprecation&msg=Auto-application to \\`\\(\\)\\` is deprecated&site=org.apache.spark.streaming.ReceiverInputDStreamSuite:s",
+        "-Wconf:cat=deprecation&msg=Auto-application to \\`\\(\\)\\` is deprecated&site=org.apache.spark.streaming.kafka010.KafkaRDDSuite:s",
         // SPARK-35574 Prevent the recurrence of compilation warnings related to `procedure syntax is deprecated`
         "-Wconf:cat=deprecation&msg=procedure syntax is deprecated:e",
         // SPARK-35496 Upgrade Scala to 2.13.7 and suppress:
diff --git a/repl/src/main/scala/org/apache/spark/repl/Main.scala b/repl/src/main/scala/org/apache/spark/repl/Main.scala
index c8d9be4..e3ce28b 100644
--- a/repl/src/main/scala/org/apache/spark/repl/Main.scala
+++ b/repl/src/main/scala/org/apache/spark/repl/Main.scala
@@ -82,7 +82,7 @@
 
     if (!hasErrors) {
       interp.run(settings) // Repl starts and goes in loop of R.E.P.L
-      Option(sparkContext).foreach(_.stop)
+      Option(sparkContext).foreach(_.stop())
     }
   }
 
@@ -103,7 +103,7 @@
         conf.setSparkHome(System.getenv("SPARK_HOME"))
       }
 
-      val builder = SparkSession.builder.config(conf)
+      val builder = SparkSession.builder().config(conf)
       if (conf
             .get(CATALOG_IMPLEMENTATION.key, "hive")
             .toLowerCase(Locale.ROOT) == "hive") {
diff --git a/resource-managers/kubernetes/core/src/main/scala/org/apache/spark/deploy/k8s/submit/KubernetesClientApplication.scala b/resource-managers/kubernetes/core/src/main/scala/org/apache/spark/deploy/k8s/submit/KubernetesClientApplication.scala
index 389ba18..662f5dd 100644
--- a/resource-managers/kubernetes/core/src/main/scala/org/apache/spark/deploy/k8s/submit/KubernetesClientApplication.scala
+++ b/resource-managers/kubernetes/core/src/main/scala/org/apache/spark/deploy/k8s/submit/KubernetesClientApplication.scala
@@ -198,7 +198,7 @@
           // Break the while loop if the pod is completed or we don't want to wait
           if (watcher.watchOrStop(sId)) {
             watch.close()
-            break
+            break()
           }
         }
       }
diff --git a/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocatorSuite.scala b/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocatorSuite.scala
index 113e36e..eb9246a 100644
--- a/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocatorSuite.scala
+++ b/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocatorSuite.scala
@@ -137,7 +137,7 @@
     waitForExecutorPodsClock = new ManualClock(0L)
     podsAllocatorUnderTest = new ExecutorPodsAllocator(
       conf, secMgr, executorBuilder, kubernetesClient, snapshotsStore, waitForExecutorPodsClock)
-    when(schedulerBackend.getExecutorIds).thenReturn(Seq.empty)
+    when(schedulerBackend.getExecutorIds()).thenReturn(Seq.empty)
     podsAllocatorUnderTest.start(TEST_SPARK_APP_ID, schedulerBackend)
     when(kubernetesClient.persistentVolumeClaims()).thenReturn(persistentVolumeClaims)
     when(persistentVolumeClaims.inNamespace("default")).thenReturn(pvcWithNamespace)
@@ -504,7 +504,7 @@
 
     // Newly created executors (both acknowledged and not) are cleaned up.
     waitForExecutorPodsClock.advance(executorIdleTimeout * 2)
-    when(schedulerBackend.getExecutorIds).thenReturn(Seq("1", "3", "4"))
+    when(schedulerBackend.getExecutorIds()).thenReturn(Seq("1", "3", "4"))
     snapshotsStore.notifySubscribers()
     // SPARK-34361: even as 1, 3 and 4 are not timed out as they are considered as known PODs so
     // this is why they are not counted into the outstanding PODs and /they are not removed even
@@ -586,7 +586,7 @@
     verify(podsWithNamespace).resource(podWithAttachedContainerForId(7, rp.id))
 
     // 1) make 1 POD known by the scheduler backend for each resource profile
-    when(schedulerBackend.getExecutorIds).thenReturn(Seq("1", "4"))
+    when(schedulerBackend.getExecutorIds()).thenReturn(Seq("1", "4"))
     snapshotsStore.notifySubscribers()
     assert(podsAllocatorUnderTest.numOutstandingPods.get() == 5,
       "scheduler backend known PODs are not outstanding")
@@ -594,7 +594,7 @@
 
     // 2) make 1 extra POD known by the scheduler backend for each resource profile
     // and make some to pending
-    when(schedulerBackend.getExecutorIds).thenReturn(Seq("1", "2", "4", "5"))
+    when(schedulerBackend.getExecutorIds()).thenReturn(Seq("1", "2", "4", "5"))
     snapshotsStore.updatePod(pendingExecutor(2, defaultProfile.id))
     snapshotsStore.updatePod(pendingExecutor(3, defaultProfile.id))
     snapshotsStore.updatePod(pendingExecutor(5, rp.id))
diff --git a/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/StatefulSetAllocatorSuite.scala b/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/StatefulSetAllocatorSuite.scala
index f74d2c9..474d5b0 100644
--- a/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/StatefulSetAllocatorSuite.scala
+++ b/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/StatefulSetAllocatorSuite.scala
@@ -124,7 +124,7 @@
     snapshotsStore = new DeterministicExecutorPodsSnapshotsStore()
     podsAllocatorUnderTest = new StatefulSetPodsAllocator(
       conf, secMgr, executorBuilder, kubernetesClient, snapshotsStore, null)
-    when(schedulerBackend.getExecutorIds).thenReturn(Seq.empty)
+    when(schedulerBackend.getExecutorIds()).thenReturn(Seq.empty)
     podsAllocatorUnderTest.start(TEST_SPARK_APP_ID, schedulerBackend)
   }
 
diff --git a/resource-managers/kubernetes/integration-tests/src/test/scala/org/apache/spark/deploy/k8s/integrationtest/backend/minikube/MinikubeTestBackend.scala b/resource-managers/kubernetes/integration-tests/src/test/scala/org/apache/spark/deploy/k8s/integrationtest/backend/minikube/MinikubeTestBackend.scala
index 36c2711..0d73cb8 100644
--- a/resource-managers/kubernetes/integration-tests/src/test/scala/org/apache/spark/deploy/k8s/integrationtest/backend/minikube/MinikubeTestBackend.scala
+++ b/resource-managers/kubernetes/integration-tests/src/test/scala/org/apache/spark/deploy/k8s/integrationtest/backend/minikube/MinikubeTestBackend.scala
@@ -26,7 +26,7 @@
 
   override def initialize(): Unit = {
     Minikube.logVersion()
-    val minikubeStatus = Minikube.getMinikubeStatus
+    val minikubeStatus = Minikube.getMinikubeStatus()
     require(minikubeStatus == MinikubeStatus.RUNNING,
         s"Minikube must be running to use the Minikube backend for integration tests." +
           s" Current status is: $minikubeStatus.")
diff --git a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
index 4fa7b66..4f1ba3b 100644
--- a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
+++ b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala
@@ -104,7 +104,7 @@
   @volatile private var exitCode = 0
   @volatile private var unregistered = false
   @volatile private var finished = false
-  @volatile private var finalStatus = getDefaultFinalStatus
+  @volatile private var finalStatus = getDefaultFinalStatus()
   @volatile private var finalMsg: String = ""
   @volatile private var userClassThread: Thread = _
 
@@ -515,7 +515,7 @@
         val driverRef = rpcEnv.setupEndpointRef(
           RpcAddress(host, port),
           YarnSchedulerBackend.ENDPOINT_NAME)
-        createAllocator(driverRef, userConf, rpcEnv, appAttemptId, distCacheConf)
+        createAllocator(driverRef, userConf, rpcEnv, appAttemptId, distCacheConf())
       } else {
         // Sanity check; should never happen in normal operation, since sc should only be null
         // if the user app did not create a SparkContext.
@@ -553,7 +553,7 @@
       YarnSchedulerBackend.ENDPOINT_NAME)
     addAmIpFilter(Some(driverRef),
       System.getenv(ApplicationConstants.APPLICATION_WEB_PROXY_BASE_ENV))
-    createAllocator(driverRef, sparkConf, rpcEnv, appAttemptId, distCacheConf)
+    createAllocator(driverRef, sparkConf, rpcEnv, appAttemptId, distCacheConf())
 
     // In client mode the actor will stop the reporter thread.
     reporterThread.join()
diff --git a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
index b209149..8153ed5 100644
--- a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
+++ b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala
@@ -1187,7 +1187,7 @@
       Thread.sleep(interval)
       val report: ApplicationReport =
         try {
-          getApplicationReport
+          getApplicationReport()
         } catch {
           case e: ApplicationNotFoundException =>
             logError(s"Application $appId not found.")
@@ -1353,7 +1353,7 @@
   def run(): Unit = {
     submitApplication()
     if (!launcherBackend.isConnected() && fireAndForget) {
-      val report = getApplicationReport
+      val report = getApplicationReport()
       val state = report.getYarnApplicationState
       logInfo(s"Application report for $appId (state: $state)")
       logInfo(formatReportDetails(report, getDriverLogsLink(report)))
diff --git a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocatorNodeHealthTracker.scala b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocatorNodeHealthTracker.scala
index e778254..d7bdd17 100644
--- a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocatorNodeHealthTracker.scala
+++ b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocatorNodeHealthTracker.scala
@@ -144,5 +144,5 @@
     allocatorExcludedNodeList.retain { (_, expiryTime) => expiryTime > now }
   }
 
-  refreshExcludedNodes
+  refreshExcludedNodes()
 }
diff --git a/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala b/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala
index 3728c33..3e25a3a 100644
--- a/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala
+++ b/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala
@@ -28,7 +28,7 @@
   extends YarnSchedulerBackend(scheduler, sc) {
 
   override def start(): Unit = {
-    val attemptId = ApplicationMaster.getAttemptId
+    val attemptId = ApplicationMaster.getAttemptId()
     bindToYarn(attemptId.getApplicationId(), Some(attemptId))
     super.start()
     totalExpectedExecutors = SchedulerBackendUtils.getInitialTargetExecutorNumber(sc.conf)
diff --git a/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala b/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala
index 34848a7..1cfb3d9 100644
--- a/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala
+++ b/resource-managers/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala
@@ -138,7 +138,7 @@
   override def applicationId(): String = {
     appId.map(_.toString).getOrElse {
       logWarning("Application ID is not initialized yet.")
-      super.applicationId
+      super.applicationId()
     }
   }
 
diff --git a/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/ContainerPlacementStrategySuite.scala b/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/ContainerPlacementStrategySuite.scala
index 0cabef7..b9f60d6 100644
--- a/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/ContainerPlacementStrategySuite.scala
+++ b/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/ContainerPlacementStrategySuite.scala
@@ -51,7 +51,7 @@
     handler.updateResourceRequests()
     handler.handleAllocatedContainers(Array(createContainer("host1"), createContainer("host2")))
 
-    ResourceProfile.clearDefaultProfile
+    ResourceProfile.clearDefaultProfile()
     val rp = ResourceProfile.getOrCreateDefaultProfile(allocatorConf)
     val localities = handler.containerPlacementStrategy.localityOfRequestedContainers(
       3, 15, Map("host3" -> 15, "host4" -> 15, "host5" -> 10),
@@ -76,7 +76,7 @@
       createContainer("host2")
     ))
 
-    ResourceProfile.clearDefaultProfile
+    ResourceProfile.clearDefaultProfile()
     val rp = ResourceProfile.getOrCreateDefaultProfile(allocatorConf)
 
     val localities = handler.containerPlacementStrategy.localityOfRequestedContainers(
@@ -100,7 +100,7 @@
       createContainer("host2")
     ))
 
-    ResourceProfile.clearDefaultProfile
+    ResourceProfile.clearDefaultProfile()
     val rp = ResourceProfile.getOrCreateDefaultProfile(allocatorConf)
     val localities = handler.containerPlacementStrategy.localityOfRequestedContainers(
       1, 15, Map("host1" -> 15, "host2" -> 15, "host3" -> 10),
@@ -122,7 +122,7 @@
       createContainer("host3")
     ))
 
-    ResourceProfile.clearDefaultProfile
+    ResourceProfile.clearDefaultProfile()
     val rp = ResourceProfile.getOrCreateDefaultProfile(allocatorConf)
     val localities = handler.containerPlacementStrategy.localityOfRequestedContainers(
       3, 15, Map("host1" -> 15, "host2" -> 15, "host3" -> 10),
@@ -138,7 +138,7 @@
     handler.updateResourceRequests()
     handler.handleAllocatedContainers(Array(createContainer("host1"), createContainer("host2")))
 
-    ResourceProfile.clearDefaultProfile
+    ResourceProfile.clearDefaultProfile()
     val rp = ResourceProfile.getOrCreateDefaultProfile(allocatorConf)
     val localities = handler.containerPlacementStrategy.localityOfRequestedContainers(
       1, 0, Map.empty,
@@ -160,7 +160,7 @@
       createContainerRequest(Array("host2", "host3")),
       createContainerRequest(Array("host1", "host4")))
 
-    ResourceProfile.clearDefaultProfile
+    ResourceProfile.clearDefaultProfile()
     val rp = ResourceProfile.getOrCreateDefaultProfile(allocatorConf)
     val localities = handler.containerPlacementStrategy.localityOfRequestedContainers(
       1, 15, Map("host1" -> 15, "host2" -> 15, "host3" -> 10),
diff --git a/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala b/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala
index 2637b2e..806efd39 100644
--- a/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala
+++ b/resource-managers/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala
@@ -602,7 +602,7 @@
       assert(configFromExecutors.find(_ == null) === None)
 
       // verify log urls are present
-      val listeners = sc.listenerBus.findListenersByClass[SaveExecutorInfo]
+      val listeners = sc.listenerBus.findListenersByClass[SaveExecutorInfo]()
       assert(listeners.size === 1)
       val listener = listeners(0)
       val executorInfos = listener.addedExecutorInfos.values
diff --git a/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/DateFormatter.scala b/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/DateFormatter.scala
index a41d2a0..34d19bb 100644
--- a/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/DateFormatter.scala
+++ b/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/DateFormatter.scala
@@ -77,7 +77,7 @@
   override def validatePatternString(): Unit = {
     try {
       formatter
-    } catch checkLegacyFormatter(pattern, legacyFormatter.validatePatternString)
+    } catch checkLegacyFormatter(pattern, legacyFormatter.validatePatternString())
     ()
   }
 }
diff --git a/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/TimestampFormatter.scala b/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/TimestampFormatter.scala
index 55eee41..df146e0 100644
--- a/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/TimestampFormatter.scala
+++ b/sql/api/src/main/scala/org/apache/spark/sql/catalyst/util/TimestampFormatter.scala
@@ -316,7 +316,7 @@
  */
 class FractionTimestampFormatter(zoneId: ZoneId)
   extends Iso8601TimestampFormatter(
-    TimestampFormatter.defaultPattern,
+    TimestampFormatter.defaultPattern(),
     zoneId,
     TimestampFormatter.defaultLocale,
     LegacyDateFormats.FAST_DATE_FORMAT,
@@ -510,7 +510,7 @@
       isParsing: Boolean,
       forTimestampNTZ: Boolean = false): TimestampFormatter = {
     val formatter = if (SqlApiConf.get.legacyTimeParserPolicy == LEGACY && !forTimestampNTZ) {
-      getLegacyFormatter(format.getOrElse(defaultPattern), zoneId, locale, legacyFormat)
+      getLegacyFormatter(format.getOrElse(defaultPattern()), zoneId, locale, legacyFormat)
     } else {
       format
         .map(new Iso8601TimestampFormatter(_, zoneId, locale, legacyFormat, isParsing))
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index f9b0837..0469fb2 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -322,7 +322,7 @@
       RewriteUpdateTable ::
       RewriteMergeIntoTable ::
       BindParameters ::
-      typeCoercionRules ++
+      typeCoercionRules() ++
       Seq(
         ResolveWithCTE,
         ExtractDistributedSequenceID) ++
@@ -1400,7 +1400,7 @@
                 cast.setTagValue(Cast.BY_TABLE_INSERTION, ())
                 Some(Alias(cast, col.name)())
               case _ if queryColumns.hasNext =>
-                Some(queryColumns.next)
+                Some(queryColumns.next())
               case _ =>
                 None
             }
@@ -2343,13 +2343,13 @@
 
           u.filter match {
             case Some(filter) if !filter.deterministic =>
-              throw QueryCompilationErrors.nonDeterministicFilterInAggregateError
+              throw QueryCompilationErrors.nonDeterministicFilterInAggregateError()
             case Some(filter) if filter.dataType != BooleanType =>
-              throw QueryCompilationErrors.nonBooleanFilterInAggregateError
+              throw QueryCompilationErrors.nonBooleanFilterInAggregateError()
             case Some(filter) if filter.exists(_.isInstanceOf[AggregateExpression]) =>
-              throw QueryCompilationErrors.aggregateInAggregateFilterError
+              throw QueryCompilationErrors.aggregateInAggregateFilterError()
             case Some(filter) if filter.exists(_.isInstanceOf[WindowExpression]) =>
-              throw QueryCompilationErrors.windowFunctionInAggregateFilterError
+              throw QueryCompilationErrors.windowFunctionInAggregateFilterError()
             case _ =>
           }
           if (u.ignoreNulls) {
@@ -3063,7 +3063,7 @@
             wsc.copy(partitionSpec = newPartitionSpec, orderSpec = newOrderSpec)
 
           case WindowExpression(ae: AggregateExpression, _) if ae.filter.isDefined =>
-            throw QueryCompilationErrors.windowAggregateFunctionWithFilterNotSupportedError
+            throw QueryCompilationErrors.windowAggregateFunctionWithFilterNotSupportedError()
 
           // Extract Windowed AggregateExpression
           case we @ WindowExpression(
@@ -3076,7 +3076,7 @@
             WindowExpression(newAgg, spec)
 
           case AggregateExpression(aggFunc, _, _, _, _) if hasWindowFunction(aggFunc.children) =>
-            throw QueryCompilationErrors.windowFunctionInsideAggregateFunctionNotAllowedError
+            throw QueryCompilationErrors.windowFunctionInsideAggregateFunctionNotAllowedError()
 
           // Extracts AggregateExpression. For example, for SUM(x) - Sum(y) OVER (...),
           // we need to extract SUM(x).
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/InMemoryCatalog.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/InMemoryCatalog.scala
index 90e8242..a9bbda5 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/InMemoryCatalog.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/InMemoryCatalog.scala
@@ -126,7 +126,7 @@
             dbDefinition, e)
       }
       val newDb = dbDefinition.copy(
-        properties = dbDefinition.properties ++ Map(PROP_OWNER -> Utils.getCurrentUserName))
+        properties = dbDefinition.properties ++ Map(PROP_OWNER -> Utils.getCurrentUserName()))
       catalog.put(dbDefinition.name, new DatabaseDesc(newDb))
     }
   }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala
index 392c911..f48ff23 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala
@@ -370,7 +370,7 @@
       validateLocation: Boolean = true): Unit = {
     val isExternal = tableDefinition.tableType == CatalogTableType.EXTERNAL
     if (isExternal && tableDefinition.storage.locationUri.isEmpty) {
-      throw QueryCompilationErrors.createExternalTableWithoutLocationError
+      throw QueryCompilationErrors.createExternalTableWithoutLocationError()
     }
 
     val qualifiedIdent = qualifyIdentifier(tableDefinition.identifier)
@@ -1124,7 +1124,7 @@
    *      updated.
    */
   def refreshTable(name: TableIdentifier): Unit = synchronized {
-    getLocalOrGlobalTempView(name).map(_.refresh).getOrElse {
+    getLocalOrGlobalTempView(name).map(_.refresh()).getOrElse {
       val qualifiedIdent = qualifyIdentifier(name)
       val qualifiedTableName = QualifiedTableName(qualifiedIdent.database.get, qualifiedIdent.table)
       tableRelationCache.invalidate(qualifiedTableName)
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExprUtils.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExprUtils.scala
index 29c9605..41071d0 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExprUtils.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ExprUtils.scala
@@ -65,7 +65,7 @@
     case m: CreateMap =>
       throw QueryCompilationErrors.keyValueInMapNotStringError(m)
     case _ =>
-      throw QueryCompilationErrors.nonMapFunctionNotAllowedError
+      throw QueryCompilationErrors.nonMapFunctionNotAllowedError()
   }
 
   /**
@@ -78,7 +78,7 @@
     schema.getFieldIndex(columnNameOfCorruptRecord).foreach { corruptFieldIndex =>
       val f = schema(corruptFieldIndex)
       if (f.dataType != StringType || !f.nullable) {
-        throw QueryCompilationErrors.invalidFieldTypeForCorruptRecordError
+        throw QueryCompilationErrors.invalidFieldTypeForCorruptRecordError()
       }
     }
   }
@@ -93,7 +93,7 @@
         val pos = new ParsePosition(0)
         val result = decimalFormat.parse(s, pos).asInstanceOf[java.math.BigDecimal]
         if (pos.getIndex() != s.length() || pos.getErrorIndex() != -1) {
-          throw QueryExecutionErrors.cannotParseDecimalError
+          throw QueryExecutionErrors.cannotParseDecimalError()
         } else {
           result
         }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ToStringBase.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ToStringBase.scala
index 1eac386..43bf845 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ToStringBase.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ToStringBase.scala
@@ -66,7 +66,7 @@
       acceptAny[ArrayData](array => {
         val builder = new UTF8StringBuilder
         builder.append("[")
-        if (array.numElements > 0) {
+        if (array.numElements() > 0) {
           val toUTF8String = castToString(et)
           if (array.isNullAt(0)) {
             if (nullString.nonEmpty) builder.append(nullString)
@@ -74,7 +74,7 @@
             builder.append(toUTF8String(array.get(0, et)).asInstanceOf[UTF8String])
           }
           var i = 1
-          while (i < array.numElements) {
+          while (i < array.numElements()) {
             builder.append(",")
             if (array.isNullAt(i)) {
               if (nullString.nonEmpty) builder.append(" " + nullString)
@@ -92,7 +92,7 @@
       acceptAny[MapData](map => {
         val builder = new UTF8StringBuilder
         builder.append(leftBracket)
-        if (map.numElements > 0) {
+        if (map.numElements() > 0) {
           val keyArray = map.keyArray()
           val valueArray = map.valueArray()
           val keyToUTF8String = castToString(kt)
@@ -106,7 +106,7 @@
             builder.append(valueToUTF8String(valueArray.get(0, vt)).asInstanceOf[UTF8String])
           }
           var i = 1
-          while (i < map.numElements) {
+          while (i < map.numElements()) {
             builder.append(", ")
             builder.append(keyToUTF8String(keyArray.get(i, kt)).asInstanceOf[UTF8String])
             builder.append(" ->")
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/HyperLogLogPlusPlus.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/HyperLogLogPlusPlus.scala
index bffec27..f304b43 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/HyperLogLogPlusPlus.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/HyperLogLogPlusPlus.scala
@@ -149,6 +149,6 @@
     case Literal(d: Double, DoubleType) => d
     case Literal(dec: Decimal, _) => dec.toDouble
     case _ =>
-      throw QueryCompilationErrors.secondArgumentNotDoubleLiteralError
+      throw QueryCompilationErrors.secondArgumentNotDoubleLiteralError()
   }
 }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/collect.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/collect.scala
index d0d4ca6..bb3460e 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/collect.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/collect.scala
@@ -170,7 +170,7 @@
   override def eval(buffer: mutable.HashSet[Any]): Any = {
     val array = child.dataType match {
       case BinaryType =>
-        buffer.iterator.map(_.asInstanceOf[ArrayData].toByteArray).toArray
+        buffer.iterator.map(_.asInstanceOf[ArrayData].toByteArray()).toArray
       case _ => buffer.toArray
     }
     new GenericArrayData(array)
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
index 6b54853..3595e43 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
@@ -502,7 +502,7 @@
       inlineToOuterClass: Boolean): NewFunctionSpec = {
     val (className, classInstance) = if (inlineToOuterClass) {
       outerClassName -> ""
-    } else if (currClassSize > GENERATED_CLASS_SIZE_THRESHOLD) {
+    } else if (currClassSize() > GENERATED_CLASS_SIZE_THRESHOLD) {
       val className = freshName("NestedClass")
       val classInstance = freshName("nestedClassInstance")
 
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/javaCode.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/javaCode.scala
index 3651dc4..552c179 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/javaCode.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/javaCode.scala
@@ -255,19 +255,19 @@
     val inputs = args.iterator
     val buf = new StringBuilder(Block.CODE_BLOCK_BUFFER_LENGTH)
 
-    buf.append(StringContext.treatEscapes(strings.next))
+    buf.append(StringContext.treatEscapes(strings.next()))
     while (strings.hasNext) {
-      val input = inputs.next
+      val input = inputs.next()
       input match {
         case _: ExprValue | _: CodeBlock =>
           codeParts += buf.toString
-          buf.clear
+          buf.clear()
           blockInputs += input.asInstanceOf[JavaCode]
         case EmptyBlock =>
         case _ =>
           buf.append(input)
       }
-      buf.append(StringContext.treatEscapes(strings.next))
+      buf.append(StringContext.treatEscapes(strings.next()))
     }
     codeParts += buf.toString
 
@@ -291,10 +291,10 @@
     val strings = codeParts.iterator
     val inputs = blockInputs.iterator
     val buf = new StringBuilder(Block.CODE_BLOCK_BUFFER_LENGTH)
-    buf.append(strings.next)
+    buf.append(strings.next())
     while (strings.hasNext) {
-      buf.append(inputs.next)
-      buf.append(strings.next)
+      buf.append(inputs.next())
+      buf.append(strings.next())
     }
     buf.toString
   }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeExtractors.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeExtractors.scala
index e22af21..3885a5b 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeExtractors.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/complexTypeExtractors.scala
@@ -268,7 +268,7 @@
     if (index >= baseValue.numElements() || index < 0) {
       if (failOnError) {
         throw QueryExecutionErrors.invalidArrayIndexError(
-          index, baseValue.numElements, getContextOrNull())
+          index, baseValue.numElements(), getContextOrNull())
       } else {
         null
       }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
index 30a6bec..50a9dbf 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
@@ -49,7 +49,7 @@
     childrenResolved && checkInputDataTypes().isSuccess && timeZoneId.isDefined
 
   final override val nodePatterns: Seq[TreePattern] =
-    Seq(TIME_ZONE_AWARE_EXPRESSION) ++ nodePatternsInternal
+    Seq(TIME_ZONE_AWARE_EXPRESSION) ++ nodePatternsInternal()
 
   // Subclasses can override this function to provide more TreePatterns.
   def nodePatternsInternal(): Seq[TreePattern] = Seq()
@@ -1017,7 +1017,7 @@
     copy(timeZoneId = Option(timeZoneId))
 
   def this(time: Expression) = {
-    this(time, Literal(TimestampFormatter.defaultPattern))
+    this(time, Literal(TimestampFormatter.defaultPattern()))
   }
 
   override def prettyName: String = "to_unix_timestamp"
@@ -1073,7 +1073,7 @@
     copy(timeZoneId = Option(timeZoneId))
 
   def this(time: Expression) = {
-    this(time, Literal(TimestampFormatter.defaultPattern))
+    this(time, Literal(TimestampFormatter.defaultPattern()))
   }
 
   def this() = {
@@ -1409,7 +1409,7 @@
   override def prettyName: String = "from_unixtime"
 
   def this(unix: Expression) = {
-    this(unix, Literal(TimestampFormatter.defaultPattern))
+    this(unix, Literal(TimestampFormatter.defaultPattern()))
   }
 
   override def dataType: DataType = StringType
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/higherOrderFunctions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/higherOrderFunctions.scala
index 4df6a5e..3750a92 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/higherOrderFunctions.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/higherOrderFunctions.scala
@@ -336,9 +336,9 @@
   override def nullSafeEval(inputRow: InternalRow, argumentValue: Any): Any = {
     val arr = argumentValue.asInstanceOf[ArrayData]
     val f = functionForEval
-    val result = new GenericArrayData(new Array[Any](arr.numElements))
+    val result = new GenericArrayData(new Array[Any](arr.numElements()))
     var i = 0
-    while (i < arr.numElements) {
+    while (i < arr.numElements()) {
       elementVar.value.set(arr.get(i, elementVar.dataType))
       if (indexVar.isDefined) {
         indexVar.get.value.set(i)
@@ -603,9 +603,9 @@
   override def nullSafeEval(inputRow: InternalRow, argumentValue: Any): Any = {
     val arr = argumentValue.asInstanceOf[ArrayData]
     val f = functionForEval
-    val buffer = new mutable.ArrayBuffer[Any](arr.numElements)
+    val buffer = new mutable.ArrayBuffer[Any](arr.numElements())
     var i = 0
-    while (i < arr.numElements) {
+    while (i < arr.numElements()) {
       elementVar.value.set(arr.get(i, elementVar.dataType))
       if (indexVar.isDefined) {
         indexVar.get.value.set(i)
@@ -683,7 +683,7 @@
     var exists = false
     var foundNull = false
     var i = 0
-    while (i < arr.numElements && !exists) {
+    while (i < arr.numElements() && !exists) {
       elementVar.value.set(arr.get(i, elementVar.dataType))
       val ret = f.eval(inputRow)
       if (ret == null) {
@@ -764,7 +764,7 @@
     var forall = true
     var foundNull = false
     var i = 0
-    while (i < arr.numElements && forall) {
+    while (i < arr.numElements() && forall) {
       elementVar.value.set(arr.get(i, elementVar.dataType))
       val ret = f.eval(inputRow)
       if (ret == null) {
@@ -934,9 +934,9 @@
 
   override def nullSafeEval(inputRow: InternalRow, argumentValue: Any): Any = {
     val map = argumentValue.asInstanceOf[MapData]
-    val resultKeys = new GenericArrayData(new Array[Any](map.numElements))
+    val resultKeys = new GenericArrayData(new Array[Any](map.numElements()))
     var i = 0
-    while (i < map.numElements) {
+    while (i < map.numElements()) {
       keyVar.value.set(map.keyArray().get(i, keyVar.dataType))
       valueVar.value.set(map.valueArray().get(i, valueVar.dataType))
       val result = InternalRow.copyValue(functionForEval.eval(inputRow))
@@ -986,9 +986,9 @@
 
   override def nullSafeEval(inputRow: InternalRow, argumentValue: Any): Any = {
     val map = argumentValue.asInstanceOf[MapData]
-    val resultValues = new GenericArrayData(new Array[Any](map.numElements))
+    val resultValues = new GenericArrayData(new Array[Any](map.numElements()))
     var i = 0
-    while (i < map.numElements) {
+    while (i < map.numElements()) {
       keyVar.value.set(map.keyArray().get(i, keyVar.dataType))
       valueVar.value.set(map.valueArray().get(i, valueVar.dataType))
       val v = InternalRow.copyValue(functionForEval.eval(inputRow))
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala
index 038e7ff..c320d98 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathExpressions.scala
@@ -1558,25 +1558,25 @@
       case ByteType if ansiEnabled =>
         MathUtils.withOverflow(
           f = BigDecimal(input1.asInstanceOf[Byte]).setScale(_scale, mode).toByteExact,
-          context = getContextOrNull)
+          context = getContextOrNull())
       case ByteType =>
         BigDecimal(input1.asInstanceOf[Byte]).setScale(_scale, mode).toByte
       case ShortType if ansiEnabled =>
         MathUtils.withOverflow(
           f = BigDecimal(input1.asInstanceOf[Short]).setScale(_scale, mode).toShortExact,
-          context = getContextOrNull)
+          context = getContextOrNull())
       case ShortType =>
         BigDecimal(input1.asInstanceOf[Short]).setScale(_scale, mode).toShort
       case IntegerType if ansiEnabled =>
         MathUtils.withOverflow(
           f = BigDecimal(input1.asInstanceOf[Int]).setScale(_scale, mode).toIntExact,
-          context = getContextOrNull)
+          context = getContextOrNull())
       case IntegerType =>
         BigDecimal(input1.asInstanceOf[Int]).setScale(_scale, mode).toInt
       case LongType if ansiEnabled =>
         MathUtils.withOverflow(
           f = BigDecimal(input1.asInstanceOf[Long]).setScale(_scale, mode).toLongExact,
-          context = getContextOrNull)
+          context = getContextOrNull())
       case LongType =>
         BigDecimal(input1.asInstanceOf[Long]).setScale(_scale, mode).toLong
       case FloatType =>
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/objects/objects.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/objects/objects.scala
index fdebca7..91bd6a6 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/objects/objects.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/objects/objects.scala
@@ -811,7 +811,7 @@
   override lazy val resolved = false
 
   override def dataType: DataType = customCollectionCls.map(ObjectType.apply).getOrElse {
-    throw QueryExecutionErrors.customCollectionClsNotResolvedError
+    throw QueryExecutionErrors.customCollectionClsNotResolvedError()
   }
 
   override protected def withNewChildInternal(newChild: Expression): UnresolvedMapObjects =
@@ -1461,7 +1461,7 @@
             keys(i) = if (key != null) {
               keyConverter.eval(rowWrapper(key))
             } else {
-              throw QueryExecutionErrors.nullAsMapKeyNotAllowedError
+              throw QueryExecutionErrors.nullAsMapKeyNotAllowedError()
             }
             values(i) = if (value != null) {
               valueConverter.eval(rowWrapper(value))
@@ -1483,7 +1483,7 @@
             keys(i) = if (key != null) {
               keyConverter.eval(rowWrapper(key))
             } else {
-              throw QueryExecutionErrors.nullAsMapKeyNotAllowedError
+              throw QueryExecutionErrors.nullAsMapKeyNotAllowedError()
             }
             values(i) = if (value != null) {
               valueConverter.eval(rowWrapper(value))
@@ -1898,7 +1898,7 @@
   override def eval(input: InternalRow): Any = {
     val inputRow = child.eval(input).asInstanceOf[Row]
     if (inputRow == null) {
-      throw QueryExecutionErrors.inputExternalRowCannotBeNullError
+      throw QueryExecutionErrors.inputExternalRowCannotBeNullError()
     }
     if (inputRow.isNullAt(index)) {
       throw QueryExecutionErrors.fieldCannotBeNullError(index, fieldName)
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala
index 6aa949b..eff63bf 100755
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala
@@ -2565,10 +2565,10 @@
         var default: Expression = Literal.create(null, StringType)
         val branches = ArrayBuffer.empty[(Expression, Expression)]
         while (itr.hasNext) {
-          val search = itr.next
+          val search = itr.next()
           if (itr.hasNext) {
             val condition = EqualNullSafe(input, search)
-            branches += ((condition, itr.next))
+            branches += ((condition, itr.next()))
           } else {
             default = search
           }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/subquery.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/subquery.scala
index 9d8b5de..79388cf 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/subquery.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/subquery.scala
@@ -41,7 +41,7 @@
     bits
   }
 
-  final override val nodePatterns: Seq[TreePattern] = Seq(PLAN_EXPRESSION) ++ nodePatternsInternal
+  final override val nodePatterns: Seq[TreePattern] = Seq(PLAN_EXPRESSION) ++ nodePatternsInternal()
 
   override lazy val deterministic: Boolean = children.forall(_.deterministic) &&
     plan.deterministic
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala
index a570962..ca3c9b0 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/windowExpressions.scala
@@ -62,7 +62,7 @@
       checkInputDataTypes().isSuccess
 
   override def nullable: Boolean = true
-  override def dataType: DataType = throw QueryCompilationErrors.dataTypeOperationUnsupportedError
+  override def dataType: DataType = throw QueryCompilationErrors.dataTypeOperationUnsupportedError()
 
   override def checkInputDataTypes(): TypeCheckResult = {
     frameSpecification match {
@@ -182,7 +182,7 @@
  * Represents a window frame.
  */
 sealed trait WindowFrame extends Expression with Unevaluable {
-  override def dataType: DataType = throw QueryCompilationErrors.dataTypeOperationUnsupportedError
+  override def dataType: DataType = throw QueryCompilationErrors.dataTypeOperationUnsupportedError()
   override def nullable: Boolean = false
 }
 
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JsonFilters.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JsonFilters.scala
index 0d5974a..01de1e3 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JsonFilters.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JsonFilters.scala
@@ -152,5 +152,5 @@
   /**
    * Reset states of all predicates by re-initializing reference counters.
    */
-  override def reset(): Unit = predicates.foreach(_.foreach(_.reset))
+  override def reset(): Unit = predicates.foreach(_.foreach(_.reset()))
 }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala
index 7e0aafc..2b5f542 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala
@@ -1450,7 +1450,7 @@
     val seed = if (ctx.seed != null) {
       ctx.seed.getText.toLong
     } else {
-      (math.random * 1000).toLong
+      (math.random() * 1000).toLong
     }
 
     ctx.sampleMethod() match {
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
index aee4790..36bdc4c 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
@@ -67,7 +67,7 @@
     // Propagate expressions' pattern bits
     val exprIterator = expressions.iterator
     while (exprIterator.hasNext) {
-      bits.union(exprIterator.next.treePatternBits)
+      bits.union(exprIterator.next().treePatternBits)
     }
     bits
   }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
index fbc4e41..4290a24 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
@@ -1332,9 +1332,9 @@
     // grouping expression or null, so here we create new instance of it.
     val output = if (hasDuplicateGroupingSets) {
       val gpos = AttributeReference("_gen_grouping_pos", IntegerType, false)()
-      child.output ++ groupByAttrs.map(_.newInstance) :+ gid :+ gpos
+      child.output ++ groupByAttrs.map(_.newInstance()) :+ gid :+ gpos
     } else {
-      child.output ++ groupByAttrs.map(_.newInstance) :+ gid
+      child.output ++ groupByAttrs.map(_.newInstance()) :+ gid
     }
     Expand(projections, output, Project(child.output ++ groupByAliases, child))
   }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleExecutor.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleExecutor.scala
index 9d29ca1..d5cd5a9 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleExecutor.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/rules/RuleExecutor.scala
@@ -63,7 +63,7 @@
            """.stripMargin
         }
 
-        logBasedOnLevel(message)
+        logBasedOnLevel(message())
       }
     }
   }
@@ -81,7 +81,7 @@
         }
       }
 
-      logBasedOnLevel(message)
+      logBasedOnLevel(message())
     }
   }
 
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreePatternBits.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreePatternBits.scala
index b133630..ee4ddef 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreePatternBits.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreePatternBits.scala
@@ -39,7 +39,7 @@
   final def containsAllPatterns(patterns: TreePattern*): Boolean = {
     val iterator = patterns.iterator
     while (iterator.hasNext) {
-      if (!containsPattern(iterator.next)) {
+      if (!containsPattern(iterator.next())) {
         return false
       }
     }
@@ -53,7 +53,7 @@
   final def containsAnyPattern(patterns: TreePattern*): Boolean = {
     val iterator = patterns.iterator
     while (iterator.hasNext) {
-      if (containsPattern(iterator.next)) {
+      if (containsPattern(iterator.next())) {
         return true
       }
     }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/package.scala
index 3646c70..28ae343 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/package.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/package.scala
@@ -46,6 +46,6 @@
       case _ => false
     }
 
-    override def hashCode: Int = if (obj == null) 0 else obj.hashCode
+    override def hashCode: Int = if (obj == null) 0 else obj.hashCode()
   }
 }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/StringUtils.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/StringUtils.scala
index f6d76bd..f94a065 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/StringUtils.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/StringUtils.scala
@@ -46,9 +46,9 @@
     val out = new StringBuilder()
 
     while (in.hasNext) {
-      in.next match {
+      in.next() match {
         case c1 if c1 == escapeChar && in.hasNext =>
-          val c = in.next
+          val c = in.next()
           c match {
             case '_' | '%' => out ++= Pattern.quote(Character.toString(c))
             case c if c == escapeChar => out ++= Pattern.quote(Character.toString(c))
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Implicits.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Implicits.scala
index 5557957..8843a9f 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Implicits.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Implicits.scala
@@ -64,7 +64,7 @@
 
         case BucketTransform(numBuckets, col, sortCol) =>
           if (bucketSpec.nonEmpty) {
-            throw QueryExecutionErrors.unsupportedMultipleBucketTransformsError
+            throw QueryExecutionErrors.unsupportedMultipleBucketTransformsError()
           }
           if (sortCol.isEmpty) {
             bucketSpec = Some(BucketSpec(numBuckets, col.map(_.fieldNames.mkString(".")), Nil))
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Util.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Util.scala
index f0f02c1..e51d650 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Util.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Util.scala
@@ -215,7 +215,7 @@
             if (update.newDefaultValue().nonEmpty) {
               Some(field.withCurrentDefaultValue(update.newDefaultValue()))
             } else {
-              Some(field.clearCurrentDefaultValue)
+              Some(field.clearCurrentDefaultValue())
             })
 
         case delete: DeleteColumn =>
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/util/SQLOpenHashSet.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/util/SQLOpenHashSet.scala
index ee4dd54..10023c2 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/util/SQLOpenHashSet.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/util/SQLOpenHashSet.scala
@@ -68,7 +68,7 @@
       handleNull: () => Unit): (ArrayData, Int) => Unit = {
     (array: ArrayData, index: Int) =>
       if (array.isNullAt(index)) {
-        if (!hashSet.containsNull) {
+        if (!hashSet.containsNull()) {
           hashSet.addNull()
           handleNull()
         }
@@ -126,7 +126,7 @@
     }
     (value: Any) =>
       if (isNaN(value)) {
-        if (!hashSet.containsNaN) {
+        if (!hashSet.containsNaN()) {
           hashSet.addNaN()
           handleNaN(valueNaN)
         }
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
index e338a5e..e792bd6 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala
@@ -1466,7 +1466,7 @@
       Iterator.empty
     }
 
-    implicit val intEncoder = ExpressionEncoder[Int]
+    implicit val intEncoder = ExpressionEncoder[Int]()
 
     val left = testRelation2.select($"e").analyze
     val right = testRelation3.select($"e").analyze
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/UnsupportedOperationsSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/UnsupportedOperationsSuite.scala
index 32c9a3a..02d70c6 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/UnsupportedOperationsSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/UnsupportedOperationsSuite.scala
@@ -683,7 +683,7 @@
     def func(k: Int, left: Iterator[Int], right: Iterator[Int]): Iterator[Int] = {
       Iterator.empty
     }
-    implicit val intEncoder = ExpressionEncoder[Int]
+    implicit val intEncoder = ExpressionEncoder[Int]()
 
     left.cogroup[Int, Int, Int, Int](
       right,
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderErrorMessageSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderErrorMessageSuite.scala
index b77cc4c..2d61f9f 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderErrorMessageSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderErrorMessageSuite.scala
@@ -54,7 +54,7 @@
   test("nice error message for missing encoder") {
     checkError(
       exception = intercept[
-        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable1]),
+        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable1]()),
       errorClass = "ENCODER_NOT_FOUND",
       parameters = Map(
         "typeName" -> "org.apache.spark.sql.catalyst.encoders.NonEncodable",
@@ -63,7 +63,7 @@
 
     checkError(
       exception = intercept[
-        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable2]),
+        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable2]()),
       errorClass = "ENCODER_NOT_FOUND",
       parameters = Map(
         "typeName" -> "org.apache.spark.sql.catalyst.encoders.NonEncodable",
@@ -72,7 +72,7 @@
 
     checkError(
       exception = intercept[
-        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable3]),
+        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable3]()),
       errorClass = "ENCODER_NOT_FOUND",
       parameters = Map(
         "typeName" -> "org.apache.spark.sql.catalyst.encoders.NonEncodable",
@@ -81,7 +81,7 @@
 
     checkError(
       exception = intercept[
-        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable4]),
+        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable4]()),
       errorClass = "ENCODER_NOT_FOUND",
       parameters = Map(
         "typeName" -> "org.apache.spark.sql.catalyst.encoders.NonEncodable",
@@ -90,7 +90,7 @@
 
     checkError(
       exception = intercept[
-        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable5]),
+        SparkUnsupportedOperationException](ExpressionEncoder[ComplexNonEncodable5]()),
       errorClass = "ENCODER_NOT_FOUND",
       parameters = Map(
         "typeName" -> "org.apache.spark.sql.catalyst.encoders.NonEncodable",
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderResolutionSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderResolutionSuite.scala
index 7f54987..82238de 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderResolutionSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/EncoderResolutionSuite.scala
@@ -52,7 +52,7 @@
   }
 
   test("real type doesn't match encoder schema but they are compatible: product") {
-    val encoder = ExpressionEncoder[StringLongClass]
+    val encoder = ExpressionEncoder[StringLongClass]()
 
     // int type can be up cast to long type
     val attrs1 = Seq($"a".string, $"b".int)
@@ -64,28 +64,28 @@
   }
 
   test("real type doesn't match encoder schema but they are compatible: nested product") {
-    val encoder = ExpressionEncoder[ComplexClass]
+    val encoder = ExpressionEncoder[ComplexClass]()
     val attrs = Seq($"a".int, $"b".struct($"a".int, $"b".long))
     testFromRow(encoder, attrs, InternalRow(1, InternalRow(2, 3L)))
   }
 
   test("real type doesn't match encoder schema but they are compatible: tupled encoder") {
     val encoder = ExpressionEncoder.tuple(
-      ExpressionEncoder[StringLongClass],
-      ExpressionEncoder[Long])
+      ExpressionEncoder[StringLongClass](),
+      ExpressionEncoder[Long]())
     val attrs = Seq($"a".struct($"a".string, $"b".byte), $"b".int)
     testFromRow(encoder, attrs, InternalRow(InternalRow(str, 1.toByte), 2))
   }
 
   test("real type doesn't match encoder schema but they are compatible: primitive array") {
-    val encoder = ExpressionEncoder[PrimitiveArrayClass]
+    val encoder = ExpressionEncoder[PrimitiveArrayClass]()
     val attrs = Seq($"arr".array(IntegerType))
     val array = new GenericArrayData(Array(1, 2, 3))
     testFromRow(encoder, attrs, InternalRow(array))
   }
 
   test("the real type is not compatible with encoder schema: primitive array") {
-    val encoder = ExpressionEncoder[PrimitiveArrayClass]
+    val encoder = ExpressionEncoder[PrimitiveArrayClass]()
     val attrs = Seq($"arr".array(StringType))
     checkError(
       exception = intercept[AnalysisException](encoder.resolveAndBind(attrs)),
@@ -103,14 +103,14 @@
   }
 
   test("real type doesn't match encoder schema but they are compatible: array") {
-    val encoder = ExpressionEncoder[ArrayClass]
+    val encoder = ExpressionEncoder[ArrayClass]()
     val attrs = Seq($"arr".array(new StructType().add("a", "int").add("b", "int").add("c", "int")))
     val array = new GenericArrayData(Array(InternalRow(1, 2, 3)))
     testFromRow(encoder, attrs, InternalRow(array))
   }
 
   test("real type doesn't match encoder schema but they are compatible: nested array") {
-    val encoder = ExpressionEncoder[NestedArrayClass]
+    val encoder = ExpressionEncoder[NestedArrayClass]()
     val et = new StructType().add("arr", ArrayType(
       new StructType().add("a", "int").add("b", "int").add("c", "int")))
     val attrs = Seq($"nestedArr".array(et))
@@ -120,7 +120,7 @@
   }
 
   test("the real type is not compatible with encoder schema: non-array field") {
-    val encoder = ExpressionEncoder[ArrayClass]
+    val encoder = ExpressionEncoder[ArrayClass]()
     val attrs = Seq($"arr".int)
     checkError(
       exception = intercept[AnalysisException](encoder.resolveAndBind(attrs)),
@@ -129,7 +129,7 @@
   }
 
   test("the real type is not compatible with encoder schema: array element type") {
-    val encoder = ExpressionEncoder[ArrayClass]
+    val encoder = ExpressionEncoder[ArrayClass]()
     val attrs = Seq($"arr".array(new StructType().add("c", "int")))
     checkError(
       exception = intercept[AnalysisException](encoder.resolveAndBind(attrs)),
@@ -138,7 +138,7 @@
   }
 
   test("the real type is not compatible with encoder schema: nested array element type") {
-    val encoder = ExpressionEncoder[NestedArrayClass]
+    val encoder = ExpressionEncoder[NestedArrayClass]()
 
     withClue("inner element is not array") {
       val attrs = Seq($"nestedArr".array(new StructType().add("arr", "int")))
@@ -159,7 +159,7 @@
   }
 
   test("nullability of array type element should not fail analysis") {
-    val encoder = ExpressionEncoder[Seq[Int]]
+    val encoder = ExpressionEncoder[Seq[Int]]()
     val attrs = $"a".array(IntegerType) :: Nil
 
     // It should pass analysis
@@ -176,7 +176,7 @@
   }
 
   test("the real number of fields doesn't match encoder schema: tuple encoder") {
-    val encoder = ExpressionEncoder[(String, Long)]
+    val encoder = ExpressionEncoder[(String, Long)]()
 
     {
       val attrs = Seq($"a".string, $"b".long, $"c".int)
@@ -198,7 +198,7 @@
   }
 
   test("the real number of fields doesn't match encoder schema: nested tuple encoder") {
-    val encoder = ExpressionEncoder[(String, (Long, String))]
+    val encoder = ExpressionEncoder[(String, (Long, String))]()
 
     {
       val attrs = Seq($"a".string, $"b".struct($"x".long, $"y".string, $"z".int))
@@ -220,13 +220,13 @@
   }
 
   test("nested case class can have different number of fields from the real schema") {
-    val encoder = ExpressionEncoder[(String, StringIntClass)]
+    val encoder = ExpressionEncoder[(String, StringIntClass)]()
     val attrs = Seq($"a".string, $"b".struct($"a".string, $"b".int, $"c".int))
     encoder.resolveAndBind(attrs)
   }
 
   test("SPARK-28497: complex type is not compatible with string encoder schema") {
-    val encoder = ExpressionEncoder[String]
+    val encoder = ExpressionEncoder[String]()
 
     Seq($"a".struct($"x".long), $"a".array(StringType), Symbol("a").map(StringType, StringType))
       .foreach { attr =>
@@ -246,7 +246,7 @@
 
   test("throw exception if real type is not compatible with encoder schema") {
     val e1 = intercept[AnalysisException] {
-      ExpressionEncoder[StringIntClass].resolveAndBind(Seq($"a".string, $"b".long))
+      ExpressionEncoder[StringIntClass]().resolveAndBind(Seq($"a".string, $"b".long))
     }
     checkError(exception = e1,
       errorClass = "CANNOT_UP_CAST_DATATYPE",
@@ -262,7 +262,7 @@
 
     val e2 = intercept[AnalysisException] {
       val structType = new StructType().add("a", StringType).add("b", DecimalType.SYSTEM_DEFAULT)
-      ExpressionEncoder[ComplexClass].resolveAndBind(Seq($"a".long, $"b".struct(structType)))
+      ExpressionEncoder[ComplexClass]().resolveAndBind(Seq($"a".long, $"b".struct(structType)))
     }
 
     checkError(exception = e2,
@@ -280,7 +280,7 @@
   }
 
   test("SPARK-31750: eliminate UpCast if child's dataType is DecimalType") {
-    val encoder = ExpressionEncoder[Seq[BigDecimal]]
+    val encoder = ExpressionEncoder[Seq[BigDecimal]]()
     val attr = Seq(AttributeReference("a", ArrayType(DecimalType(38, 0)))())
     // Before SPARK-31750, it will fail because Decimal(38, 0) can not be casted to Decimal(38, 18)
     testFromRow(encoder, attr, InternalRow(ArrayData.toArrayData(Array(Decimal(1.0)))))
@@ -302,8 +302,8 @@
 
 
   private def castSuccess[T: TypeTag, U: TypeTag]: Unit = {
-    val from = ExpressionEncoder[T]
-    val to = ExpressionEncoder[U]
+    val from = ExpressionEncoder[T]()
+    val to = ExpressionEncoder[U]()
     val catalystType = from.schema.head.dataType.simpleString
     test(s"cast from $catalystType to ${implicitly[TypeTag[U]].tpe} should success") {
       to.resolveAndBind(toAttributes(from.schema))
@@ -311,8 +311,8 @@
   }
 
   private def castFail[T: TypeTag, U: TypeTag]: Unit = {
-    val from = ExpressionEncoder[T]
-    val to = ExpressionEncoder[U]
+    val from = ExpressionEncoder[T]()
+    val to = ExpressionEncoder[U]()
     val catalystType = from.schema.head.dataType.simpleString
     test(s"cast from $catalystType to ${implicitly[TypeTag[U]].tpe} should fail") {
       intercept[AnalysisException](to.resolveAndBind(toAttributes(from.schema)))
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoderSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoderSuite.scala
index 8373f53..1c77b87 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoderSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoderSuite.scala
@@ -390,28 +390,28 @@
   encodeDecodeTest(
     1 -> 10L,
     "tuple with 2 flat encoders")(
-    ExpressionEncoder.tuple(ExpressionEncoder[Int], ExpressionEncoder[Long]))
+    ExpressionEncoder.tuple(ExpressionEncoder[Int](), ExpressionEncoder[Long]()))
 
   encodeDecodeTest(
     (PrimitiveData(1, 1, 1, 1, 1, 1, true), (3, 30L)),
     "tuple with 2 product encoders")(
-    ExpressionEncoder.tuple(ExpressionEncoder[PrimitiveData], ExpressionEncoder[(Int, Long)]))
+    ExpressionEncoder.tuple(ExpressionEncoder[PrimitiveData](), ExpressionEncoder[(Int, Long)]()))
 
   encodeDecodeTest(
     (PrimitiveData(1, 1, 1, 1, 1, 1, true), 3),
     "tuple with flat encoder and product encoder")(
-    ExpressionEncoder.tuple(ExpressionEncoder[PrimitiveData], ExpressionEncoder[Int]))
+    ExpressionEncoder.tuple(ExpressionEncoder[PrimitiveData](), ExpressionEncoder[Int]()))
 
   encodeDecodeTest(
     (3, PrimitiveData(1, 1, 1, 1, 1, 1, true)),
     "tuple with product encoder and flat encoder")(
-    ExpressionEncoder.tuple(ExpressionEncoder[Int], ExpressionEncoder[PrimitiveData]))
+    ExpressionEncoder.tuple(ExpressionEncoder[Int](), ExpressionEncoder[PrimitiveData]()))
 
   encodeDecodeTest(
     (1, (10, 100L)),
     "nested tuple encoder") {
-    val intEnc = ExpressionEncoder[Int]
-    val longEnc = ExpressionEncoder[Long]
+    val intEnc = ExpressionEncoder[Int]()
+    val longEnc = ExpressionEncoder[Long]()
     ExpressionEncoder.tuple(intEnc, ExpressionEncoder.tuple(intEnc, longEnc))
   }
 
@@ -516,7 +516,7 @@
 
     // test for nested product encoders
     {
-      val schema = ExpressionEncoder[(Int, (String, Int))].schema
+      val schema = ExpressionEncoder[(Int, (String, Int))]().schema
       assert(schema(0).nullable === false)
       assert(schema(1).nullable)
       assert(schema(1).dataType.asInstanceOf[StructType](0).nullable)
@@ -526,8 +526,8 @@
     // test for tupled encoders
     {
       val schema = ExpressionEncoder.tuple(
-        ExpressionEncoder[Int],
-        ExpressionEncoder[(String, Int)]).schema
+        ExpressionEncoder[Int](),
+        ExpressionEncoder[(String, Int)]()).schema
       assert(schema(0).nullable === false)
       assert(schema(1).nullable)
       assert(schema(1).dataType.asInstanceOf[StructType](0).nullable)
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala
index 7ddb92c..b71b426 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala
@@ -72,7 +72,7 @@
   }
 
   private def prepareEvaluation(expression: Expression): Expression = {
-    val serializer = new JavaSerializer(new SparkConf()).newInstance
+    val serializer = new JavaSerializer(new SparkConf()).newInstance()
     val resolver = ResolveTimeZone
     val expr = resolver.resolveTimeZones(expression)
     assert(expr.resolved)
@@ -123,11 +123,11 @@
             result.get(i, f.dataType), expected.get(i, f.dataType), f.dataType, f.nullable)
         }
       case (result: ArrayData, expected: ArrayData) =>
-        result.numElements == expected.numElements && {
+        result.numElements() == expected.numElements() && {
           val ArrayType(et, cn) = dataType.asInstanceOf[ArrayType]
           var isSame = true
           var i = 0
-          while (isSame && i < result.numElements) {
+          while (isSame && i < result.numElements()) {
             isSame = checkResult(result.get(i, et), expected.get(i, et), et, cn)
             i += 1
           }
@@ -135,8 +135,8 @@
         }
       case (result: MapData, expected: MapData) =>
         val MapType(kt, vt, vcn) = dataType.asInstanceOf[MapType]
-        checkResult(result.keyArray, expected.keyArray, ArrayType(kt, false), false) &&
-          checkResult(result.valueArray, expected.valueArray, ArrayType(vt, vcn), false)
+        checkResult(result.keyArray(), expected.keyArray(), ArrayType(kt, false), false) &&
+          checkResult(result.valueArray(), expected.valueArray(), ArrayType(vt, vcn), false)
       case (result: Double, expected: Double) =>
         if (expected.isNaN) result.isNaN else expected == result
       case (result: Float, expected: Float) =>
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ObjectExpressionsSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ObjectExpressionsSuite.scala
index 3af7cb3..01ecebf 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ObjectExpressionsSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ObjectExpressionsSuite.scala
@@ -107,7 +107,7 @@
 
   test("MapObjects should make copies of unsafe-backed data") {
     // test UnsafeRow-backed data
-    val structEncoder = ExpressionEncoder[Array[Tuple2[java.lang.Integer, java.lang.Integer]]]
+    val structEncoder = ExpressionEncoder[Array[Tuple2[java.lang.Integer, java.lang.Integer]]]()
     val structInputRow = InternalRow.fromSeq(Seq(Array((1, 2), (3, 4))))
     val structExpected = new GenericArrayData(
       Array(InternalRow.fromSeq(Seq(1, 2)), InternalRow.fromSeq(Seq(3, 4))))
@@ -115,7 +115,7 @@
       structEncoder.serializer.head, structExpected, structInputRow)
 
     // test UnsafeArray-backed data
-    val arrayEncoder = ExpressionEncoder[Array[Array[Int]]]
+    val arrayEncoder = ExpressionEncoder[Array[Array[Int]]]()
     val arrayInputRow = InternalRow.fromSeq(Seq(Array(Array(1, 2), Array(3, 4))))
     val arrayExpected = new GenericArrayData(
       Array(new GenericArrayData(Array(1, 2)), new GenericArrayData(Array(3, 4))))
@@ -123,7 +123,7 @@
       arrayEncoder.serializer.head, arrayExpected, arrayInputRow)
 
     // test UnsafeMap-backed data
-    val mapEncoder = ExpressionEncoder[Array[Map[Int, Int]]]
+    val mapEncoder = ExpressionEncoder[Array[Map[Int, Int]]]()
     val mapInputRow = InternalRow.fromSeq(Seq(Array(
       Map(1 -> 100, 2 -> 200), Map(3 -> 300, 4 -> 400))))
     val mapExpected = new GenericArrayData(Seq(
@@ -299,7 +299,7 @@
   // by scala values instead of catalyst values.
   private def checkObjectExprEvaluation(
       expression: => Expression, expected: Any, inputRow: InternalRow = EmptyRow): Unit = {
-    val serializer = new JavaSerializer(new SparkConf()).newInstance
+    val serializer = new JavaSerializer(new SparkConf()).newInstance()
     val resolver = ResolveTimeZone
     val expr = resolver.resolveTimeZones(serializer.deserialize(serializer.serialize(expression)))
     checkEvaluationWithoutCodegen(expr, expected, inputRow)
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/statsEstimation/BasicStatsEstimationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/statsEstimation/BasicStatsEstimationSuite.scala
index 33e521e..db2d8c2 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/statsEstimation/BasicStatsEstimationSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/statsEstimation/BasicStatsEstimationSuite.scala
@@ -232,14 +232,14 @@
   }
 
   test("sample estimation") {
-    val sample = Sample(0.0, 0.5, withReplacement = false, (math.random * 1000).toLong, plan)
+    val sample = Sample(0.0, 0.5, withReplacement = false, (math.random() * 1000).toLong, plan)
     checkStats(sample, Statistics(sizeInBytes = 60, rowCount = Some(5)))
 
     // Child doesn't have rowCount in stats
     val childStats = Statistics(sizeInBytes = 120)
     val childPlan = DummyLogicalPlan(childStats, childStats)
     val sample2 =
-      Sample(0.0, 0.11, withReplacement = false, (math.random * 1000).toLong, childPlan)
+      Sample(0.0, 0.11, withReplacement = false, (math.random() * 1000).toLong, childPlan)
     checkStats(sample2, Statistics(sizeInBytes = 14))
   }
 
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/ArrayDataIndexedSeqSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/ArrayDataIndexedSeqSuite.scala
index 50667c5..d55e672 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/ArrayDataIndexedSeqSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/ArrayDataIndexedSeqSuite.scala
@@ -27,7 +27,7 @@
 
 class ArrayDataIndexedSeqSuite extends SparkFunSuite {
   private def compArray(arrayData: ArrayData, elementDt: DataType, array: Array[Any]): Unit = {
-    assert(arrayData.numElements == array.length)
+    assert(arrayData.numElements() == array.length)
     array.zipWithIndex.map { case (e, i) =>
       if (e != null) {
         elementDt match {
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/TimestampFormatterSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/TimestampFormatterSuite.scala
index d2fc89a..977dde1 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/TimestampFormatterSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/TimestampFormatterSuite.scala
@@ -268,7 +268,7 @@
             withClue(s"zoneId = ${zoneId.getId}") {
               val formatters = LegacyDateFormats.values.toSeq.map { legacyFormat =>
                 TimestampFormatter(
-                  TimestampFormatter.defaultPattern,
+                  TimestampFormatter.defaultPattern(),
                   zoneId,
                   TimestampFormatter.defaultLocale,
                   legacyFormat,
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/UnsafeArraySuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/UnsafeArraySuite.scala
index 1801094..d8db7b5 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/UnsafeArraySuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/UnsafeArraySuite.scala
@@ -73,8 +73,8 @@
   }
 
   private def toUnsafeArray[T: TypeTag](array: Array[T]): ArrayData = {
-    val converted = ExpressionEncoder[Array[T]].createSerializer().apply(array).getArray(0)
-    assert(converted.numElements == array.length)
+    val converted = ExpressionEncoder[Array[T]]().createSerializer().apply(array).getArray(0)
+    assert(converted.numElements() == array.length)
     converted
   }
 
@@ -134,7 +134,7 @@
 
       val unsafeDecimal = ir.getArray(0)
       assert(unsafeDecimal.isInstanceOf[UnsafeArrayData])
-      assert(unsafeDecimal.numElements == decimalArray.length)
+      assert(unsafeDecimal.numElements() == decimalArray.length)
       decimalArray.zipWithIndex.map { case (e, i) =>
         assert(unsafeDecimal.getDecimal(i, e.precision, e.scale).toBigDecimal == e)
       }
@@ -146,7 +146,7 @@
     val ir = encoder.createSerializer().apply(externalRow)
     val unsafeCalendar = ir.getArray(0)
     assert(unsafeCalendar.isInstanceOf[UnsafeArrayData])
-    assert(unsafeCalendar.numElements == calendarintervalArray.length)
+    assert(unsafeCalendar.numElements() == calendarintervalArray.length)
     calendarintervalArray.zipWithIndex.map { case (e, i) =>
       assert(unsafeCalendar.getInterval(i) == e)
     }
@@ -155,7 +155,7 @@
     intMultiDimArray.zipWithIndex.map { case (a, j) =>
       val u = unsafeMultiDimInt.getArray(j)
       assert(u.isInstanceOf[UnsafeArrayData])
-      assert(u.numElements == a.length)
+      assert(u.numElements() == a.length)
       a.zipWithIndex.map { case (e, i) =>
         assert(u.getInt(i) == e)
       }
@@ -165,7 +165,7 @@
     doubleMultiDimArray.zipWithIndex.map { case (a, j) =>
       val u = unsafeMultiDimDouble.getArray(j)
       assert(u.isInstanceOf[UnsafeArrayData])
-      assert(u.numElements == a.length)
+      assert(u.numElements() == a.length)
       a.zipWithIndex.map { case (e, i) =>
         assert(u.getDouble(i) == e)
       }
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryBaseTable.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryBaseTable.scala
index a0a4d8b..7765bc2 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryBaseTable.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryBaseTable.scala
@@ -534,7 +534,7 @@
 
   protected object TruncateAndAppend extends TestBatchWrite {
     override def commit(messages: Array[WriterCommitMessage]): Unit = dataMap.synchronized {
-      dataMap.clear
+      dataMap.clear()
       withData(messages.map(_.asInstanceOf[BufferedRows]))
     }
   }
@@ -572,7 +572,7 @@
   protected object StreamingTruncateAndAppend extends TestStreamingWrite {
     override def commit(epochId: Long, messages: Array[WriterCommitMessage]): Unit = {
       dataMap.synchronized {
-        dataMap.clear
+        dataMap.clear()
         withData(messages.map(_.asInstanceOf[BufferedRows]))
       }
     }
@@ -656,7 +656,7 @@
   private def addMetadata(row: InternalRow): InternalRow = {
     val metadataRow = new GenericInternalRow(metadataColumnNames.map {
       case "index" => index
-      case "_partition" => UTF8String.fromString(partition.keyString)
+      case "_partition" => UTF8String.fromString(partition.keyString())
     }.toArray)
     new JoinedRow(row, metadataRow)
   }
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryTableWithV2Filter.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryTableWithV2Filter.scala
index b4285f31..f4e3d9e 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryTableWithV2Filter.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryTableWithV2Filter.scala
@@ -78,7 +78,7 @@
                 val matchingKeys =
                   p.children().drop(1).map(_.asInstanceOf[LiteralValue[_]].value.toString).toSet
                 data = data.filter(partition => {
-                  val key = partition.asInstanceOf[BufferedRows].keyString
+                  val key = partition.asInstanceOf[BufferedRows].keyString()
                   matchingKeys.contains(key)
                 })
               }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala b/sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala
index 3a6fb10..aa3fe8d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala
@@ -1297,7 +1297,7 @@
   }
 
   private def assertOnDriver(): Unit = {
-    if (TaskContext.get != null) {
+    if (TaskContext.get() != null) {
       // we're accessing it during task execution, fail.
       throw new IllegalStateException(
         "SparkSession should only be created and accessed on the driver.")
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
index 033fe5b..56515ca 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala
@@ -57,7 +57,7 @@
             ident, "ADD COLUMN with qualified column")
         }
         if (!c.nullable) {
-          throw QueryCompilationErrors.addColumnWithV1TableCannotSpecifyNotNullError
+          throw QueryCompilationErrors.addColumnWithV1TableCannotSpecifyNotNullError()
         }
       }
       AlterTableAddColumnsCommand(ident, cols.map(convertToStructField))
@@ -72,7 +72,7 @@
           catalog, ident, "ALTER COLUMN with qualified column")
       }
       if (a.nullable.isDefined) {
-        throw QueryCompilationErrors.alterColumnWithV1TableCannotSpecifyNotNullError
+        throw QueryCompilationErrors.alterColumnWithV1TableCannotSpecifyNotNullError()
       }
       if (a.position.isDefined) {
         throw QueryCompilationErrors.unsupportedTableOperationError(
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GroupedIterator.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GroupedIterator.scala
index 431f021..ccf3258 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GroupedIterator.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GroupedIterator.scala
@@ -94,7 +94,7 @@
    * because we will consume the input data to skip to next group while fetching a new iterator,
    * thus make the previous iterator empty.
    */
-  def hasNext: Boolean = currentIterator != null || fetchNextGroupIterator
+  def hasNext: Boolean = currentIterator != null || fetchNextGroupIterator()
 
   def next(): (InternalRow, Iterator[InternalRow]) = {
     assert(hasNext) // Ensure we have fetched the next iterator.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowConverters.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowConverters.scala
index 404c46a..a0dd939 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowConverters.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowConverters.scala
@@ -219,7 +219,7 @@
       errorOnDuplicatedFieldNames: Boolean): ArrowBatchWithSchemaIterator = {
     new ArrowBatchWithSchemaIterator(
       rowIter, schema, maxRecordsPerBatch, maxEstimatedBatchSize,
-      timeZoneId, errorOnDuplicatedFieldNames, TaskContext.get)
+      timeZoneId, errorOnDuplicatedFieldNames, TaskContext.get())
   }
 
   private[sql] def createEmptyArrowBatch(
@@ -228,7 +228,7 @@
       errorOnDuplicatedFieldNames: Boolean): Array[Byte] = {
     new ArrowBatchWithSchemaIterator(
         Iterator.empty, schema, 0L, 0L,
-        timeZoneId, errorOnDuplicatedFieldNames, TaskContext.get) {
+        timeZoneId, errorOnDuplicatedFieldNames, TaskContext.get()) {
       override def hasNext: Boolean = true
     }.next()
   }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnStats.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnStats.scala
index d2f65b7..1f47673 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnStats.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnStats.scala
@@ -80,7 +80,7 @@
     if (!row.isNullAt(ordinal)) {
       count += 1
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -96,7 +96,7 @@
       val value = row.getBoolean(ordinal)
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -120,7 +120,7 @@
       val value = row.getByte(ordinal)
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -144,7 +144,7 @@
       val value = row.getShort(ordinal)
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -168,7 +168,7 @@
       val value = row.getInt(ordinal)
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -192,7 +192,7 @@
       val value = row.getLong(ordinal)
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -216,7 +216,7 @@
       val value = row.getFloat(ordinal)
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -240,7 +240,7 @@
       val value = row.getDouble(ordinal)
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -265,7 +265,7 @@
       val size = STRING.actualSize(row, ordinal)
       gatherValueStats(value, size)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -287,7 +287,7 @@
       sizeInBytes += size
       count += 1
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -301,7 +301,7 @@
       sizeInBytes += CALENDAR_INTERVAL.actualSize(row, ordinal)
       count += 1
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -321,7 +321,7 @@
       // TODO: this is not right for DecimalType with precision > 18
       gatherValueStats(value)
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
@@ -345,7 +345,7 @@
       sizeInBytes += size
       count += 1
     } else {
-      gatherNullStats
+      gatherNullStats()
     }
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala
index 54e8181..a94140d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala
@@ -170,7 +170,7 @@
         sparkSession, table, table.storage.locationUri, SaveMode.Append, tableExists = true)
     } else {
       table.storage.locationUri.foreach { p =>
-        DataWritingCommand.assertEmptyRootPath(p, mode, sparkSession.sessionState.newHadoopConf)
+        DataWritingCommand.assertEmptyRootPath(p, mode, sparkSession.sessionState.newHadoopConf())
       }
       assert(table.schema.isEmpty)
       sparkSession.sessionState.catalog.validateTableLocation(table)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala
index 7d1acc7..1465e32 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/command/ddl.scala
@@ -393,7 +393,7 @@
       if (field.name == originColumn.name) {
         // Create a new column from the origin column with the new comment.
         val withNewComment: StructField =
-          addComment(field, newColumn.getComment)
+          addComment(field, newColumn.getComment())
         // Create a new column from the origin column with the new current default value.
         if (newColumn.getCurrentDefaultValue().isDefined) {
           if (newColumn.getCurrentDefaultValue().get.nonEmpty) {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatDataWriter.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatDataWriter.scala
index a3d2d2e..e9aa6d8 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatDataWriter.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatDataWriter.scala
@@ -173,7 +173,7 @@
     }
 
     currentWriter.write(record)
-    statsTrackers.foreach(_.newRow(currentWriter.path, record))
+    statsTrackers.foreach(_.newRow(currentWriter.path(), record))
     recordsInFile += 1
   }
 }
@@ -326,7 +326,7 @@
   protected def writeRecord(record: InternalRow): Unit = {
     val outputRow = getOutputRow(record)
     currentWriter.write(outputRow)
-    statsTrackers.foreach(_.newRow(currentWriter.path, outputRow))
+    statsTrackers.foreach(_.newRow(currentWriter.path(), outputRow))
     recordsInFile += 1
   }
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/LogicalRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/LogicalRelation.scala
index 83064a8..3c57903 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/LogicalRelation.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/LogicalRelation.scala
@@ -71,7 +71,7 @@
 
   override lazy val metadataOutput: Seq[AttributeReference] = relation match {
     case relation: HadoopFsRelation =>
-      metadataOutputWithOutConflicts(Seq(relation.fileFormat.createFileMetadataCol))
+      metadataOutputWithOutConflicts(Seq(relation.fileFormat.createFileMetadataCol()))
     case _ => Nil
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetUtils.scala
index 8a6221c..b325a2f 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetUtils.scala
@@ -376,7 +376,7 @@
           .named(schemaName)
       }
     }
-    (primitiveTypeBuilder.result, valuesBuilder.result)
+    (primitiveTypeBuilder.result(), valuesBuilder.result())
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DataSourceRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DataSourceRDD.scala
index 67e77a9..8288e7e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DataSourceRDD.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DataSourceRDD.scala
@@ -169,7 +169,7 @@
 private class MetricsRowIterator(
     iter: Iterator[InternalRow]) extends MetricsIterator[InternalRow](iter) {
   override def next(): InternalRow = {
-    val item = iter.next
+    val item = iter.next()
     metricsHandler.updateMetrics(1)
     item
   }
@@ -178,7 +178,7 @@
 private class MetricsBatchIterator(
     iter: Iterator[ColumnarBatch]) extends MetricsIterator[ColumnarBatch](iter) {
   override def next(): ColumnarBatch = {
-    val batch: ColumnarBatch = iter.next
+    val batch: ColumnarBatch = iter.next()
     metricsHandler.updateMetrics(batch.numRows)
     batch
   }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCTable.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCTable.scala
index b12f55e..1065d63 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCTable.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCTable.scala
@@ -58,7 +58,7 @@
       columnsProperties: util.Map[NamedReference, util.Map[String, String]],
       properties: util.Map[String, String]): Unit = {
     JdbcUtils.withConnection(jdbcOptions) { conn =>
-      JdbcUtils.classifyException(s"Failed to create index $indexName in $name",
+      JdbcUtils.classifyException(s"Failed to create index $indexName in ${name()}",
         JdbcDialects.get(jdbcOptions.url)) {
         JdbcUtils.createIndex(
           conn, indexName, ident, columns, columnsProperties, properties, jdbcOptions)
@@ -74,7 +74,7 @@
 
   override def dropIndex(indexName: String): Unit = {
     JdbcUtils.withConnection(jdbcOptions) { conn =>
-      JdbcUtils.classifyException(s"Failed to drop index $indexName in $name",
+      JdbcUtils.classifyException(s"Failed to drop index $indexName in ${name()}",
         JdbcDialects.get(jdbcOptions.url)) {
         JdbcUtils.dropIndex(conn, indexName, ident, jdbcOptions)
       }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala
index 7c48baf..3ae76a1 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/HashJoin.scala
@@ -341,7 +341,7 @@
           s"HashJoin should not take $x as the JoinType")
     }
 
-    val resultProj = createResultProjection
+    val resultProj = createResultProjection()
     joinedIter.map { r =>
       numOutputRows += 1
       resultProj(r)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonForeachWriter.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonForeachWriter.scala
index a229931..f5c2d9a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonForeachWriter.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonForeachWriter.scala
@@ -74,7 +74,9 @@
 
   private lazy val context = TaskContext.get()
   private lazy val buffer = new PythonForeachWriter.UnsafeRowBuffer(
-    context.taskMemoryManager, new File(Utils.getLocalDir(SparkEnv.get.conf)), schema.fields.length)
+    context.taskMemoryManager(),
+    new File(Utils.getLocalDir(SparkEnv.get.conf)),
+    schema.fields.length)
   private lazy val inputRowIterator = buffer.iterator
 
   private[this] val jobArtifactUUID = JobArtifactSet.getCurrentJobArtifactState.map(_.uuid)
@@ -101,7 +103,7 @@
   override def open(partitionId: Long, version: Long): Boolean = {
     outputIterator  // initialize everything
     writerThread.start()
-    TaskContext.get.addTaskCompletionListener[Unit] { _ => buffer.close() }
+    TaskContext.get().addTaskCompletionListener[Unit] { _ => buffer.close() }
     true
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
index 5009257..99d51f6 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
@@ -122,7 +122,7 @@
       input: mutable.Map[Any, Long]): mutable.Map[Any, Long] = {
     val otherIter = input.iterator
     while (otherIter.hasNext) {
-      val (key, count) = otherIter.next
+      val (key, count) = otherIter.next()
       add(buffer, key, count)
     }
     buffer
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
index dae2b70..e7f1aff 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
@@ -109,7 +109,7 @@
 
   /** Calculate the Pearson Correlation Coefficient for the given columns */
   def pearsonCorrelation(df: DataFrame, cols: Seq[String]): Double = {
-    calculateCorrImpl(df, cols).head.getDouble(0)
+    calculateCorrImpl(df, cols).head().getDouble(0)
   }
 
   private[sql] def calculateCorrImpl(
@@ -144,7 +144,7 @@
    * @return the covariance of the two columns.
    */
   def calculateCov(df: DataFrame, cols: Seq[String]): Double = {
-    calculateCovImpl(df, cols).head.getDouble(0)
+    calculateCovImpl(df, cols).head().getDouble(0)
   }
 
   private[sql] def calculateCovImpl(df: DataFrame, cols: Seq[String]): DataFrame = {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManager.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManager.scala
index ad32128..af2c97b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManager.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManager.scala
@@ -219,8 +219,8 @@
   }
 
   private def generateTempPath(path: Path): Path = {
-    val tc = org.apache.spark.TaskContext.get
-    val tid = if (tc != null) ".TID" + tc.taskAttemptId else ""
+    val tc = org.apache.spark.TaskContext.get()
+    val tid = if (tc != null) ".TID" + tc.taskAttemptId() else ""
     new Path(path.getParent, s".${path.getName}.${UUID.randomUUID}${tid}.tmp")
   }
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CommitLog.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CommitLog.scala
index ad7c59b..1d428e6 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CommitLog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CommitLog.scala
@@ -56,8 +56,8 @@
     if (!lines.hasNext) {
       throw new IllegalStateException("Incomplete log file in the offset commit log")
     }
-    validateVersion(lines.next.trim, VERSION)
-    val metadataJson = if (lines.hasNext) lines.next else EMPTY_JSON
+    validateVersion(lines.next().trim, VERSION)
+    val metadataJson = if (lines.hasNext) lines.next() else EMPTY_JSON
     CommitMetadata(metadataJson)
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala
index c7b0695..a5d114b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala
@@ -61,7 +61,7 @@
   val metadataPath = new Path(path)
 
   protected val fileManager =
-    CheckpointFileManager.create(metadataPath, sparkSession.sessionState.newHadoopConf)
+    CheckpointFileManager.create(metadataPath, sparkSession.sessionState.newHadoopConf())
 
   if (!fileManager.exists(metadataPath)) {
     fileManager.mkdirs(metadataPath)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/IncrementalExecution.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/IncrementalExecution.scala
index a67097f..8f01c99 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/IncrementalExecution.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/IncrementalExecution.scala
@@ -199,7 +199,7 @@
       case StateStoreSaveExec(keys, None, None, None, None, stateFormatVersion,
       UnaryExecNode(agg,
       StateStoreRestoreExec(_, None, _, child))) =>
-        val aggStateInfo = nextStatefulOperationStateInfo
+        val aggStateInfo = nextStatefulOperationStateInfo()
         StateStoreSaveExec(
           keys,
           Some(aggStateInfo),
@@ -218,7 +218,7 @@
       stateFormatVersion,
       UnaryExecNode(agg,
       SessionWindowStateStoreRestoreExec(_, _, None, None, None, _, child))) =>
-        val aggStateInfo = nextStatefulOperationStateInfo
+        val aggStateInfo = nextStatefulOperationStateInfo()
         SessionWindowStateStoreSaveExec(
           keys,
           session,
@@ -241,7 +241,7 @@
         StreamingDeduplicateExec(
           keys,
           child,
-          Some(nextStatefulOperationStateInfo),
+          Some(nextStatefulOperationStateInfo()),
           eventTimeWatermarkForLateEvents = None,
           eventTimeWatermarkForEviction = None)
 
@@ -249,7 +249,7 @@
         StreamingDeduplicateWithinWatermarkExec(
           keys,
           child,
-          Some(nextStatefulOperationStateInfo),
+          Some(nextStatefulOperationStateInfo()),
           eventTimeWatermarkForLateEvents = None,
           eventTimeWatermarkForEviction = None)
 
@@ -257,7 +257,7 @@
         // We set this to true only for the first batch of the streaming query.
         val hasInitialState = (currentBatchId == 0L && m.hasInitialState)
         m.copy(
-          stateInfo = Some(nextStatefulOperationStateInfo),
+          stateInfo = Some(nextStatefulOperationStateInfo()),
           batchTimestampMs = Some(offsetSeqMetadata.batchTimestampMs),
           eventTimeWatermarkForLateEvents = None,
           eventTimeWatermarkForEviction = None,
@@ -266,7 +266,7 @@
 
       case m: FlatMapGroupsInPandasWithStateExec =>
         m.copy(
-          stateInfo = Some(nextStatefulOperationStateInfo),
+          stateInfo = Some(nextStatefulOperationStateInfo()),
           batchTimestampMs = Some(offsetSeqMetadata.batchTimestampMs),
           eventTimeWatermarkForLateEvents = None,
           eventTimeWatermarkForEviction = None
@@ -274,14 +274,14 @@
 
       case j: StreamingSymmetricHashJoinExec =>
         j.copy(
-          stateInfo = Some(nextStatefulOperationStateInfo),
+          stateInfo = Some(nextStatefulOperationStateInfo()),
           eventTimeWatermarkForLateEvents = None,
           eventTimeWatermarkForEviction = None
         )
 
       case l: StreamingGlobalLimitExec =>
         l.copy(
-          stateInfo = Some(nextStatefulOperationStateInfo),
+          stateInfo = Some(nextStatefulOperationStateInfo()),
           outputMode = Some(outputMode))
     }
   }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MicroBatchExecution.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MicroBatchExecution.scala
index 756ee0c..3febce0 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MicroBatchExecution.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MicroBatchExecution.scala
@@ -280,7 +280,7 @@
       if (isActive) {
 
         // check if there are any previous errors and bubble up any existing async operations
-        errorNotifier.throwErrorIfExists
+        errorNotifier.throwErrorIfExists()
 
         var currentBatchHasNewData = false // Whether the current batch had new data
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
index d9cab24..d9b3b20 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala
@@ -243,7 +243,7 @@
 
   /** All checkpoint file operations should be performed through `CheckpointFileManager`. */
   private val fileManager = CheckpointFileManager.create(new Path(resolvedCheckpointRoot),
-      sparkSession.sessionState.newHadoopConf)
+      sparkSession.sessionState.newHadoopConf())
 
   /**
    * Starts the execution. This returns only after the thread has started and [[QueryStartedEvent]]
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingRelation.scala
index 0870867..135d46c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingRelation.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamingRelation.scala
@@ -64,7 +64,7 @@
       // If the dataSource provided class is a same or subclass of FileFormat class
       case f if classOf[FileFormat].isAssignableFrom(f) =>
         metadataOutputWithOutConflicts(
-          Seq(dataSource.providingInstance().asInstanceOf[FileFormat].createFileMetadataCol))
+          Seq(dataSource.providingInstance().asInstanceOf[FileFormat].createFileMetadataCol()))
       case _ => Nil
     }
   }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/TriggerExecutor.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/TriggerExecutor.scala
index e15fc8b..e807471 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/TriggerExecutor.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/TriggerExecutor.scala
@@ -62,11 +62,11 @@
 
   override def execute(triggerHandler: () => Boolean): Unit = {
     while (true) {
-      val triggerTimeMs = clock.getTimeMillis
+      val triggerTimeMs = clock.getTimeMillis()
       val nextTriggerTimeMs = nextBatchTime(triggerTimeMs)
       val terminated = !triggerHandler()
       if (intervalMs > 0) {
-        val batchElapsedTimeMs = clock.getTimeMillis - triggerTimeMs
+        val batchElapsedTimeMs = clock.getTimeMillis() - triggerTimeMs
         if (batchElapsedTimeMs > intervalMs) {
           notifyBatchFallingBehind(batchElapsedTimeMs)
         }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousTextSocketSource.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousTextSocketSource.scala
index 368dfae..d1b346b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousTextSocketSource.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousTextSocketSource.scala
@@ -56,8 +56,8 @@
 
   implicit val defaultFormats: DefaultFormats = DefaultFormats
 
-  private val encoder = ExpressionEncoder.tuple(ExpressionEncoder[String],
-    ExpressionEncoder[Timestamp])
+  private val encoder = ExpressionEncoder.tuple(ExpressionEncoder[String](),
+    ExpressionEncoder[Timestamp]())
 
   @GuardedBy("this")
   private var socket: Socket = _
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/RocksDB.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/RocksDB.scala
index 6024955..1e3f3a6 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/RocksDB.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/RocksDB.scala
@@ -559,12 +559,12 @@
     }
     if (isAcquiredByDifferentThread) {
       val stackTraceOutput = acquiredThreadInfo.threadRef.get.get.getStackTrace.mkString("\n")
-      throw QueryExecutionErrors.unreleasedThreadError(loggingId, newAcquiredThreadInfo.toString,
-        acquiredThreadInfo.toString, timeWaitedMs, stackTraceOutput)
+      throw QueryExecutionErrors.unreleasedThreadError(loggingId, newAcquiredThreadInfo.toString(),
+        acquiredThreadInfo.toString(), timeWaitedMs, stackTraceOutput)
     } else {
       acquiredThreadInfo = newAcquiredThreadInfo
       // Add a listener to always release the lock when the task (if active) completes
-      Option(TaskContext.get).foreach(_.addTaskCompletionListener[Unit] { _ => this.release() })
+      Option(TaskContext.get()).foreach(_.addTaskCompletionListener[Unit] { _ => this.release() })
       logInfo(s"RocksDB instance was acquired by $acquiredThreadInfo")
     }
   }
@@ -898,8 +898,8 @@
   override def toString(): String = {
     val taskStr = if (tc != null) {
       val taskDetails =
-        s"partition ${tc.partitionId}.${tc.attemptNumber} in stage " +
-          s"${tc.stageId}.${tc.stageAttemptNumber()}, TID ${tc.taskAttemptId}"
+        s"partition ${tc.partitionId()}.${tc.attemptNumber()} in stage " +
+          s"${tc.stageId()}.${tc.stageAttemptNumber()}, TID ${tc.taskAttemptId()}"
       s", task: $taskDetails"
     } else ""
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala
index bda560b..def4a41 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/statefulOperators.scala
@@ -897,7 +897,7 @@
         val (upserted, deleted) = stateManager.updateSessions(store, curKey, curValuesOnKey.toSeq)
         numUpdatedStateRows += upserted
         numRemovedStateRows += deleted
-        curValuesOnKey.clear
+        curValuesOnKey.clear()
       }
     }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala
index 0de16a4..8a2a528 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListener.scala
@@ -131,9 +131,9 @@
 
     // Reset the metrics tracking object for the new attempt.
     Option(stageMetrics.get(event.stageInfo.stageId)).foreach { stage =>
-      if (stage.attemptId != event.stageInfo.attemptNumber) {
+      if (stage.attemptId != event.stageInfo.attemptNumber()) {
         stageMetrics.put(event.stageInfo.stageId,
-          new LiveStageMetrics(event.stageInfo.stageId, event.stageInfo.attemptNumber,
+          new LiveStageMetrics(event.stageInfo.stageId, event.stageInfo.attemptNumber(),
             stage.numTasks, stage.accumIdsToMetricType))
       }
     }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala b/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala
index 74a4f1c..5650e9d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/internal/CatalogImpl.scala
@@ -314,7 +314,7 @@
           isTemporary = true)
 
       case _ =>
-        val catalogPath = (currentCatalog +:
+        val catalogPath = (currentCatalog() +:
           sparkSession.sessionState.catalogManager.currentNamespace).mkString(".")
         throw QueryCompilationErrors.unresolvedRoutineError(ident, Seq(catalogPath), plan.origin)
     }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala
index 3a3246a..8f537aa 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala
@@ -73,7 +73,7 @@
    */
   override def getTruncateQuery(
       table: String,
-      cascade: Option[Boolean] = isCascadingTruncateTable): String = {
+      cascade: Option[Boolean] = isCascadingTruncateTable()): String = {
     dialects.head.getTruncateQuery(table, cascade)
   }
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DB2Dialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DB2Dialect.scala
index 5d56b37..189dedb 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DB2Dialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DB2Dialect.scala
@@ -107,7 +107,7 @@
   // scalastyle:on line.size.limit
   override def getTruncateQuery(
       table: String,
-      cascade: Option[Boolean] = isCascadingTruncateTable): String = {
+      cascade: Option[Boolean] = isCascadingTruncateTable()): String = {
     s"TRUNCATE TABLE $table IMMEDIATE"
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DatabricksDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DatabricksDialect.scala
index 1b71528..697ddd2 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DatabricksDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/DatabricksDialect.scala
@@ -88,6 +88,6 @@
     while (rs.next()) {
       schemaBuilder += Array(rs.getString(1))
     }
-    schemaBuilder.result
+    schemaBuilder.result()
   }
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
index 37c378c..966092b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
@@ -243,7 +243,7 @@
    */
   @Since("2.3.0")
   def getTruncateQuery(table: String): String = {
-    getTruncateQuery(table, isCascadingTruncateTable)
+    getTruncateQuery(table, isCascadingTruncateTable())
   }
 
   /**
@@ -257,7 +257,7 @@
   @Since("2.4.0")
   def getTruncateQuery(
     table: String,
-    cascade: Option[Boolean] = isCascadingTruncateTable): String = {
+    cascade: Option[Boolean] = isCascadingTruncateTable()): String = {
       s"TRUNCATE TABLE $table"
   }
 
@@ -437,7 +437,7 @@
     while (rs.next()) {
       schemaBuilder += Array(rs.getString(1))
     }
-    schemaBuilder.result
+    schemaBuilder.result()
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala
index a08c893..3c6d02d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala
@@ -125,7 +125,7 @@
       case _: Exception =>
         logWarning("Cannot show schemas.")
     }
-    schemaBuilder.result
+    schemaBuilder.result()
   }
 
   override def getTableExistsQuery(table: String): String = {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/OracleDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/OracleDialect.scala
index 3a0333c..bcc8bc4 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/OracleDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/OracleDialect.scala
@@ -146,7 +146,7 @@
    */
   override def getTruncateQuery(
       table: String,
-      cascade: Option[Boolean] = isCascadingTruncateTable): String = {
+      cascade: Option[Boolean] = isCascadingTruncateTable()): String = {
     cascade match {
       case Some(true) => s"TRUNCATE TABLE $table CASCADE"
       case _ => s"TRUNCATE TABLE $table"
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/PostgresDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/PostgresDialect.scala
index 9c1ca2c..e3af807 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/PostgresDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/PostgresDialect.scala
@@ -64,7 +64,7 @@
     } else if ("text".equalsIgnoreCase(typeName)) {
       Some(StringType) // sqlType is  Types.VARCHAR
     } else if (sqlType == Types.ARRAY) {
-      val scale = md.build.getLong("scale").toInt
+      val scale = md.build().getLong("scale").toInt
       // postgres array type names start with underscore
       toCatalystType(typeName.drop(1), size, scale).map(ArrayType(_))
     } else None
@@ -149,7 +149,7 @@
    */
   override def getTruncateQuery(
       table: String,
-      cascade: Option[Boolean] = isCascadingTruncateTable): String = {
+      cascade: Option[Boolean] = isCascadingTruncateTable()): String = {
     cascade match {
       case Some(true) => s"TRUNCATE TABLE ONLY $table CASCADE"
       case _ => s"TRUNCATE TABLE ONLY $table"
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/TeradataDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/TeradataDialect.scala
index fb7728d..0f0812b 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/TeradataDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/TeradataDialect.scala
@@ -59,7 +59,7 @@
    */
   override def getTruncateQuery(
       table: String,
-      cascade: Option[Boolean] = isCascadingTruncateTable): String = {
+      cascade: Option[Boolean] = isCascadingTruncateTable()): String = {
     s"DELETE FROM $table ALL"
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/streaming/ui/StreamingQueryStatusListener.scala b/sql/core/src/main/scala/org/apache/spark/sql/streaming/ui/StreamingQueryStatusListener.scala
index aae2fad..48a3560 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/streaming/ui/StreamingQueryStatusListener.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/streaming/ui/StreamingQueryStatusListener.scala
@@ -93,7 +93,7 @@
     progressIds.enqueue(getUniqueId(runId, batchId, timestamp))
     store.write(new StreamingQueryProgressWrapper(event.progress))
     while (progressIds.length > streamingProgressRetention) {
-      val uniqueId = progressIds.dequeue
+      val uniqueId = progressIds.dequeue()
       store.delete(classOf[StreamingQueryProgressWrapper], uniqueId)
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala
index 7d41133..2db37745 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala
@@ -951,7 +951,7 @@
     val cachedData = checkIfNoJobTriggered {
       spark.range(1002).filter($"id" > 1000).orderBy($"id".desc).cache()
     }
-    assert(cachedData.collect === Seq(1001))
+    assert(cachedData.collect() === Seq(1001))
   }
 
   test("SPARK-24596 Non-cascading Cache Invalidation - uncache temporary view") {
@@ -1102,7 +1102,7 @@
         .agg(avg("c1").as("v1"), sum("c2").as("v2"))
     }
     // First, checks if there is no column statistic in cached query
-    val queryStats1 = query().cache.queryExecution.optimizedPlan.stats.attributeStats
+    val queryStats1 = query().cache().queryExecution.optimizedPlan.stats.attributeStats
     assert(queryStats1.map(_._1.name).isEmpty)
 
     val cacheManager = spark.sharedState.cacheManager
@@ -1596,8 +1596,8 @@
     withTempDir { dir =>
       val path1 = new File(dir, "t1").getCanonicalPath
       val path2 = new File(dir, "t2").getCanonicalPath
-      Seq(1).toDF.write.parquet(path1)
-      Seq(1).toDF.write.parquet(path2)
+      Seq(1).toDF().write.parquet(path1)
+      Seq(1).toDF().write.parquet(path2)
 
       val (tempViewStr, viewName) = if (ident.database.nonEmpty) {
         ("GLOBAL TEMPORARY VIEW", s"${ident.database.get}.${ident.table}")
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala
index 772eb9f..8c9ad21 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala
@@ -161,7 +161,7 @@
   }
 
   test("star qualified by data frame object") {
-    val df = testData.toDF
+    val df = testData.toDF()
     val goldAnswer = df.collect().toSeq
     checkAnswer(df.select(df("*")), goldAnswer)
 
@@ -260,7 +260,7 @@
 
   test("isNull") {
     checkAnswer(
-      nullStrings.toDF.where($"s".isNull),
+      nullStrings.toDF().where($"s".isNull),
       nullStrings.collect().toSeq.filter(r => r.getString(1) eq null))
 
     checkAnswer(
@@ -270,7 +270,7 @@
 
   test("isNotNull") {
     checkAnswer(
-      nullStrings.toDF.where($"s".isNotNull),
+      nullStrings.toDF().where($"s".isNotNull),
       nullStrings.collect().toSeq.filter(r => r.getString(1) ne null))
 
     checkAnswer(
@@ -539,41 +539,41 @@
         withSQLConf(
           SQLConf.OPTIMIZER_INSET_CONVERSION_THRESHOLD.key -> optThreshold.toString,
           SQLConf.OPTIMIZER_INSET_SWITCH_THRESHOLD.key -> switchThreshold.toString) {
-          checkAnswer(Seq(0).toDS.select($"value".isInCollection(Seq(null))), Seq(Row(null)))
+          checkAnswer(Seq(0).toDS().select($"value".isInCollection(Seq(null))), Seq(Row(null)))
           checkAnswer(
-            Seq(true).toDS.select($"value".isInCollection(Seq(true, false))),
+            Seq(true).toDS().select($"value".isInCollection(Seq(true, false))),
             Seq(Row(true)))
           checkAnswer(
-            Seq(0.toByte, 1.toByte).toDS.select($"value".isInCollection(Seq(0.toByte, 2.toByte))),
+            Seq(0.toByte, 1.toByte).toDS().select($"value".isInCollection(Seq(0.toByte, 2.toByte))),
             expected)
           checkAnswer(
-            Seq(0.toShort, 1.toShort).toDS
+            Seq(0.toShort, 1.toShort).toDS()
               .select($"value".isInCollection(Seq(0.toShort, 2.toShort))),
             expected)
-          checkAnswer(Seq(0, 1).toDS.select($"value".isInCollection(Seq(0, 2))), expected)
-          checkAnswer(Seq(0L, 1L).toDS.select($"value".isInCollection(Seq(0L, 2L))), expected)
-          checkAnswer(Seq(0.0f, 1.0f).toDS
+          checkAnswer(Seq(0, 1).toDS().select($"value".isInCollection(Seq(0, 2))), expected)
+          checkAnswer(Seq(0L, 1L).toDS().select($"value".isInCollection(Seq(0L, 2L))), expected)
+          checkAnswer(Seq(0.0f, 1.0f).toDS()
             .select($"value".isInCollection(Seq(0.0f, 2.0f))), expected)
-          checkAnswer(Seq(0.0D, 1.0D).toDS
+          checkAnswer(Seq(0.0D, 1.0D).toDS()
             .select($"value".isInCollection(Seq(0.0D, 2.0D))), expected)
           checkAnswer(
-            Seq(BigDecimal(0), BigDecimal(2)).toDS
+            Seq(BigDecimal(0), BigDecimal(2)).toDS()
               .select($"value".isInCollection(Seq(BigDecimal(0), BigDecimal(1)))),
             expected)
           checkAnswer(
-            Seq("abc", "def").toDS.select($"value".isInCollection(Seq("abc", "xyz"))),
+            Seq("abc", "def").toDS().select($"value".isInCollection(Seq("abc", "xyz"))),
             expected)
           checkAnswer(
-            Seq(Date.valueOf("2020-04-29"), Date.valueOf("2020-05-01")).toDS
+            Seq(Date.valueOf("2020-04-29"), Date.valueOf("2020-05-01")).toDS()
               .select($"value".isInCollection(
                 Seq(Date.valueOf("2020-04-29"), Date.valueOf("2020-04-30")))),
             expected)
           checkAnswer(
-            Seq(new Timestamp(0), new Timestamp(2)).toDS
+            Seq(new Timestamp(0), new Timestamp(2)).toDS()
               .select($"value".isInCollection(Seq(new Timestamp(0), new Timestamp(1)))),
             expected)
           checkAnswer(
-            Seq(Array("a", "b"), Array("c", "d")).toDS
+            Seq(Array("a", "b"), Array("c", "d")).toDS()
               .select($"value".isInCollection(Seq(Array("a", "b"), Array("x", "z")))),
             expected)
         }
@@ -3118,12 +3118,12 @@
   test("SPARK-39093: divide period by integral expression") {
     val df = Seq(((Period.ofMonths(10)), 2)).toDF("pd", "num")
     checkAnswer(df.select($"pd" / ($"num" + 3)),
-      Seq((Period.ofMonths(2))).toDF)
+      Seq((Period.ofMonths(2))).toDF())
   }
 
   test("SPARK-39093: divide duration by integral expression") {
     val df = Seq(((Duration.ofDays(10)), 2)).toDF("dd", "num")
     checkAnswer(df.select($"dd" / ($"num" + 3)),
-      Seq((Duration.ofDays(2))).toDF)
+      Seq((Duration.ofDays(2))).toDF())
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/CsvFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/CsvFunctionsSuite.scala
index 3b5f094..c40ecb8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/CsvFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/CsvFunctionsSuite.scala
@@ -449,11 +449,11 @@
           .selectExpr("from_csv(csv, 'a int, b int', map('mode', 'failfast')) as parsed")
 
         val err1 = intercept[SparkException] {
-          df.selectExpr("parsed.a").collect
+          df.selectExpr("parsed.a").collect()
         }
 
         val err2 = intercept[SparkException] {
-          df.selectExpr("parsed.b").collect
+          df.selectExpr("parsed.b").collect()
         }
 
         assert(err1.getMessage.contains("Malformed records are detected in record parsing"))
@@ -475,7 +475,7 @@
   }
 
   test("SPARK-35998: Make from_csv/to_csv to handle year-month intervals properly") {
-    val ymDF = Seq(Period.of(1, 2, 0)).toDF
+    val ymDF = Seq(Period.of(1, 2, 0)).toDF()
     Seq(
       (YearMonthIntervalType(), "INTERVAL '1-2' YEAR TO MONTH", Period.of(1, 2, 0)),
       (YearMonthIntervalType(YEAR), "INTERVAL '1' YEAR", Period.of(1, 0, 0)),
@@ -502,7 +502,7 @@
   }
 
   test("SPARK-35999: Make from_csv/to_csv to handle day-time intervals properly") {
-    val dtDF = Seq(Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)).toDF
+    val dtDF = Seq(Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)).toDF()
     Seq(
       (DayTimeIntervalType(), "INTERVAL '1 02:03:04' DAY TO SECOND",
         Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)),
@@ -547,7 +547,7 @@
 
   test("SPARK-36490: Make from_csv/to_csv to handle timestamp_ntz type properly") {
     val localDT = LocalDateTime.parse("2021-08-12T15:16:23")
-    val df = Seq(localDT).toDF
+    val df = Seq(localDT).toDF()
     val toCsvDF = df.select(to_csv(struct($"value")) as "csv")
     checkAnswer(toCsvDF, Row("2021-08-12T15:16:23.000"))
     val fromCsvDF = toCsvDF
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala
index 80862ee..ccfdddd 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala
@@ -158,7 +158,7 @@
       Fact(20151123, 18, 36, "room2", 25.6))).toDF()
 
     val cube0 = df0.cube("date", "hour", "minute", "room_name").agg(Map("temp" -> "avg"))
-    assert(cube0.where("date IS NULL").count > 0)
+    assert(cube0.where("date IS NULL").count() > 0)
   }
 
   test("grouping and grouping_id") {
@@ -960,7 +960,7 @@
         .select($"x", map($"x", $"y").as("y"))
         .createOrReplaceTempView("tempView")
       val error = intercept[AnalysisException] {
-        sql("SELECT max_by(x, y) FROM tempView").show
+        sql("SELECT max_by(x, y) FROM tempView").show()
       }
       checkError(
         exception = error,
@@ -1030,7 +1030,7 @@
         .select($"x", map($"x", $"y").as("y"))
         .createOrReplaceTempView("tempView")
       val error = intercept[AnalysisException] {
-        sql("SELECT min_by(x, y) FROM tempView").show
+        sql("SELECT min_by(x, y) FROM tempView").show()
       }
       checkError(
         exception = error,
@@ -1242,7 +1242,7 @@
     val df = Seq(
       A(None),
       A(Some(B(None))),
-      A(Some(B(Some(1.0))))).toDF
+      A(Some(B(Some(1.0))))).toDF()
     val groupBy = df.groupBy("b").agg(count("*"))
     checkAnswer(groupBy, Row(null, 1) :: Row(Row(null), 1) :: Row(Row(1.0), 1) :: Nil)
   }
@@ -1613,7 +1613,7 @@
 
   test("SPARK-38185: Fix data incorrect if aggregate function is empty") {
     val emptyAgg = Map.empty[String, String]
-    assert(spark.range(2).where("id > 2").agg(emptyAgg).limit(1).count == 1)
+    assert(spark.range(2).where("id > 2").agg(emptyAgg).limit(1).count() == 1)
   }
 
   test("SPARK-38221: group by stream of complex expressions should not fail") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala
index 4f25642..04c2b5a 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameComplexTypeSuite.scala
@@ -66,7 +66,7 @@
 
   test("SPARK-15285 Generated SpecificSafeProjection.apply method grows beyond 64KB") {
     val ds100_5 = Seq(S100_5()).toDS()
-    ds100_5.rdd.count
+    ds100_5.rdd.count()
   }
 
   test("SPARK-29503 nest unsafe struct inside safe array") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
index 4020688..7891965 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
@@ -176,7 +176,7 @@
 
     val df5 = Seq((Seq("a", null), Seq(1, 2))).toDF("k", "v")
     val e1 = intercept[SparkException] {
-      df5.select(map_from_arrays($"k", $"v")).collect
+      df5.select(map_from_arrays($"k", $"v")).collect()
     }
     assert(e1.getCause.isInstanceOf[SparkRuntimeException])
     checkError(
@@ -187,7 +187,7 @@
 
     val df6 = Seq((Seq(1, 2), Seq("a"))).toDF("k", "v")
     val msg2 = intercept[Exception] {
-      df6.select(map_from_arrays($"k", $"v")).collect
+      df6.select(map_from_arrays($"k", $"v")).collect()
     }.getMessage
     assert(msg2.contains("The key array and value array of MapData must have the same length"))
   }
@@ -224,7 +224,7 @@
       StructField("col1", IntegerType, nullable = false),
       StructField("b", StringType)
     ))
-    assert(result.first.schema(0).dataType === expectedType)
+    assert(result.first().schema(0).dataType === expectedType)
     checkAnswer(result, Row(Row(2, "str")))
   }
 
@@ -237,7 +237,7 @@
       StructField("col2", DoubleType, nullable = false)
     ))
 
-    assert(result.first.schema(0).dataType === expectedType)
+    assert(result.first().schema(0).dataType === expectedType)
     checkAnswer(result, Seq(Row(Row(2, 5.0)), Row(Row(4, 5.0))))
   }
 
@@ -250,7 +250,7 @@
       StructField("col2", DoubleType, nullable = false)
     ))
 
-    assert(result.first.schema(0).dataType === expectedType)
+    assert(result.first().schema(0).dataType === expectedType)
     checkAnswer(result, Seq(Row(Row("v", 5.0)), Row(Row("v", 5.0))))
   }
 
@@ -401,7 +401,7 @@
     val encryptedEcb = "9J3iZbIxnmaG+OIA9Amd+A=="
     val encryptedGcm = "y5la3muiuxN2suj6VsYXB+0XUFjtrUD0/zv5eDafsA3U"
     val encryptedCbc = "+MgyzJxhusYVGWCljk7fhhl6C6oUqWmtdqoaG93KvhY="
-    val df1 = Seq("Spark").toDF
+    val df1 = Seq("Spark").toDF()
 
     // Successful decryption of fixed values
     Seq(
@@ -426,7 +426,7 @@
     val encryptedGcm = "AAAAAAAAAAAAAAAAQiYi+sRNYDAOTjdSEcYBFsAWPL1f"
     val cbcIv = "00000000000000000000000000000000"
     val encryptedCbc = "AAAAAAAAAAAAAAAAAAAAAPSd4mWyMZ5mhvjiAPQJnfg="
-    val df1 = Seq("Spark").toDF
+    val df1 = Seq("Spark").toDF()
     Seq(
       (key32, encryptedGcm, "GCM", gcmIv),
       (key32, encryptedCbc, "CBC", cbcIv)).foreach {
@@ -451,7 +451,7 @@
     val gcmIv = "000000000000000000000000"
     val aad = "This is an AAD mixed into the input"
     val encryptedGcm = "AAAAAAAAAAAAAAAAQiYi+sTLm7KD9UcZ2nlRdYDe/PX4"
-    val df1 = Seq("Spark").toDF
+    val df1 = Seq("Spark").toDF()
     Seq(
       (key32, encryptedGcm, "GCM", gcmIv, aad)).foreach {
       case (key, ciphertext, mode, iv, aad) =>
@@ -481,7 +481,7 @@
     val encryptedEmptyText24 = "9RDK70sHNzqAFRcpfGM5gQ=="
     val encryptedEmptyText32 = "j9IDsCvlYXtcVJUf4FAjQQ=="
 
-    val df1 = Seq("Spark", "").toDF
+    val df1 = Seq("Spark", "").toDF()
 
     // Successful encryption
     Seq(
@@ -3232,7 +3232,7 @@
     ).toDF("a", "b")
     val result10 = df10.select(array_except($"a", $"b"))
     val expectedType10 = ArrayType(IntegerType, containsNull = true)
-    assert(result10.first.schema(0).dataType === expectedType10)
+    assert(result10.first().schema(0).dataType === expectedType10)
   }
 
   test("array_intersect functions") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameImplicitsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameImplicitsSuite.scala
index a454d91..8850e4d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameImplicitsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameImplicitsSuite.scala
@@ -53,13 +53,13 @@
   }
 
   test("SPARK-19959: df[java.lang.Long].collect includes null throws NullPointerException") {
-    checkAnswer(sparkContext.parallelize(Seq[java.lang.Integer](0, null, 2), 1).toDF,
+    checkAnswer(sparkContext.parallelize(Seq[java.lang.Integer](0, null, 2), 1).toDF(),
       Seq(Row(0), Row(null), Row(2)))
-    checkAnswer(sparkContext.parallelize(Seq[java.lang.Long](0L, null, 2L), 1).toDF,
+    checkAnswer(sparkContext.parallelize(Seq[java.lang.Long](0L, null, 2L), 1).toDF(),
       Seq(Row(0L), Row(null), Row(2L)))
-    checkAnswer(sparkContext.parallelize(Seq[java.lang.Float](0.0F, null, 2.0F), 1).toDF,
+    checkAnswer(sparkContext.parallelize(Seq[java.lang.Float](0.0F, null, 2.0F), 1).toDF(),
       Seq(Row(0.0F), Row(null), Row(2.0F)))
-    checkAnswer(sparkContext.parallelize(Seq[java.lang.Double](0.0D, null, 2.0D), 1).toDF,
+    checkAnswer(sparkContext.parallelize(Seq[java.lang.Double](0.0D, null, 2.0D), 1).toDF(),
       Seq(Row(0.0D), Row(null), Row(2.0D)))
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameJoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameJoinSuite.scala
index a923d1f..4c6f34d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameJoinSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameJoinSuite.scala
@@ -285,7 +285,7 @@
   test("process outer join results using the non-nullable columns in the join input") {
     // Filter data using a non-nullable column from a right table
     val df1 = Seq((0, 0), (1, 0), (2, 0), (3, 0), (4, 0)).toDF("id", "count")
-    val df2 = Seq(Tuple1(0), Tuple1(1)).toDF("id").groupBy("id").count
+    val df2 = Seq(Tuple1(0), Tuple1(1)).toDF("id").groupBy("id").count()
     checkAnswer(
       df1.join(df2, df1("id") === df2("id"), "left_outer").filter(df2("count").isNull),
       Row(2, 0, null, null) ::
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
index ea0e9a3..ab900e2 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameNaFunctionsSuite.scala
@@ -320,7 +320,7 @@
     val df = createDFWithNestedColumns
 
     // Rows with the specified nested columns whose null values are dropped.
-    assert(df.count == 3)
+    assert(df.count() == 3)
     checkAnswer(
       df.na.drop("any", Seq("c1.c1-1")),
       Seq(Row(Row("b1", "b2"))))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFramePivotSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFramePivotSuite.scala
index eafd454..237915f 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFramePivotSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFramePivotSuite.scala
@@ -332,7 +332,7 @@
       (2, Seq("a", "x")),
       (3, Seq.empty[String]),
       (3, Seq("a", "x"))).toDF("x", "s")
-    val expected = Seq((3, 1, 1), (2, 1, 1)).toDF
+    val expected = Seq((3, 1, 1), (2, 1, 1)).toDF()
     val actual = df.groupBy("x").pivot("s").count()
     checkAnswer(actual, expected)
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameRangeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameRangeSuite.scala
index 917f80e..441b276 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameRangeSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameRangeSuite.scala
@@ -35,77 +35,77 @@
   test("SPARK-7150 range api") {
     // numSlice is greater than length
     val res1 = spark.range(0, 10, 1, 15).select("id")
-    assert(res1.count == 10)
+    assert(res1.count() == 10)
     assert(res1.agg(sum("id")).as("sumid").collect() === Seq(Row(45)))
 
     val res2 = spark.range(3, 15, 3, 2).select("id")
-    assert(res2.count == 4)
+    assert(res2.count() == 4)
     assert(res2.agg(sum("id")).as("sumid").collect() === Seq(Row(30)))
 
     val res3 = spark.range(1, -2).select("id")
-    assert(res3.count == 0)
+    assert(res3.count() == 0)
 
     // start is positive, end is negative, step is negative
     val res4 = spark.range(1, -2, -2, 6).select("id")
-    assert(res4.count == 2)
+    assert(res4.count() == 2)
     assert(res4.agg(sum("id")).as("sumid").collect() === Seq(Row(0)))
 
     // start, end, step are negative
     val res5 = spark.range(-3, -8, -2, 1).select("id")
-    assert(res5.count == 3)
+    assert(res5.count() == 3)
     assert(res5.agg(sum("id")).as("sumid").collect() === Seq(Row(-15)))
 
     // start, end are negative, step is positive
     val res6 = spark.range(-8, -4, 2, 1).select("id")
-    assert(res6.count == 2)
+    assert(res6.count() == 2)
     assert(res6.agg(sum("id")).as("sumid").collect() === Seq(Row(-14)))
 
     val res7 = spark.range(-10, -9, -20, 1).select("id")
-    assert(res7.count == 0)
+    assert(res7.count() == 0)
 
     if (!conf.ansiEnabled) {
       val res8 = spark.range(Long.MinValue, Long.MaxValue, Long.MaxValue, 100).select("id")
-      assert(res8.count == 3)
+      assert(res8.count() == 3)
       assert(res8.agg(sum("id")).as("sumid").collect() === Seq(Row(-3)))
 
       val res9 = spark.range(Long.MaxValue, Long.MinValue, Long.MinValue, 100).select("id")
-      assert(res9.count == 2)
+      assert(res9.count() == 2)
       assert(res9.agg(sum("id")).as("sumid").collect() === Seq(Row(Long.MaxValue - 1)))
     }
 
     // only end provided as argument
     val res10 = spark.range(10).select("id")
-    assert(res10.count == 10)
+    assert(res10.count() == 10)
     assert(res10.agg(sum("id")).as("sumid").collect() === Seq(Row(45)))
 
     val res11 = spark.range(-1).select("id")
-    assert(res11.count == 0)
+    assert(res11.count() == 0)
 
     // using the default slice number
     val res12 = spark.range(3, 15, 3).select("id")
-    assert(res12.count == 4)
+    assert(res12.count() == 4)
     assert(res12.agg(sum("id")).as("sumid").collect() === Seq(Row(30)))
 
     // difference between range start and end does not fit in a 64-bit integer
     val n = 9L * 1000 * 1000 * 1000 * 1000 * 1000 * 1000
     val res13 = spark.range(-n, n, n / 9).select("id")
-    assert(res13.count == 18)
+    assert(res13.count() == 18)
 
     // range with non aggregation operation
-    val res14 = spark.range(0, 100, 2).toDF.filter("50 <= id")
-    val len14 = res14.collect.length
+    val res14 = spark.range(0, 100, 2).toDF().filter("50 <= id")
+    val len14 = res14.collect().length
     assert(len14 == 25)
 
-    val res15 = spark.range(100, -100, -2).toDF.filter("id <= 0")
-    val len15 = res15.collect.length
+    val res15 = spark.range(100, -100, -2).toDF().filter("id <= 0")
+    val len15 = res15.collect().length
     assert(len15 == 50)
 
-    val res16 = spark.range(-1500, 1500, 3).toDF.filter("0 <= id")
-    val len16 = res16.collect.length
+    val res16 = spark.range(-1500, 1500, 3).toDF().filter("0 <= id")
+    val len16 = res16.collect().length
     assert(len16 == 500)
 
-    val res17 = spark.range(10, 0, -1, 1).toDF.sortWithinPartitions("id")
-    assert(res17.collect === (1 to 10).map(i => Row(i)).toArray)
+    val res17 = spark.range(10, 0, -1, 1).toDF().sortWithinPartitions("id")
+    assert(res17.collect() === (1 to 10).map(i => Row(i)).toArray)
   }
 
   testWithWholeStageCodegenOnAndOff("Range with randomized parameters") { codegenEnabled =>
@@ -184,7 +184,7 @@
     "inconsistent with SparkContext.range()") { _ =>
     val start = java.lang.Long.MAX_VALUE - 3
     val end = java.lang.Long.MIN_VALUE + 2
-    assert(spark.range(start, end, 1).collect.length == 0)
-    assert(spark.range(start, start, 1).collect.length == 0)
+    assert(spark.range(start, end, 1).collect().length == 0)
+    assert(spark.range(start, start, 1).collect().length == 0)
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSelfJoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSelfJoinSuite.scala
index b830039..88ef593 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSelfJoinSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSelfJoinSuite.scala
@@ -357,7 +357,7 @@
     assertAmbiguousSelfJoin(df2.join(df1, df1("key1") === df2("key2")))
 
     // Test for SerializeFromObject
-    val df3 = spark.sparkContext.parallelize(1 to 10).map(x => (x, x)).toDF
+    val df3 = spark.sparkContext.parallelize(1 to 10).map(x => (x, x)).toDF()
     val df4 = df3.filter($"_1" <=> 0)
     assertAmbiguousSelfJoin(df3.join(df4, df3("_1") === df4("_2")))
     assertAmbiguousSelfJoin(df4.join(df3, df3("_1") === df4("_2")))
@@ -411,7 +411,7 @@
     // Test for Generate
     // Ensure that the root of the plan is Generate
     val df15 = Seq((1, Seq(1, 2, 3))).toDF("a", "intList").select($"a", explode($"intList"))
-      .queryExecution.optimizedPlan.find(_.isInstanceOf[Generate]).get.toDF
+      .queryExecution.optimizedPlan.find(_.isInstanceOf[Generate]).get.toDF()
     val df16 = df15.filter($"a" > 0)
     assertAmbiguousSelfJoin(df15.join(df16, df15("a") === df16("col")))
     assertAmbiguousSelfJoin(df16.join(df15, df15("a") === df16("col")))
@@ -424,7 +424,7 @@
         Seq(
           AttributeReference("x", IntegerType)(),
           AttributeReference("y", IntegerType)()),
-        df1.queryExecution.logical).toDF
+        df1.queryExecution.logical).toDF()
     val df18 = df17.filter($"x" > 0)
     assertAmbiguousSelfJoin(df17.join(df18, df17("x") === df18("y")))
     assertAmbiguousSelfJoin(df18.join(df17, df17("x") === df18("y")))
@@ -436,7 +436,7 @@
       Seq(Alias(dfWithTS("time").expr, "ts")()),
       Seq(dfWithTS("a").expr),
       Seq(SortOrder(dfWithTS("a").expr, Ascending)),
-      dfWithTS.queryExecution.logical).toDF
+      dfWithTS.queryExecution.logical).toDF()
     val df20 = df19.filter($"a" > 0)
     assertAmbiguousSelfJoin(df19.join(df20, df19("a") === df20("b")))
     assertAmbiguousSelfJoin(df20.join(df19, df19("a") === df20("b")))
@@ -462,7 +462,7 @@
         AttributeReference("x", IntegerType)(),
         AttributeReference("y", IntegerType)()),
       df1.queryExecution.logical,
-      ioSchema).toDF
+      ioSchema).toDF()
     val df22 = df21.filter($"x" > 0)
     assertAmbiguousSelfJoin(df21.join(df22, df21("x") === df22("y")))
     assertAmbiguousSelfJoin(df22.join(df21, df21("x") === df22("y")))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala
index 747f43f..ab8aab0 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSetOperationsSuite.scala
@@ -633,7 +633,7 @@
         (1, 1)
       )).toDF("a", "b").withColumn("c", newCol)
 
-      val df2 = df1.union(df1).withColumn("d", spark_partition_id).filter(filter)
+      val df2 = df1.union(df1).withColumn("d", spark_partition_id()).filter(filter)
       checkAnswer(df2, result)
     }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index c72bc91..b7450e5 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -989,7 +989,7 @@
       .parallelize(Seq(StringWrapper("a"), StringWrapper("b"), StringWrapper("c")))
       .toDF()
     val filtered = df.where("s = \"a\"")
-    checkAnswer(filtered, spark.sparkContext.parallelize(Seq(StringWrapper("a"))).toDF)
+    checkAnswer(filtered, spark.sparkContext.parallelize(Seq(StringWrapper("a"))).toDF())
   }
 
   test("SPARK-20384: Tuple2 of value class filter") {
@@ -1000,7 +1000,7 @@
       .toDF()
     val filtered = df.where("_2.s = \"a2\"")
     checkAnswer(filtered,
-      spark.sparkContext.parallelize(Seq((StringWrapper("a1"), StringWrapper("a2")))).toDF)
+      spark.sparkContext.parallelize(Seq((StringWrapper("a1"), StringWrapper("a2")))).toDF())
   }
 
   test("SPARK-20384: Tuple3 of value class filter") {
@@ -1012,26 +1012,26 @@
     val filtered = df.where("_3.s = \"a3\"")
     checkAnswer(filtered,
       spark.sparkContext.parallelize(
-        Seq((StringWrapper("a1"), StringWrapper("a2"), StringWrapper("a3")))).toDF)
+        Seq((StringWrapper("a1"), StringWrapper("a2"), StringWrapper("a3")))).toDF())
   }
 
   test("SPARK-20384: Array value class filter") {
     val ab = ArrayStringWrapper(Seq(StringWrapper("a"), StringWrapper("b")))
     val cd = ArrayStringWrapper(Seq(StringWrapper("c"), StringWrapper("d")))
 
-    val df = spark.sparkContext.parallelize(Seq(ab, cd)).toDF
+    val df = spark.sparkContext.parallelize(Seq(ab, cd)).toDF()
     val filtered = df.where(array_contains(col("wrappers.s"), "b"))
-    checkAnswer(filtered, spark.sparkContext.parallelize(Seq(ab)).toDF)
+    checkAnswer(filtered, spark.sparkContext.parallelize(Seq(ab)).toDF())
   }
 
   test("SPARK-20384: Nested value class filter") {
     val a = ContainerStringWrapper(StringWrapper("a"))
     val b = ContainerStringWrapper(StringWrapper("b"))
 
-    val df = spark.sparkContext.parallelize(Seq(a, b)).toDF
+    val df = spark.sparkContext.parallelize(Seq(a, b)).toDF()
     // flat value class, `s` field is not in schema
     val filtered = df.where("wrapper = \"a\"")
-    checkAnswer(filtered, spark.sparkContext.parallelize(Seq(a)).toDF)
+    checkAnswer(filtered, spark.sparkContext.parallelize(Seq(a)).toDF())
   }
 
   private lazy val person2: DataFrame = Seq(
@@ -2474,7 +2474,7 @@
     val rdd = sparkContext.makeRDD(Seq(Row.fromSeq(Seq.range(0, size))))
     val schemas = List.range(0, size).map(a => StructField("name" + a, LongType, true))
     val df = spark.createDataFrame(rdd, StructType(schemas))
-    assert(df.persist.take(1).apply(0).toSeq(100).asInstanceOf[Long] == 100)
+    assert(df.persist().take(1).apply(0).toSeq(100).asInstanceOf[Long] == 100)
   }
 
   test("SPARK-17409: Do Not Optimize Query in CTAS (Data source tables) More Than Once") {
@@ -2498,7 +2498,7 @@
   test("copy results for sampling with replacement") {
     val df = Seq((1, 0), (2, 0), (3, 0)).toDF("a", "b")
     val sampleDf = df.sample(true, 2.00)
-    val d = sampleDf.withColumn("c", monotonically_increasing_id).select($"c").collect
+    val d = sampleDf.withColumn("c", monotonically_increasing_id()).select($"c").collect()
     assert(d.size == d.distinct.size)
   }
 
@@ -2601,7 +2601,7 @@
     df1
       .join(df2, df1("x") === df2("x1"), "left_outer")
       .filter($"x1".isNotNull || !$"y".isin("a!"))
-      .count
+      .count()
   }
 
   // The fix of SPARK-21720 avoid an exception regarding JVM code size limit
@@ -2862,7 +2862,7 @@
       Console.withOut(captured) {
         df.explain(extended = true)
       }
-      checkAnswer(df, spark.range(10).toDF)
+      checkAnswer(df, spark.range(10).toDF())
       val output = captured.toString
       assert(output.contains(
         """== Parsed Logical Plan ==
@@ -2905,7 +2905,7 @@
         data1.zip(data2).map { p =>
           p._1.getInt(2) + p._2.getInt(2)
         }
-      }.toDF
+      }.toDF()
 
     checkAnswer(df3.sort("value"), Row(7) :: Row(9) :: Nil)
 
@@ -2932,7 +2932,7 @@
         data1.zip(data2).map { p =>
           p._1.getInt(2) + p._2.getInt(2)
         }
-      }.toDF
+      }.toDF()
 
     checkAnswer(df3.sort("value"), Row(7) :: Row(9) :: Nil)
   }
@@ -3459,7 +3459,7 @@
       }
     ))
 
-    assert(res.collect.length == 2)
+    assert(res.collect().length == 2)
   }
 
   test("SPARK-38285: Fix ClassCastException: GenericArrayData cannot be cast to InternalRow") {
@@ -3524,7 +3524,7 @@
       }
 
       // UNION (distinct)
-      val df4 = df3.distinct
+      val df4 = df3.distinct()
       checkAnswer(df4, rows.distinct)
 
       val t4 = sqlQuery(cols1, cols2, true)
@@ -3546,7 +3546,7 @@
   }
 
   test("SPARK-39612: exceptAll with following count should work") {
-    val d1 = Seq("a").toDF
+    val d1 = Seq("a").toDF()
     assert(d1.exceptAll(d1).count() === 0)
   }
 
@@ -3641,7 +3641,7 @@
     val df = spark.sparkContext.parallelize(1 to 5).toDF("x")
     val v1 = (rand() * 10000).cast(IntegerType)
     val v2 = to_csv(struct(v1.as("a"))) // to_csv is CodegenFallback
-    df.select(v1, v1, v2, v2).collect.foreach { row =>
+    df.select(v1, v1, v2, v2).collect().foreach { row =>
       assert(row.getInt(0) == row.getInt(1))
       assert(row.getInt(0).toString == row.getString(2))
       assert(row.getInt(0).toString == row.getString(3))
@@ -3656,7 +3656,7 @@
     val r3 = random()
     val r4 = uuid()
     val r5 = shuffle(col("a"))
-    df.select(r, r, r2, r2, r3, r3, r4, r4, r5, r5).collect.foreach { row =>
+    df.select(r, r, r2, r2, r3, r3, r4, r4, r5, r5).collect().foreach { row =>
       (0 until 5).foreach(i => assert(row.get(i * 2) === row.get(i * 2 + 1)))
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameTungstenSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameTungstenSuite.scala
index a9f7d5b..e5937ce 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameTungstenSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameTungstenSuite.scala
@@ -84,19 +84,19 @@
     }
     val rdd = sparkContext.makeRDD(Seq(Row.fromSeq(data)))
     val df = spark.createDataFrame(rdd, StructType(schemas))
-    val row = df.persist.take(1).apply(0)
+    val row = df.persist().take(1).apply(0)
     checkAnswer(df, row)
   }
 
   test("access cache multiple times") {
-    val df0 = sparkContext.parallelize(Seq(1, 2, 3), 1).toDF("x").cache
-    df0.count
+    val df0 = sparkContext.parallelize(Seq(1, 2, 3), 1).toDF("x").cache()
+    df0.count()
     val df1 = df0.filter("x > 1")
     checkAnswer(df1, Seq(Row(2), Row(3)))
     val df2 = df0.filter("x > 2")
     checkAnswer(df2, Row(3))
 
-    val df10 = sparkContext.parallelize(Seq(3, 4, 5, 6), 1).toDF("x").cache
+    val df10 = sparkContext.parallelize(Seq(3, 4, 5, 6), 1).toDF("x").cache()
     for (_ <- 0 to 2) {
       val df11 = df10.filter("x > 5")
       checkAnswer(df11, Row(6))
@@ -105,8 +105,8 @@
 
   test("access only some column of the all of columns") {
     val df = spark.range(1, 10).map(i => (i, (i + 1).toDouble)).toDF("l", "d")
-    df.cache
-    df.count
-    assert(df.filter("d < 3").count == 1)
+    df.cache()
+    df.count()
+    assert(df.filter("d < 3").count() == 1)
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetBenchmark.scala
index 076332f..dcd16ba 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetBenchmark.scala
@@ -252,7 +252,7 @@
   }
 
   override def getSparkSession: SparkSession = {
-    SparkSession.builder
+    SparkSession.builder()
       .master("local[*]")
       .appName("Dataset benchmark")
       .getOrCreate()
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
index 10a28ca..51fa3cd 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
@@ -1018,7 +1018,7 @@
     val observed_df = spark.range(100).observe(
       namedObservation, percentile_approx($"id", lit(0.5), lit(100)).as("percentile_approx_val"))
 
-    observed_df.foreach(r => f)
+    observed_df.foreach(r => f())
     val expected = Map("percentile_approx_val" -> 49)
 
     assert(namedObservation.get === expected)
@@ -1089,9 +1089,9 @@
     ).toDF("id", "stringData")
     val sampleDF = df.sample(false, 0.7, 50)
     // After sampling, sampleDF doesn't contain id=a.
-    assert(!sampleDF.select("id").as[Int].collect.contains(a))
+    assert(!sampleDF.select("id").as[Int].collect().contains(a))
     // simpleUdf should not encounter id=a.
-    checkAnswer(sampleDF.select(simpleUdf($"id")), List.fill(sampleDF.count.toInt)(Row(a)))
+    checkAnswer(sampleDF.select(simpleUdf($"id")), List.fill(sampleDF.count().toInt)(Row(a)))
   }
 
   test("SPARK-11436: we should rebind right encoder when join 2 datasets") {
@@ -1166,7 +1166,7 @@
   }
 
   test("SPARK-14696: implicit encoders for boxed types") {
-    assert(spark.range(1).map { i => i : java.lang.Long }.head == 0L)
+    assert(spark.range(1).map { i => i : java.lang.Long }.head() == 0L)
   }
 
   test("SPARK-11894: Incorrect results are returned when using null") {
@@ -1336,11 +1336,11 @@
   test("dataset.rdd with generic case class") {
     val ds = Seq(Generic(1, 1.0), Generic(2, 2.0)).toDS()
     val ds2 = ds.map(g => Generic(g.id, g.value))
-    assert(ds.rdd.map(r => r.id).count === 2)
-    assert(ds2.rdd.map(r => r.id).count === 2)
+    assert(ds.rdd.map(r => r.id).count() === 2)
+    assert(ds2.rdd.map(r => r.id).count() === 2)
 
     val ds3 = ds.map(g => java.lang.Long.valueOf(g.id))
-    assert(ds3.rdd.map(r => r).count === 2)
+    assert(ds3.rdd.map(r => r).count() === 2)
   }
 
   test("runtime null check for RowEncoder") {
@@ -1614,7 +1614,7 @@
       Route("b", "a", 1),
       Route("b", "a", 5),
       Route("b", "c", 6))
-    val ds = sparkContext.parallelize(data).toDF.as[Route]
+    val ds = sparkContext.parallelize(data).toDF().as[Route]
 
     val grouped = ds.map(r => GroupedRoutes(r.src, r.dest, Seq(r)))
       .groupByKey(r => (r.src, r.dest))
@@ -1649,15 +1649,15 @@
   }
 
   test("SPARK-18284: Serializer should have correct nullable value") {
-    val df1 = Seq(1, 2, 3, 4).toDF
+    val df1 = Seq(1, 2, 3, 4).toDF()
     assert(df1.schema(0).nullable == false)
-    val df2 = Seq(Integer.valueOf(1), Integer.valueOf(2)).toDF
+    val df2 = Seq(Integer.valueOf(1), Integer.valueOf(2)).toDF()
     assert(df2.schema(0).nullable)
 
-    val df3 = Seq(Seq(1, 2), Seq(3, 4)).toDF
+    val df3 = Seq(Seq(1, 2), Seq(3, 4)).toDF()
     assert(df3.schema(0).nullable)
     assert(df3.schema(0).dataType.asInstanceOf[ArrayType].containsNull == false)
-    val df4 = Seq(Seq("a", "b"), Seq("c", "d")).toDF
+    val df4 = Seq(Seq("a", "b"), Seq("c", "d")).toDF()
     assert(df4.schema(0).nullable)
     assert(df4.schema(0).dataType.asInstanceOf[ArrayType].containsNull)
 
@@ -1686,7 +1686,7 @@
     assert(df10.schema(0).dataType.asInstanceOf[MapType].valueContainsNull)
 
     val df11 = Seq(TestDataPoint(1, 2.2, "a", null),
-                   TestDataPoint(3, 4.4, "null", (TestDataPoint2(33, "b")))).toDF
+      TestDataPoint(3, 4.4, "null", (TestDataPoint2(33, "b")))).toDF()
     assert(df11.schema(0).nullable == false)
     assert(df11.schema(1).nullable == false)
     assert(df11.schema(2).nullable)
@@ -1802,11 +1802,11 @@
     val arrayLong = Array(1.toLong, 2.toLong, 3.toLong)
     val arrayDouble = Array(1.1, 2.2, 3.3)
     val arrayString = Array("a", "b", "c")
-    val dsByte = sparkContext.parallelize(Seq(arrayByte), 1).toDS.map(e => e)
-    val dsInt = sparkContext.parallelize(Seq(arrayInt), 1).toDS.map(e => e)
-    val dsLong = sparkContext.parallelize(Seq(arrayLong), 1).toDS.map(e => e)
-    val dsDouble = sparkContext.parallelize(Seq(arrayDouble), 1).toDS.map(e => e)
-    val dsString = sparkContext.parallelize(Seq(arrayString), 1).toDS.map(e => e)
+    val dsByte = sparkContext.parallelize(Seq(arrayByte), 1).toDS().map(e => e)
+    val dsInt = sparkContext.parallelize(Seq(arrayInt), 1).toDS().map(e => e)
+    val dsLong = sparkContext.parallelize(Seq(arrayLong), 1).toDS().map(e => e)
+    val dsDouble = sparkContext.parallelize(Seq(arrayDouble), 1).toDS().map(e => e)
+    val dsString = sparkContext.parallelize(Seq(arrayString), 1).toDS().map(e => e)
     checkDataset(dsByte, arrayByte)
     checkDataset(dsInt, arrayInt)
     checkDataset(dsLong, arrayLong)
@@ -1826,41 +1826,41 @@
 
   test("SPARK-18717: code generation works for both scala.collection.Map" +
     " and scala.collection.immutable.Map") {
-    val ds = Seq(WithImmutableMap("hi", Map(42L -> "foo"))).toDS
+    val ds = Seq(WithImmutableMap("hi", Map(42L -> "foo"))).toDS()
     checkDataset(ds.map(t => t), WithImmutableMap("hi", Map(42L -> "foo")))
 
-    val ds2 = Seq(WithMap("hi", Map(42L -> "foo"))).toDS
+    val ds2 = Seq(WithMap("hi", Map(42L -> "foo"))).toDS()
     checkDataset(ds2.map(t => t), WithMap("hi", Map(42L -> "foo")))
   }
 
   test("SPARK-18746: add implicit encoder for BigDecimal, date, timestamp") {
     // For this implicit encoder, 18 is the default scale
-    assert(spark.range(1).map { x => new java.math.BigDecimal(1) }.head ==
+    assert(spark.range(1).map { x => new java.math.BigDecimal(1) }.head() ==
       new java.math.BigDecimal(1).setScale(18))
 
-    assert(spark.range(1).map { x => scala.math.BigDecimal(1, 18) }.head ==
+    assert(spark.range(1).map { x => scala.math.BigDecimal(1, 18) }.head() ==
       scala.math.BigDecimal(1, 18))
 
-    assert(spark.range(1).map { x => java.sql.Date.valueOf("2016-12-12") }.head ==
+    assert(spark.range(1).map { x => java.sql.Date.valueOf("2016-12-12") }.head() ==
       java.sql.Date.valueOf("2016-12-12"))
 
-    assert(spark.range(1).map { x => new java.sql.Timestamp(100000) }.head ==
+    assert(spark.range(1).map { x => new java.sql.Timestamp(100000) }.head() ==
       new java.sql.Timestamp(100000))
   }
 
   test("SPARK-19896: cannot have circular references in case class") {
     val errMsg1 = intercept[UnsupportedOperationException] {
-      Seq(CircularReferenceClassA(null)).toDS
+      Seq(CircularReferenceClassA(null)).toDS()
     }
     assert(errMsg1.getMessage.startsWith("cannot have circular references in class, but got the " +
       "circular reference of class"))
     val errMsg2 = intercept[UnsupportedOperationException] {
-      Seq(CircularReferenceClassC(null)).toDS
+      Seq(CircularReferenceClassC(null)).toDS()
     }
     assert(errMsg2.getMessage.startsWith("cannot have circular references in class, but got the " +
       "circular reference of class"))
     val errMsg3 = intercept[UnsupportedOperationException] {
-      Seq(CircularReferenceClassD(null)).toDS
+      Seq(CircularReferenceClassD(null)).toDS()
     }
     assert(errMsg3.getMessage.startsWith("cannot have circular references in class, but got the " +
       "circular reference of class"))
@@ -2035,12 +2035,12 @@
 
   test("SPARK-24569: Option of primitive types are mistakenly mapped to struct type") {
     withSQLConf(SQLConf.CROSS_JOINS_ENABLED.key -> "true") {
-      val a = Seq(Some(1)).toDS
-      val b = Seq(Some(1.2)).toDS
-      val expected = Seq((Some(1), Some(1.2))).toDS
+      val a = Seq(Some(1)).toDS()
+      val b = Seq(Some(1.2)).toDS()
+      val expected = Seq((Some(1), Some(1.2))).toDS()
       val joined = a.joinWith(b, lit(true))
       assert(joined.schema == expected.schema)
-      checkDataset(joined, expected.collect: _*)
+      checkDataset(joined, expected.collect(): _*)
     }
   }
 
@@ -2186,7 +2186,7 @@
 
   test("SPARK-8288: class with only a companion object constructor") {
     val data = Seq(ScroogeLikeExample(1), ScroogeLikeExample(2))
-    val ds = data.toDS
+    val ds = data.toDS()
     checkDataset(ds, data: _*)
     checkAnswer(ds.select("x"), Seq(Row(1), Row(2)))
   }
@@ -2227,10 +2227,10 @@
 
   test("implicit encoder for LocalDate and Instant") {
     val localDate = java.time.LocalDate.of(2019, 3, 30)
-    assert(spark.range(1).map { _ => localDate }.head === localDate)
+    assert(spark.range(1).map { _ => localDate }.head() === localDate)
 
     val instant = java.time.Instant.parse("2019-03-30T09:54:00Z")
-    assert(spark.range(1).map { _ => instant }.head === instant)
+    assert(spark.range(1).map { _ => instant }.head() === instant)
   }
 
   val dotColumnTestModes = Table(
@@ -2241,7 +2241,7 @@
 
   test("SPARK-25153: Improve error messages for columns with dots/periods") {
     forAll(dotColumnTestModes) { (caseSensitive, colName) =>
-      val ds = Seq(SpecialCharClass("1", "2")).toDS
+      val ds = Seq(SpecialCharClass("1", "2")).toDS()
       withSQLConf(SQLConf.CASE_SENSITIVE.key -> caseSensitive) {
         val colName = if (caseSensitive == "true") "`Field`.`1`" else "`field`.`1`"
         checkError(
@@ -2257,7 +2257,7 @@
 
   test("SPARK-39783: Fix error messages for columns with dots/periods") {
     forAll(dotColumnTestModes) { (caseSensitive, colName) =>
-      val ds = Seq(SpecialCharClass("1", "2")).toDS
+      val ds = Seq(SpecialCharClass("1", "2")).toDS()
       withSQLConf(SQLConf.CASE_SENSITIVE.key -> caseSensitive) {
         checkError(
           exception = intercept[AnalysisException] {
@@ -2352,9 +2352,9 @@
     assert(df1.sameSemantics(df3) === false)
     assert(df3.sameSemantics(df4) === true)
 
-    assert(df1.semanticHash === df2.semanticHash)
-    assert(df1.semanticHash !== df3.semanticHash)
-    assert(df3.semanticHash === df4.semanticHash)
+    assert(df1.semanticHash() === df2.semanticHash())
+    assert(df1.semanticHash() !== df3.semanticHash())
+    assert(df3.semanticHash() === df4.semanticHash())
   }
 
   test("SPARK-31854: Invoke in MapElementsExec should not propagate null") {
@@ -2428,12 +2428,12 @@
 
   test("SPARK-34605: implicit encoder for java.time.Duration") {
     val duration = java.time.Duration.ofMinutes(10)
-    assert(spark.range(1).map { _ => duration }.head === duration)
+    assert(spark.range(1).map { _ => duration }.head() === duration)
   }
 
   test("SPARK-34615: implicit encoder for java.time.Period") {
     val period = java.time.Period.ofYears(9999).withMonths(11)
-    assert(spark.range(1).map { _ => period }.head === period)
+    assert(spark.range(1).map { _ => period }.head() === period)
   }
 
   test("SPARK-35652: joinWith on two table generated from same one performing a cartesian join," +
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
index 555679e..50dcb9d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DynamicPartitionPruningSuite.scala
@@ -1658,7 +1658,7 @@
   test("no partition pruning when the build side is a stream") {
     withTable("fact") {
       val input = MemoryStream[Int]
-      val stream = input.toDF.select($"value" as "one", ($"value" * 3) as "code")
+      val stream = input.toDF().select($"value" as "one", ($"value" * 3) as "code")
       spark.range(100).select(
         $"id",
         ($"id" + 1).as("one"),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ExplainSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/ExplainSuite.scala
index a206e97..8b5ffe5 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/ExplainSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/ExplainSuite.scala
@@ -423,7 +423,7 @@
   }
 
   test("Dataset.toExplainString has mode as string") {
-    val df = spark.range(10).toDF
+    val df = spark.range(10).toDF()
     def assertExplainOutput(mode: ExplainMode): Unit = {
       assert(df.queryExecution.explainString(mode).replaceAll("#\\d+", "#x").trim ===
         getNormalizedExplain(df, mode).trim)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
index 9327548..fc68f27 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
@@ -284,7 +284,7 @@
       val textDir = new File(dir, "text").getCanonicalPath
       checkError(
         exception = intercept[AnalysisException] {
-          Seq(1).toDF.write.text(textDir)
+          Seq(1).toDF().write.text(textDir)
         },
         errorClass = "UNSUPPORTED_DATA_TYPE_FOR_DATASOURCE",
         parameters = Map(
@@ -295,7 +295,7 @@
 
       checkError(
         exception = intercept[AnalysisException] {
-          Seq(1.2).toDF.write.text(textDir)
+          Seq(1.2).toDF().write.text(textDir)
         },
         errorClass = "UNSUPPORTED_DATA_TYPE_FOR_DATASOURCE",
         parameters = Map(
@@ -306,7 +306,7 @@
 
       checkError(
         exception = intercept[AnalysisException] {
-          Seq(true).toDF.write.text(textDir)
+          Seq(true).toDF().write.text(textDir)
         },
         errorClass = "UNSUPPORTED_DATA_TYPE_FOR_DATASOURCE",
         parameters = Map(
@@ -350,7 +350,7 @@
       )
 
       // read path
-      Seq("aaa").toDF.write.mode("overwrite").text(textDir)
+      Seq("aaa").toDF().write.mode("overwrite").text(textDir)
       checkError(
         exception = intercept[AnalysisException] {
           val schema = StructType(StructField("a", IntegerType, true) :: Nil)
@@ -802,7 +802,7 @@
         withTempPath { dir =>
           val path = dir.getCanonicalPath
           spark.range(10).write.orc(path)
-          val row = spark.read.orc(path).select(input_file_name).first()
+          val row = spark.read.orc(path).select(input_file_name()).first()
           assert(row.getString(0).contains(path))
         }
       }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala b/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala
index 6d5a0dc..8556ccf 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala
@@ -223,7 +223,7 @@
           // in case data has more than maxRecordsPerFile, split into multiple writers to improve
           // datagen speed files will be truncated to maxRecordsPerFile value, so the final
           // result will be the same.
-          val numRows = data.count
+          val numRows = data.count()
           val maxRecordPerFile = spark.conf.get(SQLConf.MAX_RECORDS_PER_FILE)
 
           if (maxRecordPerFile > 0 && numRows > maxRecordPerFile) {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/GeneratorFunctionSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/GeneratorFunctionSuite.scala
index e228d47..c55d8b7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/GeneratorFunctionSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/GeneratorFunctionSuite.scala
@@ -442,7 +442,7 @@
   test("SPARK-30998: Unsupported nested inner generators") {
     checkError(
       exception = intercept[AnalysisException] {
-        sql("SELECT array(array(1, 2), array(3)) v").select(explode(explode($"v"))).collect
+        sql("SELECT array(array(1, 2), array(3)) v").select(explode(explode($"v"))).collect()
       },
       errorClass = "UNSUPPORTED_GENERATOR.NESTED_IN_EXPRESSIONS",
       parameters = Map("expression" -> "\"explode(explode(v))\""))
@@ -509,12 +509,12 @@
   }
 
   test("SPARK-39061: inline should handle null struct") {
-    testNullStruct
+    testNullStruct()
   }
 
   test("SPARK-39496: inline eval path should handle null struct") {
     withSQLConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key -> "false") {
-      testNullStruct
+      testNullStruct()
     }
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/IntervalFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/IntervalFunctionsSuite.scala
index c7e307b..0cbc15e 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/IntervalFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/IntervalFunctionsSuite.scala
@@ -28,7 +28,7 @@
 
   test("SPARK-36022: Respect interval fields in extract") {
     yearMonthIntervalTypes.foreach { dtype =>
-      val ymDF = Seq(Period.of(1, 2, 0)).toDF.select($"value" cast dtype as "value")
+      val ymDF = Seq(Period.of(1, 2, 0)).toDF().select($"value" cast dtype as "value")
         .select($"value" cast dtype as "value")
       val expectedMap = Map("year" -> 1, "month" -> 2)
       YM.yearMonthFields.foreach { field =>
@@ -45,7 +45,7 @@
     }
 
     dayTimeIntervalTypes.foreach { dtype =>
-      val dtDF = Seq(Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)).toDF
+      val dtDF = Seq(Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)).toDF()
         .select($"value" cast dtype as "value")
       val expectedMap = Map("day" -> 1, "hour" -> 2, "minute" -> 3, "second" -> 4)
       DT.dayTimeFields.foreach { field =>
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala
index 51e66f4..5effa2e 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala
@@ -940,7 +940,7 @@
       val json_tuple_result = Seq(s"""{"test":"$str"}""").toDF("json")
         .withColumn("result", json_tuple($"json", "test"))
         .select($"result")
-        .as[String].head.length
+        .as[String].head().length
       assert(json_tuple_result === len)
     }
   }
@@ -1284,7 +1284,7 @@
   }
 
   test("SPARK-35982: from_json/to_json for map types where value types are year-month intervals") {
-    val ymDF = Seq(Period.of(1, 2, 0)).toDF
+    val ymDF = Seq(Period.of(1, 2, 0)).toDF()
     Seq(
       (YearMonthIntervalType(), """{"key":"INTERVAL '1-2' YEAR TO MONTH"}""", Period.of(1, 2, 0)),
       (YearMonthIntervalType(YEAR), """{"key":"INTERVAL '1' YEAR"}""", Period.of(1, 0, 0)),
@@ -1308,7 +1308,7 @@
   }
 
   test("SPARK-35983: from_json/to_json for map types where value types are day-time intervals") {
-    val dtDF = Seq(Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)).toDF
+    val dtDF = Seq(Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)).toDF()
     Seq(
       (DayTimeIntervalType(), """{"key":"INTERVAL '1 02:03:04' DAY TO SECOND"}""",
         Duration.ofDays(1).plusHours(2).plusMinutes(3).plusSeconds(4)),
@@ -1350,7 +1350,7 @@
 
   test("SPARK-36491: Make from_json/to_json to handle timestamp_ntz type properly") {
     val localDT = LocalDateTime.parse("2021-08-12T15:16:23")
-    val df = Seq(localDT).toDF
+    val df = Seq(localDT).toDF()
     val toJsonDF = df.select(to_json(map(lit("key"), $"value")) as "json")
     checkAnswer(toJsonDF, Row("""{"key":"2021-08-12T15:16:23.000"}"""))
     val fromJsonDF = toJsonDF
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/LateralColumnAliasSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/LateralColumnAliasSuite.scala
index cc4aeb4..a82c818 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/LateralColumnAliasSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/LateralColumnAliasSuite.scala
@@ -899,14 +899,14 @@
   test("Leaf expression as aggregate expressions should be eligible to lift up") {
     // literal
     sql(s"select 1, avg(salary) as m, m + 1 from $testTable group by dept")
-      .queryExecution.assertAnalyzed
+      .queryExecution.assertAnalyzed()
     // leaf expression current_date, now and etc
     sql(s"select current_date(), max(salary) as m, m + 1 from $testTable group by dept")
-      .queryExecution.assertAnalyzed
+      .queryExecution.assertAnalyzed()
     sql("select dateadd(month, 5, current_date()), min(salary) as m, m + 1 as n " +
-      s"from $testTable group by dept").queryExecution.assertAnalyzed
+      s"from $testTable group by dept").queryExecution.assertAnalyzed()
     sql(s"select now() as n, dateadd(day, -1, n) from $testTable group by name")
-      .queryExecution.assertAnalyzed
+      .queryExecution.assertAnalyzed()
   }
 
   test("Aggregate expressions containing no aggregate or grouping expressions still resolves") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ProductAggSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/ProductAggSuite.scala
index 7fff530..0dbc40b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/ProductAggSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/ProductAggSuite.scala
@@ -69,7 +69,7 @@
 
     val prodFactorials = data16.withColumn("f", product(col("x")).over(win)).orderBy(col("x"))
 
-    assert(prodFactorials.count === 16)
+    assert(prodFactorials.count() === 16)
 
     checkAnswer(
       prodFactorials.limit(5),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index 30a6ec6..09db772 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -283,7 +283,7 @@
   }
 
   test("SPARK-43522: Fix creating struct column name with index of array") {
-    val df = Seq("a=b,c=d,d=f").toDF.withColumn("key_value", split('value, ","))
+    val df = Seq("a=b,c=d,d=f").toDF().withColumn("key_value", split('value, ","))
       .withColumn("map_entry", transform(col("key_value"), x => struct(split(x, "=")
         .getItem(0), split(x, "=").getItem(1)))).select("map_entry")
 
@@ -2545,7 +2545,7 @@
   test("SPARK-18053: ARRAY equality is broken") {
     withTable("array_tbl") {
       spark.range(10).select(array($"id").as("arr")).write.saveAsTable("array_tbl")
-      assert(sql("SELECT * FROM array_tbl where arr = ARRAY(1L)").count == 1)
+      assert(sql("SELECT * FROM array_tbl where arr = ARRAY(1L)").count() == 1)
     }
   }
 
@@ -2881,7 +2881,7 @@
     withTable("fact_stats", "dim_stats") {
       val factData = Seq((1, 1, 99, 1), (2, 2, 99, 2), (3, 1, 99, 3), (4, 2, 99, 4))
       val storeData = Seq((1, "BW", "DE"), (2, "AZ", "US"))
-      spark.udf.register("filterND", udf((value: Int) => value > 2).asNondeterministic)
+      spark.udf.register("filterND", udf((value: Int) => value > 2).asNondeterministic())
       factData.toDF("date_id", "store_id", "product_id", "units_sold")
         .write.mode("overwrite").partitionBy("store_id").format("parquet").saveAsTable("fact_stats")
       storeData.toDF("store_id", "state_province", "country")
@@ -2938,14 +2938,14 @@
       val distributeExprs = (0 until 100).map(c => s"id$c").mkString(",")
       df.selectExpr(columns : _*).createTempView("spark_25084")
       assert(
-        spark.sql(s"select * from spark_25084 distribute by ($distributeExprs)").count === count)
+        spark.sql(s"select * from spark_25084 distribute by ($distributeExprs)").count() === count)
     }
   }
 
   test("SPARK-25144 'distinct' causes memory leak") {
-    val ds = List(Foo(Some("bar"))).toDS
-    val result = ds.flatMap(_.bar).distinct
-    result.rdd.isEmpty
+    val ds = List(Foo(Some("bar"))).toDS()
+    val result = ds.flatMap(_.bar).distinct()
+    result.rdd.isEmpty()
   }
 
   test("SPARK-25454: decimal division with negative scale") {
@@ -4249,7 +4249,7 @@
 
   test("SPARK-35749: Parse multiple unit fields interval literals as day-time interval types") {
     def evalAsSecond(query: String): Long = {
-      spark.sql(query).map(_.getAs[Duration](0)).collect.head.getSeconds
+      spark.sql(query).map(_.getAs[Duration](0)).collect().head.getSeconds
     }
 
     Seq(
@@ -4272,7 +4272,7 @@
 
   test("SPARK-35749: Parse multiple unit fields interval literals as year-month interval types") {
     def evalAsYearAndMonth(query: String): (Int, Int) = {
-      val result = spark.sql(query).map(_.getAs[Period](0)).collect.head
+      val result = spark.sql(query).map(_.getAs[Period](0)).collect().head
       (result.getYears, result.getMonths)
     }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SSBQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SSBQuerySuite.scala
index 8df91c6..6a08acb 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SSBQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SSBQuerySuite.scala
@@ -26,7 +26,7 @@
 class SSBQuerySuite extends BenchmarkQueryTest {
 
   override def beforeAll(): Unit = {
-    super.beforeAll
+    super.beforeAll()
 
     sql(
       """
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SerializationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SerializationSuite.scala
index 3ca21a3..e621980 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SerializationSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SerializationSuite.scala
@@ -24,12 +24,12 @@
 class SerializationSuite extends SparkFunSuite with SharedSparkSession {
 
   test("[SPARK-5235] SQLContext should be serializable") {
-    val spark = SparkSession.builder.getOrCreate()
+    val spark = SparkSession.builder().getOrCreate()
     new JavaSerializer(new SparkConf()).newInstance().serialize(spark.sqlContext)
   }
 
   test("[SPARK-26409] SQLConf should be serializable") {
-    val spark = SparkSession.builder.getOrCreate()
+    val spark = SparkSession.builder().getOrCreate()
     new JavaSerializer(new SparkConf()).newInstance().serialize(spark.sessionState.conf)
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala
index 0e7c294..90082c9 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SparkSessionBuilderSuite.scala
@@ -301,7 +301,7 @@
 
     val error = intercept[SparkException] {
       session.range(1).foreach { v =>
-        SparkSession.builder.master("local").getOrCreate()
+        SparkSession.builder().master("local").getOrCreate()
         ()
       }
     }.getMessage()
@@ -313,7 +313,7 @@
     val session = SparkSession.builder().master("local-cluster[3, 1, 1024]").getOrCreate()
 
     session.range(1).foreach { v =>
-      SparkSession.builder.master("local")
+      SparkSession.builder().master("local")
         .config(EXECUTOR_ALLOW_SPARK_CONTEXT.key, true).getOrCreate().stop()
       ()
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/StringFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/StringFunctionsSuite.scala
index 422498a..179f407 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/StringFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/StringFunctionsSuite.scala
@@ -812,7 +812,7 @@
     )
     checkError(
       exception = intercept[SparkRuntimeException] {
-        sql("select regexp_extract('', '[a\\\\d]{0, 2}', 1)").collect
+        sql("select regexp_extract('', '[a\\\\d]{0, 2}', 1)").collect()
       },
       errorClass = "INVALID_PARAMETER_VALUE.PATTERN",
       parameters = Map(
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala
index 4fab10c..d82fba8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SubquerySuite.scala
@@ -1197,7 +1197,7 @@
 
   test("SPARK-23316: AnalysisException after max iteration reached for IN query") {
     // before the fix this would throw AnalysisException
-    spark.range(10).where("(id,id) in (select id, null from range(3))").count
+    spark.range(10).where("(id,id) in (select id, null from range(3))").count()
   }
 
   test("SPARK-24085 scalar subquery in partitioning expression") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala
index 0670ade..814cf2f 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/UDFSuite.scala
@@ -377,7 +377,7 @@
       spark.udf.register("f", (a: Int) => a)
       val outputStream = new java.io.ByteArrayOutputStream()
       Console.withOut(outputStream) {
-        spark.sql("SELECT f(a._1) FROM x").show
+        spark.sql("SELECT f(a._1) FROM x").show()
       }
       assert(outputStream.toString.contains("f(a._1)"))
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/api/r/SQLUtilsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/api/r/SQLUtilsSuite.scala
index 3fb5a4a..0fb5ad6 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/api/r/SQLUtilsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/api/r/SQLUtilsSuite.scala
@@ -27,7 +27,7 @@
     val df = Seq(
       (1, 2, 3),
       (4, 5, 6)
-    ).toDF
+    ).toDF()
     assert(SQLUtils.dfToCols(df) === Array(
       Array(1, 4),
       Array(2, 5),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
index 64a9411..3cbbc37 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/connector/DataSourceV2SQLSuite.scala
@@ -116,14 +116,14 @@
       val df1 = sql(s"DESCRIBE $t id")
       assert(df1.schema.map(field => (field.name, field.dataType))
         === Seq(("info_name", StringType), ("info_value", StringType)))
-      assert(df1.collect === Seq(
+      assert(df1.collect() === Seq(
         Row("col_name", "id"),
         Row("data_type", "bigint"),
         Row("comment", "NULL")))
       val df2 = sql(s"DESCRIBE $t data")
       assert(df2.schema.map(field => (field.name, field.dataType))
         === Seq(("info_name", StringType), ("info_value", StringType)))
-      assert(df2.collect === Seq(
+      assert(df2.collect() === Seq(
         Row("col_name", "data"),
         Row("data_type", "string"),
         Row("comment", "hello")))
@@ -149,7 +149,7 @@
         val df = sql(s"DESCRIBE $t $col")
         assert(df.schema.map(field => (field.name, field.dataType))
           === Seq(("info_name", StringType), ("info_value", StringType)))
-        assert(df.collect === Seq(
+        assert(df.collect() === Seq(
           Row("col_name", "id"),
           Row("data_type", "bigint"),
           Row("comment", "NULL")))
@@ -399,11 +399,11 @@
       val describe = spark.sql(s"DESCRIBE $identifier")
       val part1 = describe
         .filter("col_name = 'Part 0'")
-        .select("data_type").head.getString(0)
+        .select("data_type").head().getString(0)
       assert(part1 === "id")
       val part2 = describe
         .filter("col_name = 'Part 1'")
-        .select("data_type").head.getString(0)
+        .select("data_type").head().getString(0)
       assert(part2 === "bucket(4, data1, data2, data3, data4)")
     }
   }
@@ -423,11 +423,11 @@
       val describe = spark.sql(s"DESCRIBE $identifier")
       val part1 = describe
         .filter("col_name = 'Part 0'")
-        .select("data_type").head.getString(0)
+        .select("data_type").head().getString(0)
       assert(part1 === "id")
       val part2 = describe
         .filter("col_name = 'Part 1'")
-        .select("data_type").head.getString(0)
+        .select("data_type").head().getString(0)
       assert(part2 === "sorted_bucket(data1, data2, 4, data3, data4)")
     }
   }
@@ -441,7 +441,7 @@
           "AS SELECT id FROM source")
         val location = spark.sql(s"DESCRIBE EXTENDED $identifier")
           .filter("col_name = 'Location'")
-          .select("data_type").head.getString(0)
+          .select("data_type").head().getString(0)
         assert(location === "file:/tmp/foo")
       }
     }
@@ -458,7 +458,7 @@
           "AS SELECT id FROM source")
         val location = spark.sql(s"DESCRIBE EXTENDED $identifier")
           .filter("col_name = 'Location'")
-          .select("data_type").head.getString(0)
+          .select("data_type").head().getString(0)
         assert(location === "file:/tmp/foo")
       }
     }
@@ -1743,7 +1743,7 @@
         .add("catalog", StringType, nullable = false)
         .add("namespace", StringType, nullable = false)
       val df = sql("SHOW CURRENT NAMESPACE")
-      val rows = df.collect
+      val rows = df.collect()
 
       assert(df.schema === schema)
       assert(rows.length == 1)
@@ -1973,15 +1973,15 @@
       val describe = spark.sql(s"DESCRIBE $identifier")
       val part1 = describe
         .filter("col_name = 'Part 0'")
-        .select("data_type").head.getString(0)
+        .select("data_type").head().getString(0)
       assert(part1 === "a")
       val part2 = describe
         .filter("col_name = 'Part 1'")
-        .select("data_type").head.getString(0)
+        .select("data_type").head().getString(0)
       assert(part2 === "b")
       val part3 = describe
         .filter("col_name = 'Part 2'")
-        .select("data_type").head.getString(0)
+        .select("data_type").head().getString(0)
       assert(part3 === "sorted_bucket(c, d, 4, e, f)")
     }
   }
@@ -2082,7 +2082,7 @@
         parameters = Map(
           "table" -> "testcat.ns1.ns2.tbl",
           "filters" -> "[id = 2, id = id]"))
-      assert(spark.table(t).count === 3)
+      assert(spark.table(t).count() === 3)
     }
   }
 
@@ -2775,18 +2775,18 @@
 
     val df = sql("SHOW CATALOGS")
     assert(df.schema === schema)
-    assert(df.collect === Array(Row("spark_catalog")))
+    assert(df.collect() === Array(Row("spark_catalog")))
 
     sql("use testcat")
     sql("use testpart")
     sql("use testcat2")
-    assert(sql("SHOW CATALOGS").collect === Array(
+    assert(sql("SHOW CATALOGS").collect() === Array(
       Row("spark_catalog"), Row("testcat"), Row("testcat2"), Row("testpart")))
 
-    assert(sql("SHOW CATALOGS LIKE 'test*'").collect === Array(
+    assert(sql("SHOW CATALOGS LIKE 'test*'").collect() === Array(
       Row("testcat"), Row("testcat2"), Row("testpart")))
 
-    assert(sql("SHOW CATALOGS LIKE 'testcat*'").collect === Array(
+    assert(sql("SHOW CATALOGS LIKE 'testcat*'").collect() === Array(
       Row("testcat"), Row("testcat2")))
   }
 
@@ -2902,9 +2902,9 @@
       sql(s"INSERT INTO $t2 VALUES (3)")
       sql(s"INSERT INTO $t2 VALUES (4)")
 
-      assert(sql("SELECT * FROM t VERSION AS OF 'Snapshot123456789'").collect
+      assert(sql("SELECT * FROM t VERSION AS OF 'Snapshot123456789'").collect()
         === Array(Row(1), Row(2)))
-      assert(sql("SELECT * FROM t VERSION AS OF 2345678910").collect
+      assert(sql("SELECT * FROM t VERSION AS OF 2345678910").collect()
         === Array(Row(3), Row(4)))
     }
 
@@ -2928,27 +2928,28 @@
       sql(s"INSERT INTO $t4 VALUES (7)")
       sql(s"INSERT INTO $t4 VALUES (8)")
 
-      assert(sql("SELECT * FROM t TIMESTAMP AS OF '2019-01-29 00:37:58'").collect
+      assert(sql("SELECT * FROM t TIMESTAMP AS OF '2019-01-29 00:37:58'").collect()
         === Array(Row(5), Row(6)))
-      assert(sql("SELECT * FROM t TIMESTAMP AS OF '2021-01-29 00:00:00'").collect
+      assert(sql("SELECT * FROM t TIMESTAMP AS OF '2021-01-29 00:00:00'").collect()
         === Array(Row(7), Row(8)))
-      assert(sql(s"SELECT * FROM t TIMESTAMP AS OF $ts1InSeconds").collect
+      assert(sql(s"SELECT * FROM t TIMESTAMP AS OF $ts1InSeconds").collect()
         === Array(Row(5), Row(6)))
-      assert(sql(s"SELECT * FROM t TIMESTAMP AS OF $ts2InSeconds").collect
+      assert(sql(s"SELECT * FROM t TIMESTAMP AS OF $ts2InSeconds").collect()
         === Array(Row(7), Row(8)))
-      assert(sql(s"SELECT * FROM t FOR SYSTEM_TIME AS OF $ts1InSeconds").collect
+      assert(sql(s"SELECT * FROM t FOR SYSTEM_TIME AS OF $ts1InSeconds").collect()
         === Array(Row(5), Row(6)))
-      assert(sql(s"SELECT * FROM t FOR SYSTEM_TIME AS OF $ts2InSeconds").collect
+      assert(sql(s"SELECT * FROM t FOR SYSTEM_TIME AS OF $ts2InSeconds").collect()
         === Array(Row(7), Row(8)))
-      assert(sql("SELECT * FROM t TIMESTAMP AS OF make_date(2021, 1, 29)").collect
+      assert(sql("SELECT * FROM t TIMESTAMP AS OF make_date(2021, 1, 29)").collect()
         === Array(Row(7), Row(8)))
-      assert(sql("SELECT * FROM t TIMESTAMP AS OF to_timestamp('2021-01-29 00:00:00')").collect
+      assert(sql("SELECT * FROM t TIMESTAMP AS OF to_timestamp('2021-01-29 00:00:00')").collect()
         === Array(Row(7), Row(8)))
       // Scalar subquery is also supported.
-      assert(sql("SELECT * FROM t TIMESTAMP AS OF (SELECT make_date(2021, 1, 29))").collect
+      assert(sql("SELECT * FROM t TIMESTAMP AS OF (SELECT make_date(2021, 1, 29))").collect()
         === Array(Row(7), Row(8)))
       // Nested subquery also works
-      assert(sql("SELECT * FROM t TIMESTAMP AS OF (SELECT (SELECT make_date(2021, 1, 29)))").collect
+      assert(
+        sql("SELECT * FROM t TIMESTAMP AS OF (SELECT (SELECT make_date(2021, 1, 29)))").collect()
         === Array(Row(7), Row(8)))
 
       checkError(
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTests.scala b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTests.scala
index 82a7d11..eeef056 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTests.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/connector/DeleteFromTests.scala
@@ -80,7 +80,7 @@
         sql(s"DELETE FROM $t WHERE id IN (SELECT id FROM $t)")
       }
 
-      assert(spark.table(t).count === 3)
+      assert(spark.table(t).count() === 3)
       assert(exc.getMessage.contains("Delete by condition with subquery is not supported"))
     }
   }
@@ -94,7 +94,7 @@
         sql(s"DELETE FROM $t WHERE id > 3 AND p > 3")
       }
 
-      assert(spark.table(t).count === 3)
+      assert(spark.table(t).count() === 3)
       assert(exc.getMessage.contains(s"Cannot delete from table $t"))
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionErrorsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionErrorsSuite.scala
index d133270..78bbabb 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionErrorsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionErrorsSuite.scala
@@ -103,7 +103,7 @@
     val encryptedEmptyText24 = "9RDK70sHNzqAFRcpfGM5gQ=="
     val encryptedEmptyText32 = "j9IDsCvlYXtcVJUf4FAjQQ=="
 
-    val df1 = Seq("Spark", "").toDF
+    val df1 = Seq("Spark", "").toDF()
     val df2 = Seq(
       (encryptedText16, encryptedText24, encryptedText32),
       (encryptedEmptyText16, encryptedEmptyText24, encryptedEmptyText32)
@@ -117,7 +117,7 @@
     def checkInvalidKeyLength(df: => DataFrame, inputBytes: Int): Unit = {
       checkError(
         exception = intercept[SparkException] {
-          df.collect
+          df.collect()
         }.getCause.asInstanceOf[SparkRuntimeException],
         errorClass = "INVALID_PARAMETER_VALUE.AES_KEY_LENGTH",
         parameters = Map(
@@ -154,7 +154,7 @@
       ("value32", "12345678123456781234567812345678")).foreach { case (colName, key) =>
       checkError(
         exception = intercept[SparkException] {
-          df2.selectExpr(s"aes_decrypt(unbase64($colName), binary('$key'), 'ECB')").collect
+          df2.selectExpr(s"aes_decrypt(unbase64($colName), binary('$key'), 'ECB')").collect()
         }.getCause.asInstanceOf[SparkRuntimeException],
         errorClass = "INVALID_PARAMETER_VALUE.AES_CRYPTO_ERROR",
         parameters = Map("parameter" -> "`expr`, `key`",
@@ -172,7 +172,7 @@
     def checkUnsupportedMode(df: => DataFrame, mode: String, padding: String): Unit = {
       checkError(
         exception = intercept[SparkException] {
-          df.collect
+          df.collect()
         }.getCause.asInstanceOf[SparkRuntimeException],
         errorClass = "UNSUPPORTED_FEATURE.AES_MODE",
         parameters = Map("mode" -> mode,
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/BaseScriptTransformationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/BaseScriptTransformationSuite.scala
index bfbbf2f..a07d206 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/BaseScriptTransformationSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/BaseScriptTransformationSuite.scala
@@ -614,7 +614,7 @@
       ).toDF("a", "b")
       df.createTempView("v")
 
-      if (defaultSerDe == "hive-serde") {
+      if (defaultSerDe() == "hive-serde") {
         checkAnswer(sql(
           """
             |SELECT TRANSFORM(a, b)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/QueryExecutionSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/QueryExecutionSuite.scala
index 5265095..bacd098 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/QueryExecutionSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/QueryExecutionSuite.scala
@@ -44,7 +44,7 @@
 
   def checkDumpedPlans(path: String, expected: Int): Unit = Utils.tryWithResource(
     Source.fromFile(path)) { source =>
-    assert(source.getLines.toList
+    assert(source.getLines().toList
       .takeWhile(_ != "== Whole Stage Codegen ==") == List(
       "== Parsed Logical Plan ==",
       s"Range (0, $expected, step=1, splits=Some(2))",
@@ -252,20 +252,20 @@
 
     val showTables = ShowTables(UnresolvedNamespace(Seq.empty[String]), None)
     val showTablesQe = qe(showTables, mockCallback1)
-    showTablesQe.assertAnalyzed
-    mockCallback1.assertAnalyzed
+    showTablesQe.assertAnalyzed()
+    mockCallback1.assertAnalyzed()
     assert(showTablesQe.commandExecuted.isInstanceOf[CommandResult])
-    mockCallback1.assertCommandExecuted
+    mockCallback1.assertCommandExecuted()
     assert(showTablesQe.executedPlan.isInstanceOf[CommandResultExec])
     val showTablesResultExec = showTablesQe.executedPlan.asInstanceOf[CommandResultExec]
     assert(showTablesResultExec.commandPhysicalPlan.isInstanceOf[ShowTablesExec])
 
     val project = Project(showTables.output, SubqueryAlias("s", showTables))
     val projectQe = qe(project, mockCallback2)
-    projectQe.assertAnalyzed
-    mockCallback2.assertAnalyzed
+    projectQe.assertAnalyzed()
+    mockCallback2.assertAnalyzed()
     assert(projectQe.commandExecuted.isInstanceOf[Project])
-    mockCallback2.assertCommandExecuted
+    mockCallback2.assertCommandExecuted()
     assert(projectQe.commandExecuted.children.length == 1)
     assert(projectQe.commandExecuted.children(0).isInstanceOf[SubqueryAlias])
     assert(projectQe.commandExecuted.children(0).children.length == 1)
@@ -284,28 +284,28 @@
       showTables,
       new QueryPlanningTracker(Some(mockCallback)),
       CommandExecutionMode.SKIP)
-    showTablesQe.assertAnalyzed
-    mockCallback.assertAnalyzed
-    showTablesQe.assertOptimized
-    mockCallback.assertOptimized
-    showTablesQe.assertSparkPlanPrepared
-    mockCallback.assertSparkPlanPrepared
-    showTablesQe.assertExecutedPlanPrepared
-    mockCallback.assertExecutedPlanPrepared
+    showTablesQe.assertAnalyzed()
+    mockCallback.assertAnalyzed()
+    showTablesQe.assertOptimized()
+    mockCallback.assertOptimized()
+    showTablesQe.assertSparkPlanPrepared()
+    mockCallback.assertSparkPlanPrepared()
+    showTablesQe.assertExecutedPlanPrepared()
+    mockCallback.assertExecutedPlanPrepared()
   }
 
   test("SPARK-44145: Plan setReadyForExecution") {
     val mockCallback = MockCallback()
     val plan: LogicalPlan = org.apache.spark.sql.catalyst.plans.logical.Range(0, 1, 1, 1)
     val df = Dataset.ofRows(spark, plan, new QueryPlanningTracker(Some(mockCallback)))
-    df.queryExecution.assertAnalyzed
-    mockCallback.assertAnalyzed
-    df.queryExecution.assertOptimized
-    mockCallback.assertOptimized
-    df.queryExecution.assertSparkPlanPrepared
-    mockCallback.assertSparkPlanPrepared
-    df.queryExecution.assertExecutedPlanPrepared
-    mockCallback.assertExecutedPlanPrepared
+    df.queryExecution.assertAnalyzed()
+    mockCallback.assertAnalyzed()
+    df.queryExecution.assertOptimized()
+    mockCallback.assertOptimized()
+    df.queryExecution.assertSparkPlanPrepared()
+    mockCallback.assertSparkPlanPrepared()
+    df.queryExecution.assertExecutedPlanPrepared()
+    mockCallback.assertExecutedPlanPrepared()
   }
 
   test("SPARK-35378: Return UnsafeRow in CommandResultExecCheck execute methods") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala
index 9e9d717..b5bac80 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/RemoveRedundantProjectsSuite.scala
@@ -246,7 +246,7 @@
 
           val df =
             spark.read.format(format).load(path.getCanonicalPath).filter($"i" > 0).orderBy($"i")
-          assert(df.collect === Array(Row(1, 1), Row(2, 2)))
+          assert(df.collect() === Array(Row(1, 1), Row(2, 2)))
         }
       }
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/SQLExecutionSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/SQLExecutionSuite.scala
index 766f495..48860f3 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/SQLExecutionSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/SQLExecutionSuite.scala
@@ -49,7 +49,7 @@
   }
 
   test("concurrent query execution with fork-join pool (SPARK-13747)") {
-    val spark = SparkSession.builder
+    val spark = SparkSession.builder()
       .master("local[*]")
       .appName("test")
       .getOrCreate()
@@ -69,7 +69,7 @@
    * Trigger SPARK-10548 by mocking a parent and its child thread executing queries concurrently.
    */
   private def testConcurrentQueryExecution(sc: SparkContext): Unit = {
-    val spark = SparkSession.builder.getOrCreate()
+    val spark = SparkSession.builder().getOrCreate()
     import spark.implicits._
 
     // Initialize local properties. This is necessary for the test to pass.
@@ -103,7 +103,7 @@
 
 
   test("Finding QueryExecution for given executionId") {
-    val spark = SparkSession.builder.master("local[*]").appName("test").getOrCreate()
+    val spark = SparkSession.builder().master("local[*]").appName("test").getOrCreate()
     import spark.implicits._
 
     var queryExecution: QueryExecution = null
@@ -205,7 +205,7 @@
   }
 
   test("SPARK-44591: jobTags property") {
-    val spark = SparkSession.builder.master("local[*]").appName("test").getOrCreate()
+    val spark = SparkSession.builder().master("local[*]").appName("test").getOrCreate()
     val jobTag = "jobTag"
     try {
       spark.sparkContext.addJobTag(jobTag)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala
index 5a413c7..08db88b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/WholeStageCodegenSuite.scala
@@ -743,7 +743,7 @@
         p.isInstanceOf[WholeStageCodegenExec] &&
           p.asInstanceOf[WholeStageCodegenExec].codegenStageId == 0),
         "codegen stage IDs should be preserved through ReuseExchange")
-      checkAnswer(join, df.toDF)
+      checkAnswer(join, df.toDF())
     }
   }
 
@@ -825,7 +825,7 @@
     // Case1: LocalTableScanExec is the root of a query plan tree.
     // In this case, WholeStageCodegenExec should not be inserted
     // as the direct parent of LocalTableScanExec.
-    val df = Seq(1, 2, 3).toDF
+    val df = Seq(1, 2, 3).toDF()
     val rootOfExecutedPlan = df.queryExecution.executedPlan
 
     // Ensure WholeStageCodegenExec is not inserted and
@@ -836,7 +836,7 @@
     // Case2: The parent of a LocalTableScanExec supports WholeStageCodegen.
     // In this case, the LocalTableScanExec should be within a WholeStageCodegen domain
     // and no more InputAdapter is inserted as the direct parent of the LocalTableScanExec.
-    val aggregatedDF = Seq(1, 2, 3).toDF.groupBy("value").sum()
+    val aggregatedDF = Seq(1, 2, 3).toDF().groupBy("value").sum()
     val executedPlan = aggregatedDF.queryExecution.executedPlan
 
     // HashAggregateExec supports WholeStageCodegen and it's the parent of
@@ -863,7 +863,7 @@
           // Tet case with keys
           "SELECT k, AVG(v) FROM VALUES((1, 1)) t(k, v) GROUP BY k").foreach { query =>
           val e = intercept[IllegalStateException] {
-            sql(query).collect
+            sql(query).collect()
           }
           assert(e.getMessage.contains(expectedErrMsg))
         }
@@ -885,7 +885,7 @@
           "SELECT k, AVG(a + b), SUM(a + b + c) FROM VALUES((1, 1, 1, 1)) t(k, a, b, c) " +
             "GROUP BY k").foreach { query =>
           val e = intercept[IllegalStateException] {
-            sql(query).collect
+            sql(query).collect()
           }
           assert(e.getMessage.contains(expectedErrMsg))
         }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
index 406b3ed..0ced0f8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/adaptive/AdaptiveQueryExecSuite.scala
@@ -1311,8 +1311,8 @@
         SQLConf.COALESCE_PARTITIONS_INITIAL_PARTITION_NUM.key -> "10",
         SQLConf.SHUFFLE_PARTITIONS.key -> "10") {
 
-        val df1 = spark.range(10).toDF.repartitionByRange($"id".asc)
-        val df2 = spark.range(10).toDF.repartitionByRange(($"id" + 1).asc)
+        val df1 = spark.range(10).toDF().repartitionByRange($"id".asc)
+        val df2 = spark.range(10).toDF().repartitionByRange(($"id" + 1).asc)
 
         val partitionsNum1 = df1.rdd.collectPartitions().length
         val partitionsNum2 = df2.rdd.collectPartitions().length
@@ -1344,7 +1344,7 @@
           SQLConf.COALESCE_PARTITIONS_INITIAL_PARTITION_NUM.key -> "10",
           SQLConf.SHUFFLE_PARTITIONS.key -> "10") {
 
-          spark.range(10).toDF.createTempView("test")
+          spark.range(10).toDF().createTempView("test")
 
           val df1 = spark.sql("SELECT /*+ REPARTITION(id) */ * from test")
           val df2 = spark.sql("SELECT /*+ REPARTITION_BY_RANGE(id) */ * from test")
@@ -2851,7 +2851,7 @@
     val aggDf1 = emptyDf.agg(sum("id").as("id")).withColumn("name", lit("df1"))
     val aggDf2 = emptyDf.agg(sum("id").as("id")).withColumn("name", lit("df2"))
     val unionDF = aggDf1.union(aggDf2)
-    checkAnswer(unionDF.select("id").distinct, Seq(Row(null)))
+    checkAnswer(unionDF.select("id").distinct(), Seq(Row(null)))
   }
 }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/aggregate/SortBasedAggregationStoreSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/aggregate/SortBasedAggregationStoreSuite.scala
index 4a0c88b..eea2cb0 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/aggregate/SortBasedAggregationStoreSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/aggregate/SortBasedAggregationStoreSuite.scala
@@ -78,7 +78,7 @@
       groupingSchema,
       updateInputRow,
       mergeAggBuffer,
-      createNewAggregationBuffer)
+      createNewAggregationBuffer())
 
     (5000 to 100000).foreach { _ =>
       randomKV(inputRow, group)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/BloomFilterBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/BloomFilterBenchmark.scala
index 1cb9874..523da0d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/BloomFilterBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/BloomFilterBenchmark.scala
@@ -40,7 +40,7 @@
 
   private val scaleFactor = 100
   private val N = scaleFactor * 1000 * 1000
-  private val df = spark.range(N).map(_ => Random.nextInt)
+  private val df = spark.range(N).map(_ => Random.nextInt())
 
   private def writeORCBenchmark(): Unit = {
     withTempPath { dir =>
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala
index 62bd85d..771f944 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/DataSourceReadBenchmark.scala
@@ -55,7 +55,7 @@
       .setIfMissing("spark.driver.memory", "3g")
       .setIfMissing("spark.executor.memory", "3g")
 
-    val sparkSession = SparkSession.builder.config(conf).getOrCreate()
+    val sparkSession = SparkSession.builder().config(conf).getOrCreate()
 
     // Set default configs. Individual cases will change them if necessary.
     sparkSession.conf.set(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key, "true")
@@ -135,7 +135,7 @@
     withTempPath { dir =>
       withTempTable("t1", "csvTable", "jsonTable", "parquetV1Table", "parquetV2Table", "orcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql(s"SELECT CAST(value as ${dataType.sql}) id FROM t1"))
 
@@ -280,7 +280,7 @@
     withTempPath { dir =>
       withTempTable("t1", "parquetV1Table", "parquetV2Table", "orcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(dir,
           spark.sql(s"SELECT named_struct('f', CAST(value as ${dataType.sql})) as col FROM t1"),
@@ -338,7 +338,7 @@
     withTempPath { dir =>
       withTempTable("t1", "parquetV1Table", "parquetV2Table", "orcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).map { x =>
+        spark.range(values).map(_ => Random.nextLong()).map { x =>
           val arrayOfStructColumn = (0 until 5).map(i => (x + i, s"$x" * 5))
           val mapOfStructColumn = Map(
             s"$x" -> (x * 0.1, (x, s"$x" * 100)),
@@ -404,7 +404,7 @@
     withTempPath { dir =>
       withTempTable("t1", "csvTable", "jsonTable", "parquetV1Table", "parquetV2Table", "orcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(
           dir,
@@ -453,7 +453,7 @@
     withTempPath { dir =>
       withTempTable("t1", "csvTable", "jsonTable", "parquetV1Table", "parquetV2Table", "orcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(
           dir,
@@ -502,7 +502,7 @@
     withTempPath { dir =>
       withTempTable("t1", "csvTable", "jsonTable", "parquetV1Table", "parquetV2Table", "orcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT value % 2 AS p, value AS id FROM t1"), Some("p"))
 
@@ -703,7 +703,7 @@
         import spark.implicits._
         val middle = width / 2
         val selectExpr = (1 to width).map(i => s"value as c$i")
-        spark.range(values).map(_ => Random.nextLong).toDF()
+        spark.range(values).map(_ => Random.nextLong()).toDF()
           .selectExpr(selectExpr: _*).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT * FROM t1"))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
index b572444..4862571 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/FilterPushdownBenchmark.scala
@@ -74,7 +74,7 @@
     } else {
       monotonically_increasing_id()
     }
-    val df = spark.range(numRows).map(_ => Random.nextLong).selectExpr(selectExpr: _*)
+    val df = spark.range(numRows).map(_ => Random.nextLong()).selectExpr(selectExpr: _*)
       .withColumn("value", valueCol)
       .sort("value")
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/MiscBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/MiscBenchmark.scala
index ad7850e..796c56d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/MiscBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/MiscBenchmark.scala
@@ -126,7 +126,7 @@
         import spark.implicits._
         val df = spark.sparkContext.parallelize(Seq(("1",
           Array.fill(M)({
-            val i = math.random
+            val i = math.random()
             (i.toString, (i + 1).toString, (i + 2).toString, (i + 3).toString)
           })))).toDF("col", "arr")
 
@@ -139,7 +139,7 @@
           import spark.implicits._
           val df = spark.sparkContext.parallelize(Seq(("1",
             Array.fill(M)({
-              val i = math.random
+              val i = math.random()
               (i.toString, (i + 1).toString, (i + 2).toString, (i + 3).toString)
             })))).toDF("col", "arr")
             .selectExpr("col", "struct(col, arr) as st")
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/PrimitiveArrayBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/PrimitiveArrayBenchmark.scala
index c967615..a09a64d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/PrimitiveArrayBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/PrimitiveArrayBenchmark.scala
@@ -33,7 +33,7 @@
 object PrimitiveArrayBenchmark extends SqlBasedBenchmark {
 
   override def getSparkSession: SparkSession = {
-    SparkSession.builder
+    SparkSession.builder()
       .master("local[1]")
       .appName("microbenchmark")
       .config("spark.sql.shuffle.partitions", 1)
@@ -54,24 +54,24 @@
 
     val sc = spark.sparkContext
     val primitiveIntArray = Array.fill[Int](count)(65535)
-    val dsInt = sc.parallelize(Seq(primitiveIntArray), 1).toDS
-    dsInt.count  // force to build dataset
+    val dsInt = sc.parallelize(Seq(primitiveIntArray), 1).toDS()
+    dsInt.count()  // force to build dataset
     val intArray = { i: Int =>
       var n = 0
       var len = 0
       while (n < iters) {
-        len += dsInt.map(e => e).queryExecution.toRdd.collect.length
+        len += dsInt.map(e => e).queryExecution.toRdd.collect().length
         n += 1
       }
     }
     val primitiveDoubleArray = Array.fill[Double](count)(65535.0)
-    val dsDouble = sc.parallelize(Seq(primitiveDoubleArray), 1).toDS
-    dsDouble.count  // force to build dataset
+    val dsDouble = sc.parallelize(Seq(primitiveDoubleArray), 1).toDS()
+    dsDouble.count()  // force to build dataset
     val doubleArray = { i: Int =>
       var n = 0
       var len = 0
       while (n < iters) {
-        len += dsDouble.map(e => e).queryExecution.toRdd.collect.length
+        len += dsDouble.map(e => e).queryExecution.toRdd.collect().length
         n += 1
       }
     }
@@ -79,6 +79,6 @@
     val benchmark = new Benchmark("Write an array in Dataset", count * iters, output = output)
     benchmark.addCase("Int   ")(intArray)
     benchmark.addCase("Double")(doubleArray)
-    benchmark.run
+    benchmark.run()
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/TPCDSQueryBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/TPCDSQueryBenchmark.scala
index fe89916..c26272d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/TPCDSQueryBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/TPCDSQueryBenchmark.scala
@@ -60,7 +60,7 @@
       .set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
       .set("spark.kryo.registrationRequired", "true")
 
-    SparkSession.builder.config(conf).getOrCreate()
+    SparkSession.builder().config(conf).getOrCreate()
   }
 
   val tables = Seq("catalog_page", "catalog_returns", "customer", "customer_address",
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/UnsafeArrayDataBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/UnsafeArrayDataBenchmark.scala
index 9b09564..d84fa5e 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/UnsafeArrayDataBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/UnsafeArrayDataBenchmark.scala
@@ -49,12 +49,12 @@
     val count = 1024 * 1024 * 16
     val rand = new Random(42)
     val intArrayToRow = intEncoder.createSerializer()
-    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt }
+    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt() }
     val intUnsafeArray = intArrayToRow(intPrimitiveArray).getArray(0)
     val readIntArray = { i: Int =>
       var n = 0
       while (n < iters) {
-        val len = intUnsafeArray.numElements
+        val len = intUnsafeArray.numElements()
         var sum = 0
         var i = 0
         while (i < len) {
@@ -65,13 +65,13 @@
       }
     }
 
-    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble }
+    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble() }
     val doubleArrayToRow = doubleEncoder.createSerializer()
     val doubleUnsafeArray = doubleArrayToRow(doublePrimitiveArray).getArray(0)
     val readDoubleArray = { i: Int =>
       var n = 0
       while (n < iters) {
-        val len = doubleUnsafeArray.numElements
+        val len = doubleUnsafeArray.numElements()
         var sum = 0.0
         var i = 0
         while (i < len) {
@@ -85,7 +85,7 @@
     val benchmark = new Benchmark("Read UnsafeArrayData", count * iters, output = output)
     benchmark.addCase("Int")(readIntArray)
     benchmark.addCase("Double")(readDoubleArray)
-    benchmark.run
+    benchmark.run()
   }
 
   def writeUnsafeArray(iters: Int): Unit = {
@@ -93,7 +93,7 @@
     val rand = new Random(42)
 
     var intTotalLength: Int = 0
-    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt }
+    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt() }
     val intArrayToRow = intEncoder.createSerializer()
     val writeIntArray = { i: Int =>
       var len = 0
@@ -106,7 +106,7 @@
     }
 
     var doubleTotalLength: Int = 0
-    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble }
+    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble() }
     val doubleArrayToRow = doubleEncoder.createSerializer()
     val writeDoubleArray = { i: Int =>
       var len = 0
@@ -121,7 +121,7 @@
     val benchmark = new Benchmark("Write UnsafeArrayData", count * iters, output = output)
     benchmark.addCase("Int")(writeIntArray)
     benchmark.addCase("Double")(writeDoubleArray)
-    benchmark.run
+    benchmark.run()
   }
 
   def getPrimitiveArray(iters: Int): Unit = {
@@ -129,28 +129,28 @@
     val rand = new Random(42)
 
     var intTotalLength: Int = 0
-    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt }
+    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt() }
     val intArrayToRow = intEncoder.createSerializer()
     val intUnsafeArray = intArrayToRow(intPrimitiveArray).getArray(0)
     val readIntArray = { i: Int =>
       var len = 0
       var n = 0
       while (n < iters) {
-        len += intUnsafeArray.toIntArray.length
+        len += intUnsafeArray.toIntArray().length
         n += 1
       }
       intTotalLength = len
     }
 
     var doubleTotalLength: Int = 0
-    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble }
+    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble() }
     val doubleArrayToRow = doubleEncoder.createSerializer()
     val doubleUnsafeArray = doubleArrayToRow(doublePrimitiveArray).getArray(0)
     val readDoubleArray = { i: Int =>
       var len = 0
       var n = 0
       while (n < iters) {
-        len += doubleUnsafeArray.toDoubleArray.length
+        len += doubleUnsafeArray.toDoubleArray().length
         n += 1
       }
       doubleTotalLength = len
@@ -160,7 +160,7 @@
       new Benchmark("Get primitive array from UnsafeArrayData", count * iters, output = output)
     benchmark.addCase("Int")(readIntArray)
     benchmark.addCase("Double")(readDoubleArray)
-    benchmark.run
+    benchmark.run()
   }
 
   def putPrimitiveArray(iters: Int): Unit = {
@@ -168,7 +168,7 @@
     val rand = new Random(42)
 
     var intTotalLen: Int = 0
-    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt }
+    val intPrimitiveArray = Array.fill[Int](count) { rand.nextInt() }
     val createIntArray = { i: Int =>
       var len = 0
       var n = 0
@@ -180,7 +180,7 @@
     }
 
     var doubleTotalLen: Int = 0
-    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble }
+    val doublePrimitiveArray = Array.fill[Double](count) { rand.nextDouble() }
     val createDoubleArray = { i: Int =>
       var len = 0
       var n = 0
@@ -195,7 +195,7 @@
       new Benchmark("Create UnsafeArrayData from primitive array", count * iters, output = output)
     benchmark.addCase("Int")(createIntArray)
     benchmark.addCase("Double")(createDoubleArray)
-    benchmark.run
+    benchmark.run()
   }
 
   override def runBenchmarkSuite(mainArgs: Array[String]): Unit = {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/WideSchemaBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/WideSchemaBenchmark.scala
index eb8d41e..2ef4985 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/WideSchemaBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/WideSchemaBenchmark.scala
@@ -89,7 +89,7 @@
     for (width <- widthsToTest) {
       val selectExpr = (1 to width).map(i => s"id as a_$i")
       benchmark.addCase(s"$width select expressions") { iter =>
-        spark.range(1).toDF.selectExpr(selectExpr: _*)
+        spark.range(1).toDF().selectExpr(selectExpr: _*)
       }
     }
     benchmark.run()
@@ -114,7 +114,7 @@
       // normalize by width to keep constant data size
       val numRows = scaleFactor / width
       val selectExpr = (1 to width).map(i => s"id as a_$i")
-      val df = spark.range(numRows).toDF.selectExpr(selectExpr: _*).cache()
+      val df = spark.range(numRows).toDF().selectExpr(selectExpr: _*).cache()
       df.count()  // force caching
       addCases(benchmark, df, s"$width cols x $numRows rows", "a_1")
     }
@@ -209,7 +209,7 @@
     for (width <- widthsToTest) {
       val numRows = scaleFactor / width
       val datum = Tuple1((1 to width).map(i => ("value_" + i -> 1)).toMap)
-      val df = spark.range(numRows).map(_ => datum).toDF.cache()
+      val df = spark.range(numRows).map(_ => datum).toDF().cache()
       df.count()  // force caching
       addCases(benchmark, df, s"$width wide x $numRows rows", "_1[\"value_1\"]")
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/columnar/InMemoryColumnarQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/columnar/InMemoryColumnarQuerySuite.scala
index de04938..78f8372 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/columnar/InMemoryColumnarQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/columnar/InMemoryColumnarQuerySuite.scala
@@ -167,9 +167,9 @@
 
   test("access only some column of the all of columns") {
     val df = spark.range(1, 100).map(i => (i, (i + 1).toFloat)).toDF("i", "f")
-    df.cache
-    df.count  // forced to build cache
-    assert(df.filter("f <= 10.0").count == 9)
+    df.cache()
+    df.count()  // forced to build cache
+    assert(df.filter("f <= 10.0").count() == 9)
   }
 
   test("SPARK-1436 regression: in-memory columns must be able to be accessed multiple times") {
@@ -365,7 +365,7 @@
   }
 
    test("cached row count should be calculated") {
-    val data = spark.range(6).toDF
+    val data = spark.range(6).toDF()
     val plan = spark.sessionState.executePlan(data.logicalPlan).sparkPlan
     val cached = InMemoryRelation(new TestCachedBatchSerializer(true, 5),
       MEMORY_ONLY, plan, None, data.logicalPlan)
@@ -390,7 +390,7 @@
       }
       val rdd = sparkContext.makeRDD(Seq(Row.fromSeq(data)))
       val df = spark.createDataFrame(rdd, StructType(schemas))
-      val row = df.persist.take(1).apply(0)
+      val row = df.persist().take(1).apply(0)
       checkAnswer(df, row)
     }
   }
@@ -410,7 +410,7 @@
       )
       val rdd = sparkContext.makeRDD(Seq(Row.fromSeq(data)))
       val df = spark.createDataFrame(rdd, StructType(schemas))
-      val row = df.persist.take(1).apply(0)
+      val row = df.persist().take(1).apply(0)
       checkAnswer(df, row)
     }
   }
@@ -432,16 +432,16 @@
       )
       val rdd = sparkContext.makeRDD(Seq(Row.fromSeq(data)))
       val df = spark.createDataFrame(rdd, StructType(schemas))
-      val row = df.persist.take(1).apply(0)
+      val row = df.persist().take(1).apply(0)
       checkAnswer(df, row)
     }
   }
 
   test("InMemoryTableScanExec should return correct output ordering and partitioning") {
-    val df1 = Seq((0, 0), (1, 1)).toDF
-      .repartition(col("_1")).sortWithinPartitions(col("_1")).persist
-    val df2 = Seq((0, 0), (1, 1)).toDF
-      .repartition(col("_1")).sortWithinPartitions(col("_1")).persist
+    val df1 = Seq((0, 0), (1, 1)).toDF()
+      .repartition(col("_1")).sortWithinPartitions(col("_1")).persist()
+    val df2 = Seq((0, 0), (1, 1)).toDF()
+      .repartition(col("_1")).sortWithinPartitions(col("_1")).persist()
 
     // Because two cached dataframes have the same logical plan, this is a self-join actually.
     // So we force one of in-memory relation to alias its output. Then we can test if original and
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/command/CreateNamespaceSuiteBase.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/command/CreateNamespaceSuiteBase.scala
index 7c5df7f..bfc32a7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/command/CreateNamespaceSuiteBase.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/command/CreateNamespaceSuiteBase.scala
@@ -126,7 +126,7 @@
             .toDF("k", "v")
             .where("k='Properties'")
             .where("v=''")
-            .count == 1, s"$key is a reserved namespace property and ignored")
+            .count() == 1, s"$key is a reserved namespace property and ignored")
           val meta =
             getCatalog(catalog).asNamespaceCatalog.loadNamespaceMetadata(namespaceArray)
           assert(meta.get(key) == null || !meta.get(key).contains("foo"),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileIndexSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileIndexSuite.scala
index b019381..418bff6 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileIndexSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileIndexSuite.scala
@@ -167,11 +167,11 @@
 
       val catalog1 = new InMemoryFileIndex(
         spark, Seq(unqualifiedDirPath), Map.empty, None)
-      assert(catalog1.allFiles.map(_.getPath) === Seq(qualifiedFilePath))
+      assert(catalog1.allFiles().map(_.getPath) === Seq(qualifiedFilePath))
 
       val catalog2 = new InMemoryFileIndex(
         spark, Seq(unqualifiedFilePath), Map.empty, None)
-      assert(catalog2.allFiles.map(_.getPath) === Seq(qualifiedFilePath))
+      assert(catalog2.allFiles().map(_.getPath) === Seq(qualifiedFilePath))
 
     }
   }
@@ -541,7 +541,7 @@
     when(dfs.listLocatedStatus(path)).thenReturn(new RemoteIterator[LocatedFileStatus] {
       val iter = statuses.iterator
       override def hasNext: Boolean = iter.hasNext
-      override def next(): LocatedFileStatus = iter.next
+      override def next(): LocatedFileStatus = iter.next()
     })
     val fileIndex = new TestInMemoryFileIndex(spark, path)
     assert(fileIndex.leafFileStatuses.toSeq == statuses)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceAggregatePushDownSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceAggregatePushDownSuite.scala
index 317abd5..67ec3cc 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceAggregatePushDownSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileSourceAggregatePushDownSuite.scala
@@ -212,7 +212,7 @@
           "  min(id), p FROM tmp group by p"
         var expected = Array.empty[Row]
         withSQLConf(aggPushDownEnabledKey -> "false") {
-            expected = sql(query).collect
+            expected = sql(query).collect()
         }
         Seq("false", "true").foreach { enableVectorizedReader =>
           withSQLConf(aggPushDownEnabledKey -> "true",
@@ -246,7 +246,7 @@
           " p4, p2, p3, p1 FROM tmp GROUP BY p1, p2, p3, p4"
         var expected = Array.empty[Row]
         withSQLConf(aggPushDownEnabledKey -> "false") {
-          expected = sql(query).collect
+          expected = sql(query).collect()
         }
         Seq("false", "true").foreach { enableVectorizedReader =>
           withSQLConf(aggPushDownEnabledKey -> "true",
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/PrunePartitionSuiteBase.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/PrunePartitionSuiteBase.scala
index 430e9f8..0263ae5 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/PrunePartitionSuiteBase.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/PrunePartitionSuiteBase.scala
@@ -94,9 +94,10 @@
     val plan = qe.sparkPlan
     assert(getScanExecPartitionSize(plan) == expectedPartitionCount)
 
-    val collectFn: PartialFunction[SparkPlan, Seq[Expression]] = collectPartitionFiltersFn orElse {
-      case BatchScanExec(_, scan: FileScan, _, _, _, _) => scan.partitionFilters
-    }
+    val collectFn: PartialFunction[SparkPlan, Seq[Expression]] =
+      collectPartitionFiltersFn() orElse {
+        case BatchScanExec(_, scan: FileScan, _, _, _, _) => scan.partitionFilters
+      }
     val pushedDownPartitionFilters = plan.collectFirst(collectFn)
       .map(exps => exps.filterNot(e => e.isInstanceOf[IsNotNull]))
     val pushedFilters = pushedDownPartitionFilters.map(filters => {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala
index bf496d6..0a0b23d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaPruningSuite.scala
@@ -966,7 +966,7 @@
             |  {"itemId": 2, "itemData": "b"}
             |]}
             |""".stripMargin
-        val df = spark.read.json(Seq(jsonStr).toDS)
+        val df = spark.read.json(Seq(jsonStr).toDS())
         makeDataSourceFile(df, new File(path))
 
         spark.read.format(dataSourceName).load(path)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala
index 38fbf46..111e88d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala
@@ -95,7 +95,7 @@
     val numRows = if (withHeader) numCars else numCars + 1
     // schema
     assert(df.schema.fieldNames.length === numColumns)
-    assert(df.count === numRows)
+    assert(df.count() === numRows)
 
     if (checkHeader) {
       if (withHeader) {
@@ -405,7 +405,7 @@
       .schema(StructType(List(StructField("column", StringType, false))))
       .load(testFile(emptyFile))
 
-    assert(result.collect.size === 0)
+    assert(result.collect().size === 0)
     assert(result.schema.fieldNames.size === 1)
   }
 
@@ -1441,7 +1441,7 @@
           .option("multiLine", multiLine)
           .schema(schema.add(columnNameOfCorruptRecord, IntegerType))
           .csv(testFile(valueMalformedFile))
-          .collect
+          .collect()
       }.getMessage
       assert(errMsg.startsWith("The field for corrupt records must be string type and nullable"))
     }
@@ -1721,7 +1721,7 @@
           .option("inferSchema", true).option("samplingRatio", 0.1)
           .option("path", path.getCanonicalPath)
           .format("csv")
-          .load
+          .load()
         assert(readback2.schema == new StructType().add("_c0", IntegerType))
       }
     })
@@ -2328,12 +2328,12 @@
 
   test("lineSep restrictions") {
     val errMsg1 = intercept[IllegalArgumentException] {
-      spark.read.option("lineSep", "").csv(testFile(carsFile)).collect
+      spark.read.option("lineSep", "").csv(testFile(carsFile)).collect()
     }.getMessage
     assert(errMsg1.contains("'lineSep' cannot be an empty string"))
 
     val errMsg2 = intercept[IllegalArgumentException] {
-      spark.read.option("lineSep", "123").csv(testFile(carsFile)).collect
+      spark.read.option("lineSep", "123").csv(testFile(carsFile)).collect()
     }.getMessage
     assert(errMsg2.contains("'lineSep' can contain only 1 character"))
   }
@@ -2374,7 +2374,7 @@
 
   test("SPARK-26208: write and read empty data to csv file with headers") {
     withTempPath { path =>
-      val df1 = spark.range(10).repartition(2).filter(_ < 0).map(_.toString).toDF
+      val df1 = spark.range(10).repartition(2).filter(_ < 0).map(_.toString).toDF()
       // we have 2 partitions but they are both empty and will be filtered out upon writing
       // thanks to SPARK-23271 one new empty partition will be inserted
       df1.write.format("csv").option("header", true).save(path.getAbsolutePath)
@@ -2407,7 +2407,7 @@
     assert(spark.read
       .option("delimiter", "|")
       .option("inferSchema", "true")
-      .csv(Seq("1,2").toDS).schema.head.dataType === StringType)
+      .csv(Seq("1,2").toDS()).schema.head.dataType === StringType)
   }
 
   test("SPARK-27873: disabling enforceSchema should not fail columnNameOfCorruptRecord") {
@@ -2651,7 +2651,7 @@
 
   test("SPARK-32025: infer the schema from mixed-type values") {
     withTempPath { path =>
-      Seq("col_mixed_types", "2012", "1997", "True").toDS.write.text(path.getCanonicalPath)
+      Seq("col_mixed_types", "2012", "1997", "True").toDS().write.text(path.getCanonicalPath)
       val df = spark.read.format("csv")
         .option("header", "true")
         .option("inferSchema", "true")
@@ -2663,7 +2663,7 @@
 
   test("SPARK-32614: don't treat rows starting with null char as comment") {
     withTempPath { path =>
-      Seq("\u0000foo", "bar", "baz").toDS.write.text(path.getCanonicalPath)
+      Seq("\u0000foo", "bar", "baz").toDS().write.text(path.getCanonicalPath)
       val df = spark.read.format("csv")
         .option("header", "false")
         .option("inferSchema", "true")
@@ -2713,7 +2713,7 @@
       spark.range(3).coalesce(1).write.csv(s"$basePath/$csvTableName")
       val readback = spark.read
         .csv(s"$basePath/${"""(\[|\]|\{|\})""".r.replaceAllIn(csvTableName, """\\$1""")}")
-      assert(readback.collect sameElements Array(Row("0"), Row("1"), Row("2")))
+      assert(readback.collect() sameElements Array(Row("0"), Row("1"), Row("2")))
     }
   }
 
@@ -2745,7 +2745,7 @@
     val bufSize = 128
     val line = "X" * (bufSize - 1) + "| |"
     withTempPath { path =>
-      Seq(line).toDF.write.text(path.getAbsolutePath)
+      Seq(line).toDF().write.text(path.getAbsolutePath)
       assert(spark.read.format("csv")
         .option("delimiter", "|")
         .option("ignoreTrailingWhiteSpace", "true").load(path.getAbsolutePath).count() == 1)
@@ -2777,7 +2777,7 @@
           StructType(
             StructField("f1", StringType, nullable = false) ::
             StructField("f2", StringType, nullable = false) :: Nil)
-        ).option("mode", "DROPMALFORMED").csv(Seq("a,", "a,b").toDS),
+        ).option("mode", "DROPMALFORMED").csv(Seq("a,", "a,b").toDS()),
         Row("a", "b"))
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
index 5096b24..f0561a3 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
@@ -1252,7 +1252,7 @@
 
       val df1 = spark.createDataFrame(rowRDD1, schema1)
       df1.createOrReplaceTempView("applySchema1")
-      val df2 = df1.toDF
+      val df2 = df1.toDF()
       val result = df2.toJSON.collect()
       // scalastyle:off
       assert(result(0) === "{\"f1\":1,\"f2\":\"A1\",\"f3\":true,\"f4\":[\"1\",\" A1\",\" true\",\" null\"]}")
@@ -1275,7 +1275,7 @@
 
       val df3 = spark.createDataFrame(rowRDD2, schema2)
       df3.createOrReplaceTempView("applySchema2")
-      val df4 = df3.toDF
+      val df4 = df3.toDF()
       val result2 = df4.toJSON.collect()
 
       assert(result2(1) === "{\"f1\":{\"f11\":2,\"f12\":false},\"f2\":{\"B2\":null}}")
@@ -1584,7 +1584,7 @@
         // inferring partitions because the original path in the "path" option will list the
         // partition directory that has been removed.
         assert(
-          spark.read.options(extraOptions).format("json").option("path", path).load.count() === 2)
+          spark.read.options(extraOptions).format("json").option("path", path).load().count() === 2)
       }
     }
   }
@@ -1663,7 +1663,7 @@
         .format("json")
         .load(jsonDir)
 
-      assert(jsonCopy.count == jsonDF.count)
+      assert(jsonCopy.count() == jsonDF.count())
       val jsonCopySome = jsonCopy.selectExpr("string", "long", "boolean")
       val jsonDFSome = jsonDF.selectExpr("string", "long", "boolean")
       checkAnswer(jsonCopySome, jsonDFSome)
@@ -1701,7 +1701,7 @@
         .options(extraOptions)
         .load(jsonDir)
 
-      assert(jsonCopy.count == jsonDF.count)
+      assert(jsonCopy.count() == jsonDF.count())
       val jsonCopySome = jsonCopy.selectExpr("string", "long", "boolean")
       val jsonDFSome = jsonDF.selectExpr("string", "long", "boolean")
       checkAnswer(jsonCopySome, jsonDFSome)
@@ -2075,7 +2075,7 @@
           .option("columnNameOfCorruptRecord", columnNameOfCorruptRecord)
           .schema(schema)
           .json(path)
-          .collect
+          .collect()
       }.getMessage
       assert(errMsg.startsWith("The field for corrupt records must be string type and nullable"))
     }
@@ -2235,7 +2235,7 @@
         // inferred when sampling ratio is involved.
         val readback2 = spark.read
           .option("samplingRatio", 0.1).option("path", path.getCanonicalPath)
-          .format("json").load
+          .format("json").load()
         assert(readback2.schema == new StructType().add("f1", LongType))
       }
     })
@@ -2662,7 +2662,7 @@
 
   private def failedOnEmptyString(dataType: DataType): Unit = {
     val df = spark.read.schema(s"a ${dataType.catalogString}")
-      .option("mode", "FAILFAST").json(Seq("""{"a":""}""").toDS)
+      .option("mode", "FAILFAST").json(Seq("""{"a":""}""").toDS())
     val e = intercept[SparkException] {df.collect()}
     checkError(
       exception = e.getCause.getCause.getCause.asInstanceOf[SparkRuntimeException],
@@ -2673,7 +2673,7 @@
 
   private def emptyString(dataType: DataType, expected: Any): Unit = {
     val df = spark.read.schema(s"a ${dataType.catalogString}")
-      .option("mode", "FAILFAST").json(Seq("""{"a":""}""").toDS)
+      .option("mode", "FAILFAST").json(Seq("""{"a":""}""").toDS())
     checkAnswer(df, Row(expected) :: Nil)
   }
 
@@ -2699,7 +2699,7 @@
   test("SPARK-25040: allowing empty strings when legacy config is enabled") {
     def emptyStringAsNull(dataType: DataType): Unit = {
       val df = spark.read.schema(s"a ${dataType.catalogString}")
-        .option("mode", "FAILFAST").json(Seq("""{"a":""}""").toDS)
+        .option("mode", "FAILFAST").json(Seq("""{"a":""}""").toDS())
       checkAnswer(df, Row(null) :: Nil)
     }
 
@@ -2741,7 +2741,7 @@
 
   test("inferring timestamp type") {
     def schemaOf(jsons: String*): StructType = {
-      spark.read.option("inferTimestamp", true).json(jsons.toDS).schema
+      spark.read.option("inferTimestamp", true).json(jsons.toDS()).schema
     }
 
     assert(schemaOf(
@@ -3127,7 +3127,7 @@
       spark.range(3).coalesce(1).write.json(s"$basePath/$jsonTableName")
       val readback = spark.read
         .json(s"$basePath/${"""(\[|\]|\{|\})""".r.replaceAllIn(jsonTableName, """\\$1""")}")
-      assert(readback.collect sameElements Array(Row(0), Row(1), Row(2)))
+      assert(readback.collect() sameElements Array(Row(0), Row(1), Row(2)))
     }
   }
 
@@ -3136,7 +3136,7 @@
     withTempPaths(2) { paths =>
       paths.foreach(_.delete())
       val seq = Seq("a", "\n", "\u3042")
-      val df = seq.toDF
+      val df = seq.toDF()
 
       val basePath1 = paths(0).getCanonicalPath
       df.write.option("writeNonAsciiCharacterAsCodePoint", "true")
@@ -3190,7 +3190,7 @@
     withSQLConf(SQLConf.LEAF_NODE_DEFAULT_PARALLELISM.key -> "1") {
       withTempPath { path =>
         val basePath = path.getCanonicalPath
-        val df = Seq("a", "b", "c").toDF
+        val df = Seq("a", "b", "c").toDF()
         df.write.option("pretty", "true").json(basePath)
 
         val expectedText =
@@ -3241,7 +3241,7 @@
           StructType(
             StructField("f1", LongType, nullable = false) ::
             StructField("f2", LongType, nullable = false) :: Nil)
-        ).option("mode", "DROPMALFORMED").json(Seq("""{"f1": 1}""").toDS),
+        ).option("mode", "DROPMALFORMED").json(Seq("""{"f1": 1}""").toDS()),
         // It is for testing legacy configuration. This is technically a bug as
         // `0` has to be `null` but the schema is non-nullable.
         Row(1, 0))
@@ -3251,7 +3251,7 @@
   test("SPARK-36379: proceed parsing with root nulls in permissive mode") {
     val exception = intercept[SparkException] {
       spark.read.option("mode", "failfast")
-        .schema("a string").json(Seq("""[{"a": "str"}, null]""").toDS).collect()
+        .schema("a string").json(Seq("""[{"a": "str"}, null]""").toDS()).collect()
     }
     assert(exception.getMessage.contains("Malformed records are detected"))
 
@@ -3265,7 +3265,7 @@
     // Here, since an array fails to parse in the middle, we will return one row.
     checkAnswer(
       spark.read.option("mode", "permissive")
-        .json(Seq("""[{"a": "str"}, null, {"a": "str"}]""").toDS),
+        .json(Seq("""[{"a": "str"}, null, {"a": "str"}]""").toDS()),
       Row(null) :: Nil)
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcQuerySuite.scala
index f12f882..39447ed 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcQuerySuite.scala
@@ -413,7 +413,7 @@
           // results. So, this checks if the number of result is less than the original count
           // of data, and then checks if it contains the expected data.
           assert(
-            sourceDf.count < 10 && expectedData.subsetOf(data),
+            sourceDf.count() < 10 && expectedData.subsetOf(data),
             s"No data was filtered for predicate: $pred")
         }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcSourceSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcSourceSuite.scala
index 024f5f6..2ed2494 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcSourceSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcSourceSuite.scala
@@ -366,7 +366,7 @@
   test("SPARK-24322 Fix incorrect workaround for bug in java.sql.Timestamp") {
     withTempPath { path =>
       val ts = Timestamp.valueOf("1900-05-05 12:34:56.000789")
-      Seq(ts).toDF.write.orc(path.getCanonicalPath)
+      Seq(ts).toDF().write.orc(path.getCanonicalPath)
       checkAnswer(spark.read.orc(path.getCanonicalPath), Row(ts))
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetEncodingSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetEncodingSuite.scala
index 65b067e..a0d11e2 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetEncodingSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetEncodingSuite.scala
@@ -58,7 +58,7 @@
   test("All Types Dictionary") {
     (1 :: 1000 :: Nil).foreach { n => {
       withTempPath { dir =>
-        List.fill(n)(ROW).toDF.repartition(1).write.parquet(dir.getCanonicalPath)
+        List.fill(n)(ROW).toDF().repartition(1).write.parquet(dir.getCanonicalPath)
         val file = TestUtils.listDirectory(dir).head
 
         val conf = sqlContext.conf
@@ -87,7 +87,7 @@
   test("All Types Null") {
     (1 :: 100 :: Nil).foreach { n => {
       withTempPath { dir =>
-        val data = List.fill(n)(NULL_ROW).toDF
+        val data = List.fill(n)(NULL_ROW).toDF()
         data.repartition(1).write.parquet(dir.getCanonicalPath)
         val file = TestUtils.listDirectory(dir).head
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileMetadataStructRowIndexSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileMetadataStructRowIndexSuite.scala
index c10e179..2465dee 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileMetadataStructRowIndexSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileMetadataStructRowIndexSuite.scala
@@ -148,7 +148,7 @@
 
           assert(df.select("*", s"${FileFormat.METADATA_NAME}.$mixedCaseRowIndex")
             .where(s"$EXPECTED_ROW_ID_COL != $mixedCaseRowIndex")
-            .count == 0)
+            .count() == 0)
         }
       }
     }
@@ -160,7 +160,7 @@
         Seq(StructField(ROW_INDEX_TEMPORARY_COLUMN_NAME, LongType))) { df =>
       assert(df
           .where(col(EXPECTED_ROW_ID_COL) === col(ROW_INDEX_TEMPORARY_COLUMN_NAME))
-          .count == NUM_ROWS)
+          .count() == NUM_ROWS)
     }
 
     // File format not supporting row index generation populates missing column with nulls.
@@ -168,7 +168,7 @@
         Seq(StructField(ROW_INDEX_TEMPORARY_COLUMN_NAME, LongType)))  { df =>
       assert(df
           .where(col(ROW_INDEX_TEMPORARY_COLUMN_NAME).isNull)
-          .count == NUM_ROWS)
+          .count() == NUM_ROWS)
     }
   }
 
@@ -180,7 +180,7 @@
       //                    ROW_INDEX_TEMPORARY_COLUMN_NAME in their schemas.
       assert(df
         .where(col(EXPECTED_ROW_ID_COL) === col(ROW_INDEX_TEMPORARY_COLUMN_NAME))
-        .count == NUM_ROWS)
+        .count() == NUM_ROWS)
 
       // Column cannot be read in combination with _metadata.row_index.
       intercept[AnalysisException](df.select("*", FileFormat.METADATA_NAME).collect())
@@ -194,7 +194,7 @@
       // Column values are set for each partition, rather than populated with generated row indexes.
       assert(df
         .where(col(EXPECTED_PARTITION_COL) === col(ROW_INDEX_TEMPORARY_COLUMN_NAME))
-        .count == NUM_ROWS)
+        .count() == NUM_ROWS)
 
       // Column cannot be read in combination with _metadata.row_index.
       intercept[AnalysisException](df.select("*", FileFormat.METADATA_NAME).collect())
@@ -230,13 +230,13 @@
 
         assert(spark
           .read.parquet(dir.getAbsolutePath)
-          .count == NUM_ROWS)
+          .count() == NUM_ROWS)
 
         // The _metadata.row_index is returning data from the file, not generated metadata.
         assert(spark
           .read.parquet(dir.getAbsolutePath)
           .select(s"${FileFormat.METADATA_NAME}.${ROW_INDEX}")
-          .distinct.count == NUM_ROWS / 10)
+          .distinct().count() == NUM_ROWS / 10)
       }
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
index 269a3ef..0d64d8f 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
@@ -791,7 +791,7 @@
           SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> INT96.toString) {
           import testImplicits._
           withTempPath { file =>
-            millisData.map(i => Tuple1(Timestamp.valueOf(i))).toDF
+            millisData.map(i => Tuple1(Timestamp.valueOf(i))).toDF()
               .write.format(dataSourceName).save(file.getCanonicalPath)
             readParquetFile(file.getCanonicalPath) { df =>
               val schema = new SparkToParquetSchemaConverter(conf).convert(df.schema)
@@ -1024,7 +1024,7 @@
           // When a filter is pushed to Parquet, Parquet can apply it to every row.
           // So, we can check the number of rows returned from the Parquet
           // to make sure our filter pushdown work.
-          assert(stripSparkFilter(df).count == 1)
+          assert(stripSparkFilter(df).count() == 1)
         }
       }
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
index 2e7b261..dc8a89c 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetQuerySuite.scala
@@ -964,7 +964,7 @@
     withAllParquetReaders {
       withTempPath { path =>
         // Repeated values for dictionary encoding.
-        Seq(Some("A"), Some("A"), None).toDF.repartition(1)
+        Seq(Some("A"), Some("A"), None).toDF().repartition(1)
           .write.parquet(path.getAbsolutePath)
         val df = spark.read.parquet(path.getAbsolutePath)
         checkAnswer(stripSparkFilter(df.where("NOT (value <=> 'A')")), df)
@@ -1305,7 +1305,7 @@
     override def userClass: Class[TestArray] = classOf[TestArray]
 
     override def deserialize(datum: Any): TestArray = datum match {
-      case value: ArrayData => TestArray(value.toLongArray.toSeq)
+      case value: ArrayData => TestArray(value.toLongArray().toSeq)
     }
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala
index 69b07e6..4bfc34a 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/joins/HashedRelationSuite.scala
@@ -759,7 +759,7 @@
       val res = new UnsafeRow(1)
       val it = map.get(1L, res)
       assert(it.hasNext)
-      assert(it.next.getLong(0) == 1)
+      assert(it.next().getLong(0) == 1)
       assert(it.hasNext != ignoresDuplicatedKey)
       map.free()
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsTestUtils.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsTestUtils.scala
index 81667d5..cae008a 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsTestUtils.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/metric/SQLMetricsTestUtils.scala
@@ -36,7 +36,7 @@
 
   protected def currentExecutionIds(): Set[Long] = {
     spark.sparkContext.listenerBus.waitUntilEmpty(10000)
-    statusStore.executionsList.map(_.executionId).toSet
+    statusStore.executionsList().map(_.executionId).toSet
   }
 
   protected def statusStore: SQLAppStatusStore = spark.sharedState.statusStore
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonUDFSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonUDFSuite.scala
index 84c23b7..3101281 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonUDFSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/python/PythonUDFSuite.scala
@@ -98,7 +98,7 @@
     df.count()
 
     val statusStore = spark.sharedState.statusStore
-    val lastExecId = statusStore.executionsList.last.executionId
+    val lastExecId = statusStore.executionsList().last.executionId
     val executionMetrics = statusStore.execution(lastExecId).get.metrics.mkString
     for (metric <- pythonSQLMetrics) {
       assert(executionMetrics.contains(metric))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/AsyncProgressTrackingMicroBatchExecutionSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/AsyncProgressTrackingMicroBatchExecutionSuite.scala
index d083cac..efb7e12 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/AsyncProgressTrackingMicroBatchExecutionSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/AsyncProgressTrackingMicroBatchExecutionSuite.scala
@@ -147,7 +147,7 @@
     def startQuery(): StreamingQuery = {
       ds.writeStream
         .foreachBatch((ds: Dataset[Row], batchId: Long) => {
-          ds.collect.foreach((row: Row) => {
+          ds.collect().foreach((row: Row) => {
             data += row.getInt(0)
           }: Unit)
           countDownLatch.countDown()
@@ -352,7 +352,7 @@
       ds.writeStream
         .trigger(trigger)
         .foreachBatch((ds: Dataset[Row], batchId: Long) => {
-          ds.collect.foreach((row: Row) => {
+          ds.collect().foreach((row: Row) => {
             data += row.getInt(0)
           }: Unit)
           countDownLatch.countDown()
@@ -512,7 +512,7 @@
       ds.writeStream
         .trigger(trigger)
         .foreachBatch((ds: Dataset[Row], batchId: Long) => {
-          ds.collect.foreach((row: Row) => {
+          ds.collect().foreach((row: Row) => {
             data += row.getInt(0)
           }: Unit)
           countDownLatch.countDown()
@@ -785,7 +785,7 @@
     def startQuery(): StreamingQuery = {
       ds.writeStream
         .foreachBatch((ds: Dataset[Row], batchId: Long) => {
-          ds.collect.foreach((row: Row) => {
+          ds.collect().foreach((row: Row) => {
             data += row.getInt(0)
           }: Unit)
         })
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManagerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManagerSuite.scala
index cbcb4a4..cdf736b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManagerSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/CheckpointFileManagerSuite.scala
@@ -122,7 +122,7 @@
       SQLConf.STREAMING_CHECKPOINT_FILE_MANAGER_CLASS.parent.key ->
         classOf[CreateAtomicTestManager].getName) {
       val fileManager =
-        CheckpointFileManager.create(new Path("/"), spark.sessionState.newHadoopConf)
+        CheckpointFileManager.create(new Path("/"), spark.sessionState.newHadoopConf())
       assert(fileManager.isInstanceOf[CreateAtomicTestManager])
     }
   }
@@ -236,5 +236,5 @@
 }
 
 private object CheckpointFileManagerSuiteFileSystem {
-  val scheme = s"CheckpointFileManagerSuiteFileSystem${math.abs(Random.nextInt)}"
+  val scheme = s"CheckpointFileManagerSuiteFileSystem${math.abs(Random.nextInt())}"
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/FileStreamSinkLogSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/FileStreamSinkLogSuite.scala
index d6707e7..d2b751d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/FileStreamSinkLogSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/FileStreamSinkLogSuite.scala
@@ -331,7 +331,7 @@
 }
 
 object CountOpenLocalFileSystem {
-  val scheme = s"FileStreamSinkLogSuite${math.abs(Random.nextInt)}fs"
+  val scheme = s"FileStreamSinkLogSuite${math.abs(Random.nextInt())}fs"
   val pathToNumOpenCalled = new ConcurrentHashMap[String, JLong]
 
   def resetCount(): Unit = pathToNumOpenCalled.clear()
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/ProcessingTimeExecutorSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/ProcessingTimeExecutorSuite.scala
index c0fd3fe3..110b562 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/ProcessingTimeExecutorSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/ProcessingTimeExecutorSuite.scala
@@ -53,7 +53,7 @@
       override def run(): Unit = {
         executor.execute(() => {
           // Record the trigger time, increment clock if needed and
-          triggerTimes.add(clock.getTimeMillis.toInt)
+          triggerTimes.add(clock.getTimeMillis().toInt)
           clock.advance(clockIncrementInTrigger)
           clockIncrementInTrigger = 0 // reset this so that there are no runaway triggers
           continueExecuting
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/sources/ForeachBatchSinkSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/sources/ForeachBatchSinkSuite.scala
index b92fa4c..b27aa37 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/sources/ForeachBatchSinkSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/sources/ForeachBatchSinkSuite.scala
@@ -34,7 +34,7 @@
 
   test("foreachBatch with non-stateful query") {
     val mem = MemoryStream[Int]
-    val ds = mem.toDS.map(_ + 1)
+    val ds = mem.toDS().map(_ + 1)
 
     val tester = new ForeachBatchTester[Int](mem)
     val writer = (ds: Dataset[Int], batchId: Long) => tester.record(batchId, ds.map(_ + 1))
@@ -47,7 +47,7 @@
 
   test("foreachBatch with non-stateful query - untyped Dataset") {
     val mem = MemoryStream[Int]
-    val ds = mem.toDF.selectExpr("value + 1 as value")
+    val ds = mem.toDF().selectExpr("value + 1 as value")
 
     val tester = new ForeachBatchTester[Row](mem)(ExpressionEncoder(ds.schema))
     val writer = (df: DataFrame, batchId: Long) =>
@@ -66,7 +66,7 @@
       .select($"value" % 2 as "key")
       .groupBy("key")
       .agg(count("*") as "value")
-      .toDF.as[KV]
+      .toDF().as[KV]
 
     val tester = new ForeachBatchTester[KV](mem)
     val writer = (batchDS: Dataset[KV], batchId: Long) => tester.record(batchId, batchDS)
@@ -84,7 +84,7 @@
       .select($"value" % 2 as "key")
       .groupBy("key")
       .agg(count("*") as "value")
-      .toDF.as[KV]
+      .toDF().as[KV]
 
     val tester = new ForeachBatchTester[KV](mem)
     val writer = (batchDS: Dataset[KV], batchId: Long) => tester.record(batchId, batchDS)
@@ -98,7 +98,7 @@
 
   test("foreachBatch with batch specific operations") {
     val mem = MemoryStream[Int]
-    val ds = mem.toDS.map(_ + 1)
+    val ds = mem.toDS().map(_ + 1)
 
     val tester = new ForeachBatchTester[Int](mem)
     val writer: (Dataset[Int], Long) => Unit = { case (df, batchId) =>
@@ -127,7 +127,7 @@
 
   test("foreachBatchSink does not affect metric generation") {
     val mem = MemoryStream[Int]
-    val ds = mem.toDS.map(_ + 1)
+    val ds = mem.toDS().map(_ + 1)
 
     val tester = new ForeachBatchTester[Int](mem)
     val writer = (ds: Dataset[Int], batchId: Long) => tester.record(batchId, ds.map(_ + 1))
@@ -139,7 +139,7 @@
   }
 
   test("throws errors in invalid situations") {
-    val ds = MemoryStream[Int].toDS
+    val ds = MemoryStream[Int].toDS()
     val ex1 = intercept[IllegalArgumentException] {
       ds.writeStream.foreachBatch(null.asInstanceOf[(Dataset[Int], Long) => Unit]).start()
     }
@@ -176,7 +176,7 @@
 
     // typed
     val mem = MemoryStream[Int]
-    val ds = mem.toDS.map(_ + 1)
+    val ds = mem.toDS().map(_ + 1)
     assertPlan(mem, ds)
 
     // untyped
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/OperatorStateMetadataSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/OperatorStateMetadataSuite.scala
index b75da90..48cc17b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/OperatorStateMetadataSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/OperatorStateMetadataSuite.scala
@@ -83,8 +83,8 @@
       val input1 = MemoryStream[Int]
       val input2 = MemoryStream[Int]
 
-      val df1 = input1.toDF.select($"value" as "key", ($"value" * 2) as "leftValue")
-      val df2 = input2.toDF.select($"value" as "key", ($"value" * 3) as "rightValue")
+      val df1 = input1.toDF().select($"value" as "key", ($"value" * 2) as "leftValue")
+      val df2 = input2.toDF().select($"value" as "key", ($"value" * 3) as "rightValue")
       val joined = df1.join(df2, "key")
 
       testStream(joined)(
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreIntegrationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreIntegrationSuite.scala
index 7adafe1..28c755b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreIntegrationSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreIntegrationSuite.scala
@@ -40,7 +40,7 @@
       val conf = Map(SQLConf.STATE_STORE_PROVIDER_CLASS.key ->
         classOf[RocksDBStateStoreProvider].getName)
 
-      testStream(input.toDF.groupBy().count(), outputMode = OutputMode.Update)(
+      testStream(input.toDF().groupBy().count(), outputMode = OutputMode.Update)(
         StartStream(checkpointLocation = dir.getAbsolutePath, additionalConfs = conf),
         AddData(input, 1, 2, 3),
         CheckAnswer(3),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreSuite.scala
index 82f677a..4ce344d4 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBStateStoreSuite.scala
@@ -75,7 +75,7 @@
 
   test("RocksDB confs are passed correctly from SparkSession to db instance") {
     val sparkConf = new SparkConf().setMaster("local").setAppName(this.getClass.getSimpleName)
-    withSparkSession(SparkSession.builder.config(sparkConf).getOrCreate()) { spark =>
+    withSparkSession(SparkSession.builder().config(sparkConf).getOrCreate()) { spark =>
       // Set the session confs that should be passed into RocksDB
       val testConfs = Seq(
         ("spark.sql.streaming.stateStore.providerClass",
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBSuite.scala
index b5e1ecc..15d35ba 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBSuite.scala
@@ -1100,7 +1100,7 @@
               db.load(0)
               db.put("a", "1")
               db.commit()
-              db.getWriteBufferManagerAndCache
+              db.getWriteBufferManagerAndCache()
             }
 
             val remoteDir2 = dir2.getCanonicalPath
@@ -1108,7 +1108,7 @@
               db.load(0)
               db.put("a", "1")
               db.commit()
-              db.getWriteBufferManagerAndCache
+              db.getWriteBufferManagerAndCache()
             }
 
             if (boundedMemoryUsage == "true") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreRDDSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreRDDSuite.scala
index c2728b9..f2a5554 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreRDDSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreRDDSuite.scala
@@ -58,8 +58,8 @@
   }
 
   test("versioning and immutability") {
-    withSparkSession(SparkSession.builder.config(sparkConf).getOrCreate()) { spark =>
-      val path = Utils.createDirectory(tempDir, Random.nextFloat.toString).toString
+    withSparkSession(SparkSession.builder().config(sparkConf).getOrCreate()) { spark =>
+      val path = Utils.createDirectory(tempDir, Random.nextFloat().toString).toString
       val rdd1 = makeRDD(spark.sparkContext, Seq(("a", 0), ("b", 0), ("a", 0)))
         .mapPartitionsWithStateStore(spark.sqlContext, operatorStateInfo(path, version = 0),
           keySchema, valueSchema, numColsPrefixKey = 0)(increment)
@@ -77,7 +77,7 @@
   }
 
   test("recovering from files") {
-    val path = Utils.createDirectory(tempDir, Random.nextFloat.toString).toString
+    val path = Utils.createDirectory(tempDir, Random.nextFloat().toString).toString
 
     def makeStoreRDD(
         spark: SparkSession,
@@ -90,22 +90,22 @@
     }
 
     // Generate RDDs and state store data
-    withSparkSession(SparkSession.builder.config(sparkConf).getOrCreate()) { spark =>
+    withSparkSession(SparkSession.builder().config(sparkConf).getOrCreate()) { spark =>
       for (i <- 1 to 20) {
         require(makeStoreRDD(spark, Seq(("a", 0)), i - 1).collect().toSet === Set(("a", 0) -> i))
       }
     }
 
     // With a new context, try using the earlier state store data
-    withSparkSession(SparkSession.builder.config(sparkConf).getOrCreate()) { spark =>
+    withSparkSession(SparkSession.builder().config(sparkConf).getOrCreate()) { spark =>
       assert(makeStoreRDD(spark, Seq(("a", 0)), 20).collect().toSet === Set(("a", 0) -> 21))
     }
   }
 
   test("usage with iterators - only gets and only puts") {
-    withSparkSession(SparkSession.builder.config(sparkConf).getOrCreate()) { spark =>
+    withSparkSession(SparkSession.builder().config(sparkConf).getOrCreate()) { spark =>
       implicit val sqlContext = spark.sqlContext
-      val path = Utils.createDirectory(tempDir, Random.nextFloat.toString).toString
+      val path = Utils.createDirectory(tempDir, Random.nextFloat().toString).toString
       val opId = 0
 
       // Returns an iterator of the incremented value made into the store
@@ -158,9 +158,9 @@
     quietly {
       val queryRunId = UUID.randomUUID
       val opId = 0
-      val path = Utils.createDirectory(tempDir, Random.nextFloat.toString).toString
+      val path = Utils.createDirectory(tempDir, Random.nextFloat().toString).toString
 
-      withSparkSession(SparkSession.builder.config(sparkConf).getOrCreate()) { spark =>
+      withSparkSession(SparkSession.builder().config(sparkConf).getOrCreate()) { spark =>
         implicit val sqlContext = spark.sqlContext
         val coordinatorRef = sqlContext.streams.stateStoreCoordinator
         val storeProviderId1 = StateStoreProviderId(StateStoreId(path, opId, 0), queryRunId)
@@ -194,11 +194,11 @@
     quietly {
 
       withSparkSession(
-        SparkSession.builder
+        SparkSession.builder()
           .config(sparkConf.setMaster("local-cluster[2, 1, 1024]"))
           .getOrCreate()) { spark =>
         implicit val sqlContext = spark.sqlContext
-        val path = Utils.createDirectory(tempDir, Random.nextFloat.toString).toString
+        val path = Utils.createDirectory(tempDir, Random.nextFloat().toString).toString
         val opId = 0
         val rdd1 = makeRDD(spark.sparkContext, Seq(("a", 0), ("b", 0), ("a", 0)))
           .mapPartitionsWithStateStore(sqlContext, operatorStateInfo(path, version = 0),
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreSuite.scala
index 067a1a3..fd7a292 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/StateStoreSuite.scala
@@ -133,7 +133,7 @@
   }
 
   test("failure after committing with MAX_BATCHES_TO_RETAIN_IN_MEMORY set to 1") {
-    tryWithProviderResource(newStoreProvider(opId = Random.nextInt, partition = 0,
+    tryWithProviderResource(newStoreProvider(opId = Random.nextInt(), partition = 0,
       numOfVersToRetainInMemory = 1)) { provider =>
 
       var currentVersion = 0
@@ -174,7 +174,7 @@
   }
 
   test("no cache data with MAX_BATCHES_TO_RETAIN_IN_MEMORY set to 0") {
-    tryWithProviderResource(newStoreProvider(opId = Random.nextInt, partition = 0,
+    tryWithProviderResource(newStoreProvider(opId = Random.nextInt(), partition = 0,
       numOfVersToRetainInMemory = 0)) { provider =>
 
       var currentVersion = 0
@@ -194,7 +194,7 @@
   }
 
   test("cleaning") {
-    tryWithProviderResource(newStoreProvider(opId = Random.nextInt, partition = 0,
+    tryWithProviderResource(newStoreProvider(opId = Random.nextInt(), partition = 0,
       minDeltasForSnapshot = 5)) { provider =>
 
       for (i <- 1 to 20) {
@@ -221,7 +221,7 @@
     conf.set("fs.defaultFS", "fake:///")
 
     tryWithProviderResource(
-      newStoreProvider(opId = Random.nextInt, partition = 0, hadoopConf = conf)) { provider =>
+      newStoreProvider(opId = Random.nextInt(), partition = 0, hadoopConf = conf)) { provider =>
 
       provider.getStore(0).commit()
       provider.getStore(0).commit()
@@ -234,7 +234,7 @@
   }
 
   test("corrupted file handling") {
-    tryWithProviderResource(newStoreProvider(opId = Random.nextInt, partition = 0,
+    tryWithProviderResource(newStoreProvider(opId = Random.nextInt(), partition = 0,
       minDeltasForSnapshot = 5)) { provider =>
 
       for (i <- 1 to 6) {
@@ -280,7 +280,7 @@
         errorClass = "CANNOT_LOAD_STATE_STORE.CANNOT_READ_DELTA_FILE_NOT_EXISTS",
         parameters = Map(
           "fileToRead" -> s"${provider.stateStoreId.storeCheckpointLocation()}/1.delta",
-          "clazz" -> s"${provider.toString}"
+          "clazz" -> s"${provider.toString()}"
         )
       )
     }
@@ -660,7 +660,7 @@
       classOf[CreateAtomicTestManager].getName)
     val remoteDir = Utils.createTempDir().getAbsolutePath
 
-    tryWithProviderResource(newStoreProvider(opId = Random.nextInt, partition = 0,
+    tryWithProviderResource(newStoreProvider(opId = Random.nextInt(), partition = 0,
       dir = remoteDir, hadoopConf = hadoopConf)) { provider =>
 
       // Disable failure of output stream and generate versions
@@ -1043,14 +1043,14 @@
       put(store, "b", 0, 2)
 
       // Updates should work while iterating of filtered entries
-      val filtered = store.iterator.filter { tuple => keyRowToData(tuple.key) == ("a", 0) }
+      val filtered = store.iterator().filter { tuple => keyRowToData(tuple.key) == ("a", 0) }
       filtered.foreach { tuple =>
         store.put(tuple.key, dataToValueRow(valueRowToData(tuple.value) + 1))
       }
       assert(get(store, "a", 0) === Some(2))
 
       // Removes should work while iterating of filtered entries
-      val filtered2 = store.iterator.filter { tuple => keyRowToData(tuple.key) == ("b", 0) }
+      val filtered2 = store.iterator().filter { tuple => keyRowToData(tuple.key) == ("b", 0) }
       filtered2.foreach { tuple => store.remove(tuple.key) }
       assert(get(store, "b", 0) === None)
     }
@@ -1252,7 +1252,7 @@
         withCoordinatorRef(sc) { coordinatorRef =>
           val dir = newDir()
           val storeId = StateStoreProviderId(StateStoreId(dir, 0, 0), UUID.randomUUID)
-          val storeConf = getDefaultStoreConf
+          val storeConf = getDefaultStoreConf()
           val hadoopConf = new Configuration()
 
           // Verify that trying to get incorrect versions throw errors
@@ -1616,5 +1616,5 @@
 }
 
 object RenameReturnsFalseFileSystem {
-  val scheme = s"StateStoreSuite${math.abs(Random.nextInt)}fs"
+  val scheme = s"StateStoreSuite${math.abs(Random.nextInt())}fs"
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/MetricsAggregationBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/MetricsAggregationBenchmark.scala
index 252bcea8..b194ce8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/MetricsAggregationBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/MetricsAggregationBenchmark.scala
@@ -128,8 +128,8 @@
 
         info.setAccumulables(accumulables)
 
-        val start = SparkListenerTaskStart(stageInfo.stageId, stageInfo.attemptNumber, info)
-        val end = SparkListenerTaskEnd(stageInfo.stageId, stageInfo.attemptNumber,
+        val start = SparkListenerTaskStart(stageInfo.stageId, stageInfo.attemptNumber(), info)
+        val end = SparkListenerTaskEnd(stageInfo.stageId, stageInfo.attemptNumber(),
           taskType = "",
           reason = null,
           info,
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListenerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListenerSuite.scala
index 67206e9..9a3313b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListenerSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLAppStatusListenerSuite.scala
@@ -694,7 +694,7 @@
       SparkPlanInfo.fromSparkPlan(df.queryExecution.executedPlan),
       time,
       Map.empty))
-    assert(statusStore.executionsCount === 2)
+    assert(statusStore.executionsCount() === 2)
     assert(statusStore.execution(2) === None)
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnVectorSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnVectorSuite.scala
index 42125c5..3cbf0bb 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnVectorSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnVectorSuite.scala
@@ -512,7 +512,7 @@
     }
 
     withVectors(16, dataType) { testVector =>
-      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build)
+      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build())
       ColumnAccessor.decompress(columnAccessor, testVector, 16)
 
       assert(testVector.isNullAt(0))
@@ -536,7 +536,7 @@
     }
 
     withVectors(16, dataType) { testVector =>
-      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build)
+      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build())
       ColumnAccessor.decompress(columnAccessor, testVector, 16)
 
       assert(testVector.isNullAt(0))
@@ -560,7 +560,7 @@
     }
 
     withVectors(16, dataType) { testVector =>
-      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build)
+      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build())
       ColumnAccessor.decompress(columnAccessor, testVector, 16)
 
       assert(testVector.isNullAt(0))
@@ -584,7 +584,7 @@
     }
 
     withVectors(16, dataType) { testVector =>
-      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build)
+      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build())
       ColumnAccessor.decompress(columnAccessor, testVector, 16)
 
       assert(testVector.isNullAt(0))
@@ -608,7 +608,7 @@
       }
 
       withVectors(16, dataType) { testVector =>
-        val columnAccessor = ColumnAccessor(dataType, columnBuilder.build)
+        val columnAccessor = ColumnAccessor(dataType, columnBuilder.build())
         ColumnAccessor.decompress(columnAccessor, testVector, 16)
 
         assert(testVector.isNullAt(0))
@@ -633,7 +633,7 @@
     }
 
     withVectors(16, dataType) { testVector =>
-      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build)
+      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build())
       ColumnAccessor.decompress(columnAccessor, testVector, 16)
 
       assert(testVector.isNullAt(0))
@@ -657,7 +657,7 @@
     }
 
     withVectors(16, dataType) { testVector =>
-      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build)
+      val columnAccessor = ColumnAccessor(dataType, columnBuilder.build())
       ColumnAccessor.decompress(columnAccessor, testVector, 16)
 
       assert(testVector.isNullAt(0))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnarBatchBenchmark.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnarBatchBenchmark.scala
index bffd006..a11b209 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnarBatchBenchmark.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnarBatchBenchmark.scala
@@ -371,7 +371,7 @@
     val benchmark = new Benchmark("String Read/Write", count * iters, output = output)
     benchmark.addCase("On Heap")(column(MemoryMode.ON_HEAP))
     benchmark.addCase("Off Heap")(column(MemoryMode.OFF_HEAP))
-    benchmark.run
+    benchmark.run()
   }
 
   def arrayAccess(iters: Int): Unit = {
@@ -442,7 +442,7 @@
     benchmark.addCase("On Heap Read Elements") { _ => readArrayElements(true) }
     benchmark.addCase("Off Heap Read Elements") { _ => readArrayElements(false) }
 
-    benchmark.run
+    benchmark.run()
   }
 
   override def runBenchmarkSuite(mainArgs: Array[String]): Unit = {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/internal/ExecutorSideSQLConfSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/internal/ExecutorSideSQLConfSuite.scala
index 81bcf7d..6149f3e 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/internal/ExecutorSideSQLConfSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/internal/ExecutorSideSQLConfSuite.scala
@@ -141,7 +141,7 @@
           Seq(true)
             .toDF()
             .mapPartitions { _ =>
-              if (TaskContext.get.getLocalProperty(confKey) == confValue) {
+              if (TaskContext.get().getLocalProperty(confKey) == confValue) {
                 Iterator(true)
               } else {
                 Iterator.empty
@@ -173,7 +173,7 @@
 
       def generateBroadcastDataFrame(confKey: String, confValue: String): Dataset[Boolean] = {
         val df = spark.range(1).mapPartitions { _ =>
-          Iterator(TaskContext.get.getLocalProperty(confKey) == confValue)
+          Iterator(TaskContext.get().getLocalProperty(confKey) == confValue)
         }
         df.hint("broadcast")
       }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
index 60785e3..5f28164 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
@@ -365,12 +365,12 @@
     // This is a test to reflect discussion in SPARK-12218.
     // The older versions of spark have this kind of bugs in parquet data source.
     val df1 = sql("SELECT * FROM foobar WHERE NOT (THEID != 2) OR NOT (NAME != 'mary')")
-    assert(df1.collect.toSet === Set(Row("mary", 2)))
+    assert(df1.collect().toSet === Set(Row("mary", 2)))
 
     // SPARK-22548: Incorrect nested AND expression pushed down to JDBC data source
     val df2 = sql("SELECT * FROM foobar " +
       "WHERE (THEID > 0 AND TRIM(NAME) = 'mary') OR (NAME = 'fred')")
-    assert(df2.collect.toSet === Set(Row("fred", 1), Row("mary", 2)))
+    assert(df2.collect().toSet === Set(Row("fred", 1), Row("mary", 2)))
 
     assert(checkNotPushdown(sql("SELECT * FROM foobar WHERE (THEID + 1) < 2")).collect().size == 0)
     assert(checkNotPushdown(sql("SELECT * FROM foobar WHERE (THEID + 2) != 4")).collect().size == 2)
@@ -383,7 +383,7 @@
     // are applied for columns with Filter producing wrong results. On the other hand, JDBCRDD
     // correctly handles this case by assigning `requiredColumns` properly. See PR 10427 for more
     // discussions.
-    assert(sql("SELECT COUNT(1) FROM foobar WHERE NAME = 'mary'").collect.toSet === Set(Row(1)))
+    assert(sql("SELECT COUNT(1) FROM foobar WHERE NAME = 'mary'").collect().toSet === Set(Row(1)))
   }
 
   test("SELECT * WHERE (quoted strings)") {
@@ -1841,8 +1841,8 @@
       rawPlan.execute().count()
     }
 
-    assert(getRowCount(df1) == df3.count)
-    assert(getRowCount(df2) < df3.count)
+    assert(getRowCount(df1) == df3.count())
+    assert(getRowCount(df2) < df3.count())
   }
 
   test("SPARK-26383 throw IllegalArgumentException if wrong kind of driver to the given url") {
@@ -1852,7 +1852,7 @@
         "dbtable" -> "table",
         "driver" -> "org.postgresql.Driver"
       )
-      spark.read.format("jdbc").options(opts).load
+      spark.read.format("jdbc").options(opts).load()
     }.getMessage
     assert(e.contains("The driver could not open a JDBC connection. " +
       "Check the URL: jdbc:mysql://localhost/db"))
@@ -2056,7 +2056,7 @@
 
   test("SPARK-41990: Filter with composite name") {
     val df = sql("SELECT * FROM composite_name WHERE `last name` = 'smith'")
-    assert(df.collect.toSet === Set(Row("smith", 1)))
+    assert(df.collect().toSet === Set(Row("smith", 1)))
   }
 
   test("SPARK-44866: SnowflakeDialect BOOLEAN type mapping") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala
index b913a39..42cfe7c 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCWriteSuite.scala
@@ -280,7 +280,7 @@
     .options(Map("url" -> url, "dbtable" -> "TEST.SAVETEST"))
     .save()
 
-    assert(2 === sqlContext.read.jdbc(url, "TEST.SAVETEST", new Properties).count)
+    assert(2 === sqlContext.read.jdbc(url, "TEST.SAVETEST", new Properties).count())
     assert(
       2 === sqlContext.read.jdbc(url, "TEST.SAVETEST", new Properties).collect()(0).length)
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/DisableUnnecessaryBucketedScanSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/DisableUnnecessaryBucketedScanSuite.scala
index d675503..c5c56f0 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/DisableUnnecessaryBucketedScanSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/DisableUnnecessaryBucketedScanSuite.scala
@@ -258,7 +258,7 @@
             |INSERT INTO TABLE t1 VALUES(2.28, cast("2021-08-08" as date))
             |""".stripMargin)
         val df = spark.sql("select sum(id) from t1 where id is not null")
-        assert(df.count == 1)
+        assert(df.count() == 1)
         checkDisableBucketedScan(query = "SELECT SUM(id) FROM t1 WHERE id is not null",
           expectedNumScanWithAutoScanEnabled = 1, expectedNumScanWithAutoScanDisabled = 1)
       }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/sources/InsertSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/sources/InsertSuite.scala
index eac7be7..baffc50 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/sources/InsertSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/sources/InsertSuite.scala
@@ -52,7 +52,7 @@
   override def schema: StructType = userSpecifiedSchema
 
   override def insert(input: DataFrame, overwrite: Boolean): Unit = {
-    input.collect
+    input.collect()
   }
 }
 
@@ -1112,11 +1112,11 @@
       withTable("t1", "t2") {
         sql("create table t1(j int, s bigint default 42, x bigint default 43) using parquet")
         if (useDataFrames) {
-          Seq((1, 42, 43)).toDF.write.insertInto("t1")
-          Seq((2, 42, 43)).toDF.write.insertInto("t1")
-          Seq((3, 42, 43)).toDF.write.insertInto("t1")
-          Seq((4, 44, 43)).toDF.write.insertInto("t1")
-          Seq((5, 44, 43)).toDF.write.insertInto("t1")
+          Seq((1, 42, 43)).toDF().write.insertInto("t1")
+          Seq((2, 42, 43)).toDF().write.insertInto("t1")
+          Seq((3, 42, 43)).toDF().write.insertInto("t1")
+          Seq((4, 44, 43)).toDF().write.insertInto("t1")
+          Seq((5, 44, 43)).toDF().write.insertInto("t1")
         } else {
           sql("insert into t1(j) values(1)")
           sql("insert into t1(j, s) values(2, default)")
@@ -1769,7 +1769,7 @@
       }
       def withTableT(f: => Unit): Unit = {
         sql(s"create table t(a string, i int) using $dataSource")
-        insertIntoT
+        insertIntoT()
         withTable("t") { f }
       }
       // Positive tests:
@@ -1791,7 +1791,7 @@
       withTableT {
         sql("alter table t add column (s string default concat('abc', 'def'))")
         if (config.useDataFrames) {
-          Seq((null, null, null)).toDF.write.insertInto("t")
+          Seq((null, null, null)).toDF().write.insertInto("t")
         } else {
           sql("insert into t values(null, null, null)")
         }
@@ -1915,7 +1915,7 @@
       sql(s"create table t(a string, i int default 42) using parquet")
       checkError(
         exception = intercept[AnalysisException] {
-          Seq("xyz").toDF.select("value", "default").write.insertInto("t")
+          Seq("xyz").toDF().select("value", "default").write.insertInto("t")
         },
         errorClass = "UNRESOLVED_COLUMN.WITH_SUGGESTION",
         parameters = Map("objectName" -> "`default`", "proposal" -> "`value`"))
@@ -1984,7 +1984,7 @@
       withTable("t") {
         sql(s"create table t(i boolean) using ${config.dataSource}")
         if (config.useDataFrames) {
-          Seq(false).toDF.write.insertInto("t")
+          Seq(false).toDF().write.insertInto("t")
         } else {
           sql("insert into t select false")
         }
@@ -2003,7 +2003,7 @@
       withTable("t") {
         sql(s"create table t(i boolean) using ${config.dataSource}")
         if (config.useDataFrames) {
-          Seq((false)).toDF.write.insertInto("t")
+          Seq((false)).toDF().write.insertInto("t")
         } else {
           sql("insert into t select false")
         }
@@ -2041,7 +2041,7 @@
       withTable("t") {
         sql(s"create table t(i boolean) using ${config.dataSource}")
         if (config.useDataFrames) {
-          Seq((false)).toDF.write.insertInto("t")
+          Seq((false)).toDF().write.insertInto("t")
         } else {
           sql("insert into t select false")
         }
@@ -2061,7 +2061,7 @@
       withTable("t") {
         sql(s"create table t(i boolean) using ${config.dataSource}")
         if (config.useDataFrames) {
-          Seq((false)).toDF.write.insertInto("t")
+          Seq((false)).toDF().write.insertInto("t")
         } else {
           sql("insert into t select false")
         }
@@ -2099,7 +2099,7 @@
       withTable("t") {
         sql(s"create table t(i boolean) using ${config.dataSource}")
         if (config.useDataFrames) {
-          Seq((false)).toDF.write.insertInto("t")
+          Seq((false)).toDF().write.insertInto("t")
         } else {
           sql("insert into t select false")
         }
@@ -2125,7 +2125,7 @@
         sql("insert into t select 1, default")
         sql("alter table t alter column s drop default")
         if (config.useDataFrames) {
-          Seq((2, null)).toDF.write.insertInto("t")
+          Seq((2, null)).toDF().write.insertInto("t")
         } else {
           sql("insert into t select 2, default")
         }
@@ -2173,7 +2173,7 @@
       withTable("t") {
         sql(s"create table t(i boolean) using ${config.dataSource}")
         if (config.useDataFrames) {
-          Seq((false)).toDF.write.insertInto("t")
+          Seq((false)).toDF().write.insertInto("t")
         } else {
           sql("insert into t select false")
         }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/EventTimeWatermarkSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/EventTimeWatermarkSuite.scala
index 0b076e0..36ee322 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/EventTimeWatermarkSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/EventTimeWatermarkSuite.scala
@@ -911,7 +911,7 @@
             (MONTHS_PER_YEAR * DAYS_PER_MONTH + 2 * DAYS_PER_MONTH) * MILLIS_PER_DAY)
         ).foreach { case (delayThresholdVariants, expectedMs) =>
           delayThresholdVariants.foreach { case delayThreshold =>
-            val df = MemoryStream[Int].toDF
+            val df = MemoryStream[Int].toDF()
               .withColumn("eventTime", timestamp_seconds($"value"))
               .withWatermark("eventTime", delayThreshold)
             val eventTimeAttr = df.queryExecution.analyzed.output.find(a => a.name == "eventTime")
@@ -932,7 +932,7 @@
           "interval '1 2:3:4' day to hour",
           "interval '1 2' year to month").foreach { delayThreshold =>
           intercept[AnalysisException] {
-            val df = MemoryStream[Int].toDF
+            val df = MemoryStream[Int].toDF()
               .withColumn("eventTime", timestamp_seconds($"value"))
               .withWatermark("eventTime", delayThreshold)
           }
@@ -944,10 +944,10 @@
   private def dfWithMultipleWatermarks(
       input1: MemoryStream[Int],
       input2: MemoryStream[Int]): Dataset[_] = {
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .withColumn("eventTime", timestamp_seconds($"value"))
       .withWatermark("eventTime", "10 seconds")
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .withColumn("eventTime", timestamp_seconds($"value"))
       .withWatermark("eventTime", "15 seconds")
     df1.union(df2).select($"eventTime".cast("int"))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSinkSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSinkSuite.scala
index b40ab4c..f03f737 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSinkSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSinkSuite.scala
@@ -212,7 +212,7 @@
     // with aggregations using event time windows and watermark, which allows
     // aggregation + append mode.
     val inputData = MemoryStream[Long]
-    val inputDF = inputData.toDF.toDF("time")
+    val inputDF = inputData.toDF().toDF("time")
     val outputDf = inputDF
       .selectExpr("timestamp_seconds(time) AS timestamp")
       .withWatermark("timestamp", "10 seconds")
@@ -588,7 +588,7 @@
       "fs.file.impl.disable.cache" -> "true") {
       withTempDir { tempDir =>
         val path = new File(tempDir, "text").getCanonicalPath
-        Seq("foo").toDF.write.format("text").save(path)
+        Seq("foo").toDF().write.format("text").save(path)
         spark.read.format("text").load(path)
       }
     }
@@ -600,7 +600,7 @@
       "fs.file.impl.disable.cache" -> "true") {
       withTempDir { tempDir =>
         val path = new File(tempDir, "text").getCanonicalPath
-        Seq("foo").toDF.write.format("text").save(path)
+        Seq("foo").toDF().write.format("text").save(path)
         spark.read.format("text").load(path + "/*")
       }
     }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSourceSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSourceSuite.scala
index 684447e..d6867da 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSourceSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FileStreamSourceSuite.scala
@@ -1304,7 +1304,7 @@
       try {
         assert(q.awaitTermination(streamingTimeout.toMillis))
         assert(q.recentProgress.count(_.numInputRows != 0) == 1) // only one trigger was run
-        checkAnswer(sql(s"SELECT * from parquet.`$targetDir`"), (1 to 3).map(_.toString).toDF)
+        checkAnswer(sql(s"SELECT * from parquet.`$targetDir`"), (1 to 3).map(_.toString).toDF())
       } finally {
         q.stop()
       }
@@ -1317,7 +1317,7 @@
       try {
         assert(q2.awaitTermination(streamingTimeout.toMillis))
         assert(q2.recentProgress.count(_.numInputRows != 0) == 1) // only one trigger was run
-        checkAnswer(sql(s"SELECT * from parquet.`$targetDir`"), (1 to 5).map(_.toString).toDF)
+        checkAnswer(sql(s"SELECT * from parquet.`$targetDir`"), (1 to 5).map(_.toString).toDF())
       } finally {
         q2.stop()
       }
@@ -2410,7 +2410,7 @@
 }
 
 object ExistsThrowsExceptionFileSystem {
-  val scheme = s"FileStreamSourceSuite${math.abs(Random.nextInt)}fs"
+  val scheme = s"FileStreamSourceSuite${math.abs(Random.nextInt())}fs"
 }
 
 class CountListingLocalFileSystem extends RawLocalFileSystem {
@@ -2428,7 +2428,7 @@
 }
 
 object CountListingLocalFileSystem {
-  val scheme = s"CountListingLocalFileSystem${math.abs(Random.nextInt)}fs"
+  val scheme = s"CountListingLocalFileSystem${math.abs(Random.nextInt())}fs"
   val pathToNumListStatusCalled = new mutable.HashMap[String, AtomicLong]
 
   def resetCount(): Unit = pathToNumListStatusCalled.clear()
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsInPandasWithStateSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsInPandasWithStateSuite.scala
index 20fb17f..006cc1c 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsInPandasWithStateSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsInPandasWithStateSuite.scala
@@ -224,7 +224,7 @@
       name = "pandas_grouped_map_with_state", pythonScript = pythonScript)
 
     val inputData = MemoryStream[String]
-    val inputDataDS = inputData.toDS
+    val inputDataDS = inputData.toDS()
     val outputStructType = StructType(
       Seq(
         StructField("key", StringType),
@@ -308,7 +308,7 @@
 
     val clock = new StreamManualClock
     val inputData = MemoryStream[String]
-    val inputDataDS = inputData.toDS
+    val inputDataDS = inputData.toDS()
     val outputStructType = StructType(
       Seq(
         StructField("key", StringType),
@@ -415,7 +415,7 @@
 
       val inputData = MemoryStream[(String, Int)]
       val inputDataDF =
-        inputData.toDF.select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
+        inputData.toDF().select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
       val outputStructType = StructType(
         Seq(
           StructField("key", StringType),
@@ -497,7 +497,7 @@
         val clock = new StreamManualClock
         val inputData = MemoryStream[(String, Long)]
         val inputDataDF = inputData
-          .toDF.toDF("key", "time")
+          .toDF().toDF("key", "time")
           .selectExpr("key", "timestamp_seconds(time) as timestamp")
         val outputStructType = StructType(
           Seq(
@@ -762,7 +762,7 @@
 
     val clock = new StreamManualClock
     val inputData = MemoryStream[String]
-    val inputDataDS = inputData.toDS
+    val inputDataDS = inputData.toDS()
       .withColumnRenamed("value", "key1")
       // the type of columns with string literal will be non-nullable
       .withColumn("key2", lit("__FAKE__"))
@@ -847,7 +847,7 @@
     val clock = new StreamManualClock
     val inputData = MemoryStream[String]
     // schema: val1, key2, val2, key1, val3
-    val inputDataDS = inputData.toDS
+    val inputDataDS = inputData.toDS()
       .withColumnRenamed("value", "val1")
       .withColumn("key2", $"val1")
       // the type of columns with string literal will be non-nullable
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
index a3774bf..b35e9961 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
@@ -452,10 +452,10 @@
       if (state.exists) throw new IllegalArgumentException("state.exists should be false")
       Iterator((key, values.size))
     }
-    val df = Seq("a", "a", "b").toDS
+    val df = Seq("a", "a", "b").toDS()
       .groupByKey(x => x)
-      .flatMapGroupsWithState(Update, GroupStateTimeout.NoTimeout)(stateFunc).toDF
-    checkAnswer(df, Seq(("a", 2), ("b", 1)).toDF)
+      .flatMapGroupsWithState(Update, GroupStateTimeout.NoTimeout)(stateFunc).toDF()
+    checkAnswer(df, Seq(("a", 2), ("b", 1)).toDF())
   }
 
   testWithAllStateVersions("flatMapGroupsWithState - streaming with processing time timeout") {
@@ -528,7 +528,7 @@
   testWithAllStateVersions("flatMapGroupsWithState - streaming w/ event time timeout + watermark") {
     val inputData = MemoryStream[(String, Int)]
     val result =
-      inputData.toDS
+      inputData.toDS()
         .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
         .withWatermark("eventTime", "10 seconds")
         .as[(String, Long)]
@@ -583,7 +583,7 @@
   test("flatMapGroupsWithState - recovery from checkpoint uses state format version 1") {
     val inputData = MemoryStream[(String, Int)]
     val result =
-      inputData.toDS
+      inputData.toDS()
         .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
         .withWatermark("eventTime", "10 seconds")
         .as[(String, Long)]
@@ -697,14 +697,14 @@
       spark.createDataset(Seq("a", "a", "b"))
         .groupByKey(x => x)
         .mapGroupsWithState(EventTimeTimeout)(stateFunc)
-        .toDF,
-      spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
+        .toDF(),
+      spark.createDataset(Seq(("a", 2), ("b", 1))).toDF())
   }
 
   test("SPARK-35896: metrics in StateOperatorProgress are output correctly") {
     val inputData = MemoryStream[(String, Int)]
     val result =
-      inputData.toDS
+      inputData.toDS()
         .select($"_1".as("key"), timestamp_seconds($"_2").as("eventTime"))
         .withWatermark("eventTime", "10 seconds")
         .as[(String, Long)]
@@ -825,7 +825,7 @@
   test("output partitioning is unknown") {
     val stateFunc = (key: String, values: Iterator[String], state: GroupState[RunningCount]) => key
     val inputData = MemoryStream[String]
-    val result = inputData.toDS.groupByKey(x => x).mapGroupsWithState(stateFunc)
+    val result = inputData.toDS().groupByKey(x => x).mapGroupsWithState(stateFunc)
     testStream(result, Update)(
       AddData(inputData, "a"),
       CheckNewAnswer("a"),
@@ -1042,7 +1042,7 @@
     val stateFormatVersion = spark.conf.get(SQLConf.FLATMAPGROUPSWITHSTATE_STATE_FORMAT_VERSION)
     val emptyRdd = spark.sparkContext.emptyRDD[InternalRow]
     MemoryStream[Int]
-      .toDS
+      .toDS()
       .groupByKey(x => x)
       .flatMapGroupsWithState[Int, Int](Append, timeoutConf = timeoutType)(func)
       .logicalPlan.collectFirst {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/GroupStateSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/GroupStateSuite.scala
index 93dac34..d795e7a 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/GroupStateSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/GroupStateSuite.scala
@@ -42,8 +42,8 @@
     assert(testState.get === prodState.get)
     assert(testState.getTimeoutTimestampMs === prodState.getTimeoutTimestampMs)
     assert(testState.hasTimedOut === prodState.hasTimedOut)
-    assert(testState.getCurrentProcessingTimeMs === prodState.getCurrentProcessingTimeMs)
-    assert(testState.getCurrentWatermarkMs === prodState.getCurrentWatermarkMs)
+    assert(testState.getCurrentProcessingTimeMs() === prodState.getCurrentProcessingTimeMs())
+    assert(testState.getCurrentWatermarkMs() === prodState.getCurrentWatermarkMs())
 
     testState.update(6)
     prodState.update(6)
@@ -403,7 +403,8 @@
 
         // Tests for getCurrentProcessingTimeMs in batch queries
         val currentTime = System.currentTimeMillis()
-        assert(batchState(timeoutConf, watermarkPresent).getCurrentProcessingTimeMs >= currentTime)
+        assert(
+          batchState(timeoutConf, watermarkPresent).getCurrentProcessingTimeMs() >= currentTime)
       }
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/MultiStatefulOperatorsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/MultiStatefulOperatorsSuite.scala
index fb5445a..405c0bb 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/MultiStatefulOperatorsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/MultiStatefulOperatorsSuite.scala
@@ -836,12 +836,12 @@
     }
 
     val input1 = MemoryStream[(String, Timestamp)]
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .selectExpr("_1 as leftId", "_2 as leftEventTime")
       .withWatermark("leftEventTime", "5 minutes")
 
     val input2 = MemoryStream[(String, Timestamp)]
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .selectExpr("_1 as rightId", "_2 as rightEventTime")
       .withWatermark("rightEventTime", "10 minutes")
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala
index c97979a..e54ce64 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala
@@ -94,7 +94,7 @@
       }
       assert(streamingRelation.nonEmpty, "cannot find StreamingRelation")
       assert(
-        streamingRelation.head.computeStats.sizeInBytes ==
+        streamingRelation.head.computeStats().sizeInBytes ==
           spark.sessionState.conf.defaultSizeInBytes)
     }
   }
@@ -105,7 +105,8 @@
     }
     assert(streamingRelation.nonEmpty, "cannot find StreamingRelationV2")
     assert(
-      streamingRelation.head.computeStats.sizeInBytes == spark.sessionState.conf.defaultSizeInBytes)
+      streamingRelation.head.computeStats().sizeInBytes ==
+        spark.sessionState.conf.defaultSizeInBytes)
   }
 
   test("StreamingExecutionRelation.computeStats") {
@@ -113,7 +114,8 @@
     val executionRelation = StreamingExecutionRelation(
       memoryStream, toAttributes(memoryStream.encoder.schema), None)(
       memoryStream.sqlContext.sparkSession)
-    assert(executionRelation.computeStats.sizeInBytes == spark.sessionState.conf.defaultSizeInBytes)
+    assert(executionRelation.computeStats().sizeInBytes ==
+      spark.sessionState.conf.defaultSizeInBytes)
   }
 
   test("explain join with a normal source") {
@@ -146,7 +148,7 @@
       val smallTable3 = Seq((1, "one"), (2, "two"), (4, "four")).toDF("number", "word")
 
       // Join the input stream with a table.
-      val df = MemoryStream[Int].toDF
+      val df = MemoryStream[Int].toDF()
       val joined = df.join(smallTable, smallTable("number") === $"value")
         .join(smallTable2, smallTable2("number") === $"value")
         .join(smallTable3, smallTable3("number") === $"value")
@@ -279,7 +281,7 @@
 
     // Running streaming plan as a batch query
     assertError("start" :: Nil) {
-      streamInput.toDS.map { i => i }.count()
+      streamInput.toDS().map { i => i }.count()
     }
 
     // Running non-streaming plan with as a streaming query
@@ -290,7 +292,7 @@
 
     // Running streaming plan that cannot be incrementalized
     assertError("not supported" :: "streaming" :: Nil) {
-      val ds = streamInput.toDS.map { i => i }.sort()
+      val ds = streamInput.toDS().map { i => i }.sort()
       testStream(ds)()
     }
   }
@@ -647,7 +649,7 @@
   test("SPARK-19065: dropDuplicates should not create expressions using the same id") {
     withTempPath { testPath =>
       val data = Seq((1, 2), (2, 3), (3, 4))
-      data.toDS.write.mode("overwrite").json(testPath.getCanonicalPath)
+      data.toDS().write.mode("overwrite").json(testPath.getCanonicalPath)
       val schema = spark.read.json(testPath.getCanonicalPath).schema
       val query = spark
         .readStream
@@ -875,7 +877,7 @@
     withTempDir { dir =>
       val checkpointLocation = dir.getCanonicalPath
       assert(!checkpointLocation.startsWith("file:/"))
-      val query = MemoryStream[Int].toDF
+      val query = MemoryStream[Int].toDF()
         .writeStream
         .option("checkpointLocation", checkpointLocation)
         .format("console")
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingDeduplicationSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingDeduplicationSuite.scala
index c690885..5c3d8d8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingDeduplicationSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingDeduplicationSuite.scala
@@ -264,7 +264,7 @@
 
   test("SPARK-19841: watermarkPredicate should filter based on keys") {
     val input = MemoryStream[(Int, Int)]
-    val df = input.toDS.toDF("time", "id")
+    val df = input.toDS().toDF("time", "id")
       .withColumn("time", timestamp_seconds($"time"))
       .withWatermark("time", "1 second")
       .dropDuplicates("id", "time") // Change the column positions
@@ -283,7 +283,7 @@
 
   test("SPARK-21546: dropDuplicates should ignore watermark when it's not a key") {
     val input = MemoryStream[(Int, Int)]
-    val df = input.toDS.toDF("id", "time")
+    val df = input.toDS().toDF("id", "time")
       .withColumn("time", timestamp_seconds($"time"))
       .withWatermark("time", "1 second")
       .dropDuplicates("id")
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingJoinSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingJoinSuite.scala
index 3e1bc57..a380451 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingJoinSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingJoinSuite.scala
@@ -55,7 +55,7 @@
 
   protected def setupStream(prefix: String, multiplier: Int): (MemoryStream[Int], DataFrame) = {
     val input = MemoryStream[Int]
-    val df = input.toDF
+    val df = input.toDF()
       .select(
         $"value" as "key",
         timestamp_seconds($"value")  as s"${prefix}Time",
@@ -163,12 +163,12 @@
     val leftInput = MemoryStream[(Int, Int)]
     val rightInput = MemoryStream[(Int, Int)]
 
-    val df1 = leftInput.toDF.toDF("leftKey", "time")
+    val df1 = leftInput.toDF().toDF("leftKey", "time")
       .select($"leftKey", timestamp_seconds($"time") as "leftTime",
         ($"leftKey" * 2) as "leftValue")
       .withWatermark("leftTime", watermark)
 
-    val df2 = rightInput.toDF.toDF("rightKey", "time")
+    val df2 = rightInput.toDF().toDF("rightKey", "time")
       .select($"rightKey", timestamp_seconds($"time") as "rightTime",
         ($"rightKey" * 3) as "rightValue")
       .withWatermark("rightTime", watermark)
@@ -232,8 +232,8 @@
     val input1 = MemoryStream[Int]
     val input2 = MemoryStream[Int]
 
-    val df1 = input1.toDF.select($"value" as "key", ($"value" * 2) as "leftValue")
-    val df2 = input2.toDF.select($"value" as "key", ($"value" * 3) as "rightValue")
+    val df1 = input1.toDF().select($"value" as "key", ($"value" * 2) as "leftValue")
+    val df2 = input2.toDF().select($"value" as "key", ($"value" * 3) as "rightValue")
     val joined = df1.join(df2, "key")
 
     testStream(joined)(
@@ -261,12 +261,12 @@
     val input1 = MemoryStream[Int]
     val input2 = MemoryStream[Int]
 
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .select($"value" as "key", timestamp_seconds($"value") as "timestamp",
         ($"value" * 2) as "leftValue")
       .select($"key", window($"timestamp", "10 second"), $"leftValue")
 
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .select($"value" as "key", timestamp_seconds($"value") as "timestamp",
         ($"value" * 3) as "rightValue")
       .select($"key", window($"timestamp", "10 second"), $"rightValue")
@@ -302,13 +302,13 @@
     val input1 = MemoryStream[Int]
     val input2 = MemoryStream[Int]
 
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .select($"value" as "key", timestamp_seconds($"value") as "timestamp",
         ($"value" * 2) as "leftValue")
       .withWatermark("timestamp", "10 seconds")
       .select($"key", window($"timestamp", "10 second"), $"leftValue")
 
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .select($"value" as "key", timestamp_seconds($"value") as "timestamp",
         ($"value" * 3) as "rightValue")
       .select($"key", window($"timestamp", "10 second"), $"rightValue")
@@ -353,12 +353,12 @@
     val leftInput = MemoryStream[(Int, Int)]
     val rightInput = MemoryStream[(Int, Int)]
 
-    val df1 = leftInput.toDF.toDF("leftKey", "time")
+    val df1 = leftInput.toDF().toDF("leftKey", "time")
       .select($"leftKey", timestamp_seconds($"time") as "leftTime",
         ($"leftKey" * 2) as "leftValue")
       .withWatermark("leftTime", "10 seconds")
 
-    val df2 = rightInput.toDF.toDF("rightKey", "time")
+    val df2 = rightInput.toDF().toDF("rightKey", "time")
       .select($"rightKey", timestamp_seconds($"time") as "rightTime",
         ($"rightKey" * 3) as "rightValue")
       .withWatermark("rightTime", "10 seconds")
@@ -413,12 +413,12 @@
     val leftInput = MemoryStream[(Int, Int)]
     val rightInput = MemoryStream[(Int, Int)]
 
-    val df1 = leftInput.toDF.toDF("leftKey", "time")
+    val df1 = leftInput.toDF().toDF("leftKey", "time")
       .select($"leftKey", timestamp_seconds($"time") as "leftTime",
         ($"leftKey" * 2) as "leftValue")
       .withWatermark("leftTime", "20 seconds")
 
-    val df2 = rightInput.toDF.toDF("rightKey", "time")
+    val df2 = rightInput.toDF().toDF("rightKey", "time")
       .select($"rightKey", timestamp_seconds($"time") as "rightTime",
         ($"rightKey" * 3) as "rightValue")
       .withWatermark("rightTime", "30 seconds")
@@ -497,9 +497,9 @@
     val input1 = MemoryStream[Int]
     val input2 = MemoryStream[Int]
 
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .select($"value" as "leftKey", ($"value" * 2) as "leftValue")
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .select($"value" as "rightKey", ($"value" * 3) as "rightValue")
     val joined = df1.join(df2, expr("leftKey < rightKey"))
     val e = intercept[Exception] {
@@ -512,7 +512,7 @@
 
   test("stream stream self join") {
     val input = MemoryStream[Int]
-    val df = input.toDF
+    val df = input.toDF()
     val join =
       df.select($"value" % 5 as "key", $"value").join(
         df.select($"value" % 5 as "key", $"value"), "key")
@@ -537,7 +537,8 @@
     withTempDir { tempDir =>
       val queryId = UUID.randomUUID
       val opId = 0
-      val path = Utils.createDirectory(tempDir.getAbsolutePath, Random.nextFloat.toString).toString
+      val path =
+        Utils.createDirectory(tempDir.getAbsolutePath, Random.nextFloat().toString).toString
       val stateInfo = StatefulOperatorStateInfo(path, queryId, opId, 0L, 5)
 
       implicit val sqlContext = spark.sqlContext
@@ -579,10 +580,10 @@
     val input2 = MemoryStream[Int]
     val input3 = MemoryStream[Int]
 
-    val df1 = input1.toDF.select($"value" as "leftKey", ($"value" * 2) as "leftValue")
-    val df2 = input2.toDF
+    val df1 = input1.toDF().select($"value" as "leftKey", ($"value" * 2) as "leftValue")
+    val df2 = input2.toDF()
       .select($"value" as "middleKey", ($"value" * 3) as "middleValue")
-    val df3 = input3.toDF
+    val df3 = input3.toDF()
       .select($"value" as "rightKey", ($"value" * 5) as "rightValue")
 
     val joined = df1.join(df2, expr("leftKey = middleKey")).join(df3, expr("rightKey = middleKey"))
@@ -598,9 +599,9 @@
     val input1 = MemoryStream[Int]
     val input2 = MemoryStream[Int]
 
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .select($"value" as Symbol("a"), $"value" * 2 as Symbol("b"))
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .select($"value" as Symbol("a"), $"value" * 2 as Symbol("b"))
       .repartition($"b")
     val joined = df1.join(df2, Seq("a", "b")).select($"a")
@@ -691,13 +692,13 @@
     val input1 = MemoryStream[Int]
     val input2 = MemoryStream[Int]
 
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .select($"value" as "key", timestamp_seconds($"value") as "timestamp",
         ($"value" * 2) as "leftValue")
       .withWatermark("timestamp", "10 seconds")
       .select($"key", window($"timestamp", "10 second"), $"leftValue")
 
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .select($"value" as "key", timestamp_seconds($"value") as "timestamp",
         ($"value" * 3) as "rightValue")
       .select($"key", window($"timestamp", "10 second"), $"rightValue")
@@ -1151,7 +1152,7 @@
     def constructUnionDf(desiredPartitionsForInput1: Int)
         : (MemoryStream[Int], MemoryStream[Int], MemoryStream[Int], DataFrame) = {
       val input1 = MemoryStream[Int](desiredPartitionsForInput1)
-      val df1 = input1.toDF
+      val df1 = input1.toDF()
         .select(
           $"value" as "key",
           $"value" as "leftValue",
@@ -1206,12 +1207,12 @@
 
   test("SPARK-32148 stream-stream join regression on Spark 3.0.0") {
     val input1 = MemoryStream[(Timestamp, String, String)]
-    val df1 = input1.toDF
+    val df1 = input1.toDF()
       .selectExpr("_1 as eventTime", "_2 as id", "_3 as comment")
       .withWatermark(s"eventTime", "2 minutes")
 
     val input2 = MemoryStream[(Timestamp, String, String)]
-    val df2 = input2.toDF
+    val df2 = input2.toDF()
       .selectExpr("_1 as eventTime", "_2 as id", "_3 as name")
       .withWatermark(s"eventTime", "4 minutes")
 
@@ -1366,12 +1367,12 @@
       SQLConf.STATE_STORE_PROVIDER_CLASS.key -> classOf[RocksDBStateStoreProvider].getName) {
 
       val input1 = MemoryStream[(Timestamp, String, String)]
-      val df1 = input1.toDF
+      val df1 = input1.toDF()
         .selectExpr("_1 as eventTime", "_2 as id", "_3 as comment")
         .withWatermark("eventTime", "0 second")
 
       val input2 = MemoryStream[(Timestamp, String, String)]
-      val df2 = input2.toDF
+      val df2 = input2.toDF()
         .selectExpr("_1 as eventTime", "_2 as id", "_3 as comment")
         .withWatermark("eventTime", "0 second")
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenerSuite.scala
index a0f3853..5bf346d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenerSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenerSuite.scala
@@ -66,7 +66,7 @@
       extends AssertOnQuery(q => {
         eventually(Timeout(streamingTimeout)) {
           if (q.exception.isEmpty) {
-            assert(clock.isStreamWaitingAt(clock.getTimeMillis))
+            assert(clock.isStreamWaitingAt(clock.getTimeMillis()))
           }
         }
         if (q.exception.isDefined) {
@@ -210,7 +210,7 @@
   test("adding and removing listener") {
     def isListenerActive(listener: EventCollector): Boolean = {
       listener.reset()
-      testStream(MemoryStream[Int].toDS)(
+      testStream(MemoryStream[Int].toDS())(
         StartStream(),
         StopStream
       )
@@ -241,7 +241,7 @@
       for (i <- 1 to 50) {
         listener.reset()
         require(listener.startEvent === null)
-        testStream(MemoryStream[Int].toDS)(
+        testStream(MemoryStream[Int].toDS())(
           StartStream(),
           Assert(listener.startEvent !== null, "onQueryStarted not called before query returned"),
           StopStream,
@@ -335,7 +335,7 @@
         actions += AssertOnQuery { q =>
           q.recentProgress.size > 1 && q.recentProgress.size <= 11
         }
-        testStream(input.toDS)(actions.toSeq: _*)
+        testStream(input.toDS())(actions.toSeq: _*)
         spark.sparkContext.listenerBus.waitUntilEmpty()
         // 11 is the max value of the possible numbers of events.
         assert(numIdleEvent > 1 && numIdleEvent <= 11)
@@ -355,7 +355,7 @@
       collector1.reset()
       collector2.reset()
       val mem = MemoryStream[Int](implicitly[Encoder[Int]], session.sqlContext)
-      testStream(mem.toDS)(
+      testStream(mem.toDS())(
         AddData(mem, 1, 2, 3),
         CheckAnswer(1, 2, 3)
       )
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenersConfSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenersConfSuite.scala
index 153ba7a..305d9ca 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenersConfSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryListenersConfSuite.scala
@@ -38,7 +38,7 @@
       .set("spark.bbb", "bbb")
 
   test("test if the configured query listener is loaded") {
-    testStream(MemoryStream[Int].toDS)(
+    testStream(MemoryStream[Int].toDS())(
       StartStream(),
       StopStream
     )
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryManagerSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryManagerSuite.scala
index 7deb0c6..754f552 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryManagerSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQueryManagerSuite.scala
@@ -115,11 +115,11 @@
       // Terminate a query asynchronously with exception and see awaitAnyTermination throws
       // the exception
       val q2 = stopRandomQueryAsync(100.milliseconds, withError = true)
-      testAwaitAnyTermination(ExpectException[SparkException])
+      testAwaitAnyTermination(ExpectException[SparkException]())
       require(!q2.isActive) // should be inactive by the time the prev awaitAnyTerm returned
 
       // All subsequent calls to awaitAnyTermination should throw the exception
-      testAwaitAnyTermination(ExpectException[SparkException])
+      testAwaitAnyTermination(ExpectException[SparkException]())
 
       // Resetting termination should make awaitAnyTermination() blocking again
       spark.streams.resetTerminated()
@@ -133,7 +133,7 @@
       val q4 = stopRandomQueryAsync(10.milliseconds, withError = true)
       eventually(Timeout(streamingTimeout)) { require(!q4.isActive) }
       // After q4 terminates with exception, awaitAnyTerm should start throwing exception
-      testAwaitAnyTermination(ExpectException[SparkException])
+      testAwaitAnyTermination(ExpectException[SparkException]())
     }
   }
 
@@ -181,14 +181,14 @@
       // throws the exception
       val q2 = stopRandomQueryAsync(100.milliseconds, withError = true)
       testAwaitAnyTermination(
-        ExpectException[SparkException],
+        ExpectException[SparkException](),
         awaitTimeout = 4.seconds,
         testBehaviorFor = 6.seconds)
       require(!q2.isActive) // should be inactive by the time the prev awaitAnyTerm returned
 
       // All subsequent calls to awaitAnyTermination should throw the exception
       testAwaitAnyTermination(
-        ExpectException[SparkException],
+        ExpectException[SparkException](),
         awaitTimeout = 2.seconds,
         testBehaviorFor = 4.seconds)
 
@@ -208,7 +208,7 @@
       // `StreamingQueryManager` has already received the error.
       q3.stop()
       testAwaitAnyTermination(
-        ExpectException[SparkException],
+        ExpectException[SparkException](),
         awaitTimeout = 100.milliseconds,
         testBehaviorFor = 4.seconds)
 
@@ -228,7 +228,7 @@
       // `StreamingQueryManager` has already received the error.
       q5.stop()
       // After q5 terminates with exception, awaitAnyTerm should start throwing exception
-      testAwaitAnyTermination(ExpectException[SparkException], awaitTimeout = 2.seconds)
+      testAwaitAnyTermination(ExpectException[SparkException](), awaitTimeout = 2.seconds)
     }
   }
 
@@ -409,7 +409,7 @@
         datasets.zipWithIndex.map { case (ds, i) =>
           var query: StreamingQuery = null
           try {
-            val df = ds.toDF
+            val df = ds.toDF()
             val metadataRoot =
               Utils.createTempDir(namePrefix = "streaming.checkpoint").getCanonicalPath
             query =
@@ -480,7 +480,7 @@
 
   private def makeDataset: (MemoryStream[Int], Dataset[Int]) = {
     val inputData = MemoryStream[Int]
-    val mapped = inputData.toDS.map(6 / _)
+    val mapped = inputData.toDS().map(6 / _)
     (inputData, mapped)
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala
index 9444db3..1e0fa5b 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala
@@ -69,7 +69,7 @@
   test("name unique in active queries") {
     withTempDir { dir =>
       def startQuery(name: Option[String]): StreamingQuery = {
-        val writer = MemoryStream[Int].toDS.writeStream
+        val writer = MemoryStream[Int].toDS().writeStream
         name.foreach(writer.queryName)
         writer
           .foreach(new TestForeachWriter)
@@ -164,9 +164,9 @@
       AddData(inputData, 0),
       ExpectFailure[SparkException](),
       AssertOnQuery(_.isActive === false),
-      TestAwaitTermination(ExpectException[SparkException]),
-      TestAwaitTermination(ExpectException[SparkException], timeoutMs = 2000),
-      TestAwaitTermination(ExpectException[SparkException], timeoutMs = 10),
+      TestAwaitTermination(ExpectException[SparkException]()),
+      TestAwaitTermination(ExpectException[SparkException](), timeoutMs = 2000),
+      TestAwaitTermination(ExpectException[SparkException](), timeoutMs = 10),
       AssertOnQuery(q => {
         q.exception.get.startOffset ===
           q.committedOffsets.toOffsetSeq(Seq(inputData), OffsetSeqMetadata()).toString &&
@@ -245,7 +245,7 @@
     }
 
     // query execution should take 350 ms the first time it is called
-    val mapped = inputData.toDS.coalesce(1).as[Long].map { x =>
+    val mapped = inputData.toDS().coalesce(1).as[Long].map { x =>
       clock.waitTillTime(1500)  // this will only wait the first time when clock < 1500
       10 / x
     }.agg(count("*")).as[Long]
@@ -431,7 +431,7 @@
     assert(spark.conf.get(SQLConf.STREAMING_METRICS_ENABLED.key).toBoolean === false)
 
     withSQLConf(SQLConf.STREAMING_METRICS_ENABLED.key -> "false") {
-      testStream(inputData.toDF)(
+      testStream(inputData.toDF())(
         AssertOnQuery { q => !isMetricsRegistered(q) },
         StopStream,
         AssertOnQuery { q => !isMetricsRegistered(q) }
@@ -440,7 +440,7 @@
 
     // Registered when enabled
     withSQLConf(SQLConf.STREAMING_METRICS_ENABLED.key -> "true") {
-      testStream(inputData.toDF)(
+      testStream(inputData.toDF())(
         AssertOnQuery { q => isMetricsRegistered(q) },
         StopStream,
         AssertOnQuery { q => !isMetricsRegistered(q) }
@@ -485,7 +485,7 @@
   }
 
   test("input row calculation with same V1 source used twice in self-join") {
-    val streamingTriggerDF = spark.createDataset(1 to 10).toDF
+    val streamingTriggerDF = spark.createDataset(1 to 10).toDF()
     val streamingInputDF = createSingleTriggerStreamingDF(streamingTriggerDF).toDF("value")
 
     val progress = getStreamingQuery(streamingInputDF.join(streamingInputDF, "value"))
@@ -496,7 +496,7 @@
   }
 
   test("input row calculation with mixed batch and streaming V1 sources") {
-    val streamingTriggerDF = spark.createDataset(1 to 10).toDF
+    val streamingTriggerDF = spark.createDataset(1 to 10).toDF()
     val streamingInputDF = createSingleTriggerStreamingDF(streamingTriggerDF).toDF("value")
     val staticInputDF = spark.createDataFrame(Seq(1 -> "1", 2 -> "2")).toDF("value", "anotherValue")
 
@@ -511,7 +511,7 @@
 
   test("input row calculation with trigger input DF having multiple leaves in V1 source") {
     val streamingTriggerDF =
-      spark.createDataset(1 to 5).toDF.union(spark.createDataset(6 to 10).toDF)
+      spark.createDataset(1 to 5).toDF().union(spark.createDataset(6 to 10).toDF())
     require(streamingTriggerDF.logicalPlan.collectLeaves().size > 1)
     val streamingInputDF = createSingleTriggerStreamingDF(streamingTriggerDF)
 
@@ -826,14 +826,14 @@
     }
 
     val input = MemoryStream[Int] :: MemoryStream[Int] :: MemoryStream[Int] :: Nil
-    val q1 = startQuery(input(0).toDS, "stream_serializable_test_1")
-    val q2 = startQuery(input(1).toDS.map { i =>
+    val q1 = startQuery(input(0).toDS(), "stream_serializable_test_1")
+    val q2 = startQuery(input(1).toDS().map { i =>
       // Emulate that `StreamingQuery` get captured with normal usage unintentionally.
       // It should not fail the query.
       val q = q1
       i
     }, "stream_serializable_test_2")
-    val q3 = startQuery(input(2).toDS.map { i =>
+    val q3 = startQuery(input(2).toDS().map { i =>
       // Emulate that `StreamingQuery` is used in executors. We should fail the query with a clear
       // error message.
       q1.explain()
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/test/DataStreamReaderWriterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/test/DataStreamReaderWriterSuite.scala
index d03e8bc..4cdfc83 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/test/DataStreamReaderWriterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/test/DataStreamReaderWriterSuite.scala
@@ -601,7 +601,7 @@
         assert(!userCheckpointPath.exists(), s"$userCheckpointPath should not exist")
         withSQLConf(SQLConf.CHECKPOINT_LOCATION.key -> checkpointPath.getAbsolutePath) {
           val queryName = "test_query"
-          val ds = MemoryStream[Int].toDS
+          val ds = MemoryStream[Int].toDS()
           ds.writeStream
             .format("memory")
             .queryName(queryName)
@@ -623,7 +623,7 @@
     withTempDir { checkpointPath =>
       withSQLConf(SQLConf.CHECKPOINT_LOCATION.key -> checkpointPath.getAbsolutePath) {
         val queryName = "test_query"
-        val ds = MemoryStream[Int].toDS
+        val ds = MemoryStream[Int].toDS()
         ds.writeStream.format("memory").queryName(queryName).start().stop()
         // Should use query name to create a folder in `checkpointPath`
         val queryCheckpointDir = new File(checkpointPath, queryName)
@@ -639,7 +639,7 @@
     import testImplicits._
     withTempDir { checkpointPath =>
       withSQLConf(SQLConf.CHECKPOINT_LOCATION.key -> checkpointPath.getAbsolutePath) {
-        val ds = MemoryStream[Int].toDS
+        val ds = MemoryStream[Int].toDS()
         ds.writeStream.format("console").start().stop()
         // Should create a random folder in `checkpointPath`
         assert(
@@ -655,7 +655,7 @@
     withTempDir { checkpointPath =>
       withSQLConf(SQLConf.CHECKPOINT_LOCATION.key -> checkpointPath.getAbsolutePath,
         SQLConf.FORCE_DELETE_TEMP_CHECKPOINT_LOCATION.key -> "true") {
-        val ds = MemoryStream[Int].toDS
+        val ds = MemoryStream[Int].toDS()
         val query = ds.writeStream.format("console").start()
         assert(checkpointPath.exists())
         query.stop()
@@ -666,7 +666,7 @@
 
   test("temp checkpoint dir should be deleted if a query is stopped without errors") {
     import testImplicits._
-    val query = MemoryStream[Int].toDS.writeStream.format("console").start()
+    val query = MemoryStream[Int].toDS().writeStream.format("console").start()
     query.processAllAvailable()
     val checkpointDir = new Path(
       query.asInstanceOf[StreamingQueryWrapper].streamingQuery.resolvedCheckpointRoot)
@@ -690,7 +690,7 @@
   private def testTempCheckpointWithFailedQuery(checkpointMustBeDeleted: Boolean): Unit = {
     import testImplicits._
     val input = MemoryStream[Int]
-    val query = input.toDS.map(_ / 0).writeStream.format("console").start()
+    val query = input.toDS().map(_ / 0).writeStream.format("console").start()
     val checkpointDir = new Path(
       query.asInstanceOf[StreamingQueryWrapper].streamingQuery.resolvedCheckpointRoot)
     val fs = checkpointDir.getFileSystem(spark.sessionState.newHadoopConf())
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/streaming/ui/UISeleniumSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/streaming/ui/UISeleniumSuite.scala
index ca36528..f27fc88 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/ui/UISeleniumSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/ui/UISeleniumSuite.scala
@@ -136,7 +136,7 @@
 
             // Check the query statistics page
             val activeQueryLink =
-              findAll(cssSelector("""#active-table td a""")).flatMap(_.attribute("href")).next
+              findAll(cssSelector("""#active-table td a""")).flatMap(_.attribute("href")).next()
             go to activeQueryLink
 
             findAll(cssSelector("h3"))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/test/DataFrameReaderWriterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/test/DataFrameReaderWriterSuite.scala
index 66e07e6..4b97a0c 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/test/DataFrameReaderWriterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/test/DataFrameReaderWriterSuite.scala
@@ -252,7 +252,7 @@
   }
 
   test("SPARK-32364: later option should override earlier options for save()") {
-    Seq(1).toDF.write
+    Seq(1).toDF().write
       .format("org.apache.spark.sql.test")
       .option("paTh", "1")
       .option("PATH", "2")
@@ -264,7 +264,7 @@
 
     withClue("SPARK-32516: legacy path option behavior") {
       withSQLConf(SQLConf.LEGACY_PATH_OPTION_BEHAVIOR.key -> "true") {
-        Seq(1).toDF.write
+        Seq(1).toDF().write
           .format("org.apache.spark.sql.test")
           .option("paTh", "1")
           .option("PATH", "2")
@@ -277,7 +277,7 @@
   }
 
   test("pass partitionBy as options") {
-    Seq(1).toDF.write
+    Seq(1).toDF().write
       .format("org.apache.spark.sql.test")
       .partitionBy("col1", "col2")
       .save()
@@ -1212,7 +1212,7 @@
     withSQLConf(SQLConf.LEGACY_PATH_OPTION_BEHAVIOR.key -> "true") {
       withTempDir { dir =>
         val path = dir.getCanonicalPath
-        Seq(1).toDF.write.mode("overwrite").parquet(path)
+        Seq(1).toDF().write.mode("overwrite").parquet(path)
 
         // When there is one path parameter to load(), "path" option is overwritten.
         checkAnswer(spark.read.format("parquet").option("path", path).load(path), Row(1))
@@ -1239,7 +1239,7 @@
         "Either remove the path option, or call save() without the parameter"))
     }
 
-    val df = Seq(1).toDF
+    val df = Seq(1).toDF()
     val path = "tmp"
     verifyLoadFails(df.write.option("path", path).parquet(path))
     verifyLoadFails(df.write.option("path", path).parquet(""))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFlatSpecSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFlatSpecSuite.scala
index dfa0348..d4c3d7a 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFlatSpecSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFlatSpecSuite.scala
@@ -26,20 +26,20 @@
 class GenericFlatSpecSuite extends AnyFlatSpec with SharedSparkSessionBase {
   import testImplicits._
 
-  private def ds = Seq((1, 1), (2, 1), (3, 2), (4, 2), (5, 3), (6, 3), (7, 4), (8, 4)).toDS
+  private def ds = Seq((1, 1), (2, 1), (3, 2), (4, 2), (5, 3), (6, 3), (7, 4), (8, 4)).toDS()
 
   "A Simple Dataset" should "have the specified number of elements" in {
-    assert(8 === ds.count)
+    assert(8 === ds.count())
   }
   it should "have the specified number of unique elements" in {
-      assert(8 === ds.distinct.count)
+      assert(8 === ds.distinct().count())
   }
   it should "have the specified number of elements in each column" in {
-    assert(8 === ds.select("_1").count)
-    assert(8 === ds.select("_2").count)
+    assert(8 === ds.select("_1").count())
+    assert(8 === ds.select("_2").count())
   }
   it should "have the correct number of distinct elements in each column" in {
-    assert(8 === ds.select("_1").distinct.count)
-    assert(4 === ds.select("_2").distinct.count)
+    assert(8 === ds.select("_1").distinct().count())
+    assert(4 === ds.select("_2").distinct().count())
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFunSpecSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFunSpecSuite.scala
index d15e5c4..d1b8b2f 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFunSpecSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/test/GenericFunSpecSuite.scala
@@ -26,22 +26,22 @@
 class GenericFunSpecSuite extends AnyFunSpec with SharedSparkSessionBase {
   import testImplicits._
 
-  private def ds = Seq((1, 1), (2, 1), (3, 2), (4, 2), (5, 3), (6, 3), (7, 4), (8, 4)).toDS
+  private def ds = Seq((1, 1), (2, 1), (3, 2), (4, 2), (5, 3), (6, 3), (7, 4), (8, 4)).toDS()
 
   describe("Simple Dataset") {
     it("should have the specified number of elements") {
-      assert(8 === ds.count)
+      assert(8 === ds.count())
     }
     it("should have the specified number of unique elements") {
-      assert(8 === ds.distinct.count)
+      assert(8 === ds.distinct().count())
     }
     it("should have the specified number of elements in each column") {
-      assert(8 === ds.select("_1").count)
-      assert(8 === ds.select("_2").count)
+      assert(8 === ds.select("_1").count())
+      assert(8 === ds.select("_2").count())
     }
     it("should have the correct number of distinct elements in each column") {
-      assert(8 === ds.select("_1").distinct.count)
-      assert(4 === ds.select("_2").distinct.count)
+      assert(8 === ds.select("_1").distinct().count())
+      assert(4 === ds.select("_2").distinct().count())
     }
   }
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/test/GenericWordSpecSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/test/GenericWordSpecSuite.scala
index e693dc9..c0725f7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/test/GenericWordSpecSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/test/GenericWordSpecSuite.scala
@@ -26,25 +26,25 @@
 class GenericWordSpecSuite extends AnyWordSpec with SharedSparkSessionBase {
   import testImplicits._
 
-  private def ds = Seq((1, 1), (2, 1), (3, 2), (4, 2), (5, 3), (6, 3), (7, 4), (8, 4)).toDS
+  private def ds = Seq((1, 1), (2, 1), (3, 2), (4, 2), (5, 3), (6, 3), (7, 4), (8, 4)).toDS()
 
   "A Simple Dataset" when {
     "looked at as complete rows" should {
       "have the specified number of elements" in {
-        assert(8 === ds.count)
+        assert(8 === ds.count())
       }
       "have the specified number of unique elements" in {
-        assert(8 === ds.distinct.count)
+        assert(8 === ds.distinct().count())
       }
     }
     "refined to specific columns" should {
       "have the specified number of elements in each column" in {
-        assert(8 === ds.select("_1").count)
-        assert(8 === ds.select("_2").count)
+        assert(8 === ds.select("_1").count())
+        assert(8 === ds.select("_2").count())
       }
       "have the correct number of distinct elements in each column" in {
-        assert(8 === ds.select("_1").distinct.count)
-        assert(4 === ds.select("_2").distinct.count)
+        assert(8 === ds.select("_1").distinct().count())
+        assert(4 === ds.select("_2").distinct().count())
       }
     }
   }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/util/DataFrameCallbackSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/util/DataFrameCallbackSuite.scala
index f046daa..808f783 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/util/DataFrameCallbackSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/util/DataFrameCallbackSuite.scala
@@ -112,7 +112,7 @@
 
     val df = Seq(1).toDF("i")
 
-    df.foreach(r => f)
+    df.foreach(r => f())
     df.reduce((x, y) => x)
 
     sparkContext.listenerBus.waitUntilEmpty()
diff --git a/sql/core/src/test/scala/org/apache/spark/status/api/v1/sql/SqlResourceWithActualMetricsSuite.scala b/sql/core/src/test/scala/org/apache/spark/status/api/v1/sql/SqlResourceWithActualMetricsSuite.scala
index c63c748..deb2c8f 100644
--- a/sql/core/src/test/scala/org/apache/spark/status/api/v1/sql/SqlResourceWithActualMetricsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/status/api/v1/sql/SqlResourceWithActualMetricsSuite.scala
@@ -128,7 +128,7 @@
       .filter(_.getAs[Int]("age") <= 30)
       .sort()
 
-    ds.toDF
+    ds.toDF()
   }
 
   test("SPARK-44334: Status of a failed DDL/DML with no jobs should be FAILED") {
diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala
index 155861a..e70d058 100644
--- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala
+++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkExecuteStatementOperation.scala
@@ -230,7 +230,7 @@
         result.queryExecution.toString())
       iter = if (sqlContext.getConf(SQLConf.THRIFTSERVER_INCREMENTAL_COLLECT.key).toBoolean) {
         new IterableFetchIterator[Row](new Iterable[Row] {
-          override def iterator: Iterator[Row] = result.toLocalIterator.asScala
+          override def iterator: Iterator[Row] = result.toLocalIterator().asScala
         })
       } else {
         new ArrayFetchIterator[Row](result.collect())
diff --git a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala
index ceba74e..5b76cd6 100644
--- a/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala
+++ b/sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIDriver.scala
@@ -218,7 +218,7 @@
     // Execute -i init files (always in silent mode)
     cli.processInitFiles(sessionState)
 
-    cli.printMasterAndAppId
+    cli.printMasterAndAppId()
 
     if (sessionState.execString != null) {
       exit(cli.processLine(sessionState.execString))
@@ -238,7 +238,7 @@
     reader.setBellEnabled(false)
     reader.setExpandEvents(false)
     // reader.setDebug(new PrintWriter(new FileWriter("writer.debug", true)))
-    getCommandCompleter.foreach(reader.addCompleter)
+    getCommandCompleter().foreach(reader.addCompleter)
 
     val historyDirectory = System.getProperty("user.home")
 
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
index db72218..ddfe01b 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2Suites.scala
@@ -1189,7 +1189,7 @@
   protected val startScript = "../../sbin/start-thriftserver.sh".split("/").mkString(File.separator)
   protected val stopScript = "../../sbin/stop-thriftserver.sh".split("/").mkString(File.separator)
 
-  val localhost = Utils.localCanonicalHostName
+  val localhost = Utils.localCanonicalHostName()
   private var listeningPort: Int = _
   protected def serverPort: Int = listeningPort
 
diff --git a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/SparkMetadataOperationSuite.scala b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/SparkMetadataOperationSuite.scala
index a3f1a06..94f1e53 100644
--- a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/SparkMetadataOperationSuite.scala
+++ b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/SparkMetadataOperationSuite.scala
@@ -36,7 +36,7 @@
     def checkResult(rs: ResultSet, dbNames: Seq[String]): Unit = {
       val expected = dbNames.iterator
       while(rs.next() || expected.hasNext) {
-        assert(rs.getString("TABLE_SCHEM") === expected.next)
+        assert(rs.getString("TABLE_SCHEM") === expected.next())
         assert(rs.getString("TABLE_CATALOG").isEmpty)
       }
       // Make sure there are no more elements
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateHiveTableAsSelectCommand.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateHiveTableAsSelectCommand.scala
index eef2ae1..811d186 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateHiveTableAsSelectCommand.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/CreateHiveTableAsSelectCommand.scala
@@ -65,7 +65,7 @@
       qe.assertCommandExecuted()
     } else {
       tableDesc.storage.locationUri.foreach { p =>
-        DataWritingCommand.assertEmptyRootPath(p, mode, sparkSession.sessionState.newHadoopConf)
+        DataWritingCommand.assertEmptyRootPath(p, mode, sparkSession.sessionState.newHadoopConf())
       }
       // TODO ideally, we should get the output data ready first and then
       // add the relation into catalog, just in case of failure occurs while data
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSchemaInferenceSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSchemaInferenceSuite.scala
index 400befb..8ff209d 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSchemaInferenceSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSchemaInferenceSuite.scala
@@ -163,7 +163,7 @@
   private def testFieldQuery(fields: Seq[String]): Unit = {
     if (!fields.isEmpty) {
       val query = s"SELECT * FROM ${TEST_TABLE_NAME} WHERE ${Random.shuffle(fields).head} >= 0"
-      assert(spark.sql(query).count == NUM_RECORDS)
+      assert(spark.sql(query).count() == NUM_RECORDS)
     }
   }
 
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
index 62b2d84..05d2ca1 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
@@ -2851,7 +2851,7 @@
         .select("data_type")
       // check if the last access time doesn't have the default date of year
       // 1970 as its a wrong access time
-      assert((desc.first.toString.contains("UNKNOWN")))
+      assert((desc.first().toString.contains("UNKNOWN")))
     }
   }
 
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
index b2a6e45..a658067 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveQuerySuite.scala
@@ -880,7 +880,7 @@
       """CREATE TEMPORARY FUNCTION udtf_count2 AS
         |'org.apache.spark.sql.hive.execution.GenericUDTFCount2'
       """.stripMargin)
-    assert(sql("DESCRIBE FUNCTION udtf_count2").count > 1)
+    assert(sql("DESCRIBE FUNCTION udtf_count2").count() > 1)
     sql("DROP TEMPORARY FUNCTION udtf_count2")
   }
 
@@ -946,7 +946,7 @@
       assert(sql(s"list archive ${zipFile.getAbsolutePath}").count() === 1)
       assert(sql(s"list archives ${zipFile.getAbsolutePath} nonexistence").count() === 1)
       assert(sql(s"list archives ${zipFile.getAbsolutePath} " +
-        s"${jarFile.getAbsolutePath}").count === 2)
+        s"${jarFile.getAbsolutePath}").count() === 2)
     }
   }
 
@@ -990,7 +990,7 @@
         filter(_.getString(0).contains(s"${xzFile.getAbsolutePath}")).count() > 0)
       assert(sql(s"list archive ${bz2File.getAbsolutePath}").count() === 1)
       assert(sql(s"list archives ${bz2File.getAbsolutePath} " +
-        s"${xzFile.getAbsolutePath}").count === 2)
+        s"${xzFile.getAbsolutePath}").count() === 2)
     }
   }
 
@@ -1010,7 +1010,7 @@
       sql(s"""ADD FILES "${file3.getAbsolutePath}" ${file4.getAbsoluteFile}""")
       val listFiles = sql(s"LIST FILES ${file1.getAbsolutePath} " +
         s"'${file2.getAbsolutePath}' '${file3.getAbsolutePath}' ${file4.getAbsolutePath}")
-      assert(listFiles.count === 4)
+      assert(listFiles.count() === 4)
       assert(listFiles.filter(_.getString(0).contains(file1.getName)).count() === 1)
       assert(listFiles.filter(
         _.getString(0).contains(file2.getName.replace(" ", "%20"))).count() === 1)
@@ -1046,7 +1046,7 @@
       sql(s"ADD JARS ${jarFile3.getAbsolutePath} '${jarFile4.getAbsoluteFile}'")
       val listFiles = sql(s"LIST JARS '${jarFile1.getAbsolutePath}' " +
         s"${jarFile2.getAbsolutePath} ${jarFile3.getAbsolutePath} '${jarFile4.getAbsoluteFile}'")
-      assert(listFiles.count === 4)
+      assert(listFiles.count() === 4)
       assert(listFiles.filter(
         _.getString(0).contains(jarFile1.getName.replace(" ", "%20"))).count() === 1)
       assert(listFiles.filter(_.getString(0).contains(jarFile2.getName)).count() === 1)
@@ -1082,7 +1082,7 @@
       sql(s"ADD ARCHIVES ${jarFile3.getAbsolutePath} '${jarFile4.getAbsoluteFile}'")
       val listFiles = sql(s"LIST ARCHIVES ${jarFile1.getAbsolutePath} " +
         s"'${jarFile2.getAbsolutePath}' ${jarFile3.getAbsolutePath} '${jarFile4.getAbsolutePath}'")
-      assert(listFiles.count === 4)
+      assert(listFiles.count() === 4)
       assert(listFiles.filter(_.getString(0).contains(jarFile1.getName)).count() === 1)
       assert(listFiles.filter(
         _.getString(0).contains(jarFile2.getName.replace(" ", "%20"))).count() === 1)
@@ -1108,7 +1108,7 @@
       val listFiles = sql("LIST FILES " +
         s"""'${file1.getAbsolutePath}' ${file2.getAbsolutePath} "${file3.getAbsolutePath}"""")
 
-      assert(listFiles.count === 3)
+      assert(listFiles.count() === 3)
       assert(listFiles.filter(_.getString(0).contains(file1.getName)).count() === 1)
       assert(listFiles.filter(_.getString(0).contains(file2.getName)).count() === 1)
       assert(listFiles.filter(
@@ -1134,7 +1134,7 @@
       val listArchives = sql(s"LIST ARCHIVES '${jarFile1.getAbsolutePath}' " +
         s"""${jarFile2.getAbsolutePath} "${jarFile3.getAbsolutePath}"""")
 
-      assert(listArchives.count === 3)
+      assert(listArchives.count() === 3)
       assert(listArchives.filter(_.getString(0).contains(jarFile1.getName)).count() === 1)
       assert(listArchives.filter(_.getString(0).contains(jarFile2.getName)).count() === 1)
       assert(listArchives.filter(
@@ -1159,7 +1159,7 @@
       sql(s"ADD JAR '${jarFile6.getAbsolutePath}'")
       val listJars = sql(s"LIST JARS '${jarFile4.getAbsolutePath}' " +
         s"""${jarFile5.getAbsolutePath} "${jarFile6.getAbsolutePath}"""")
-      assert(listJars.count === 3)
+      assert(listJars.count() === 3)
       assert(listJars.filter(_.getString(0).contains(jarFile4.getName)).count() === 1)
       assert(listJars.filter(_.getString(0).contains(jarFile5.getName)).count() === 1)
       assert(listJars.filter(
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUDFSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUDFSuite.scala
index 1eff35c..d188e2d 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUDFSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveUDFSuite.scala
@@ -493,7 +493,7 @@
         sql("SELECT input_file_name() as file FROM external_t5").head().getString(0)
       assert(answer1.contains("data1") || answer1.contains("data2"))
 
-      val count2 = sql("SELECT input_file_name() as file FROM external_t5").distinct().count
+      val count2 = sql("SELECT input_file_name() as file FROM external_t5").distinct().count()
       assert(count2 == 2)
       sql("DROP TABLE external_t5")
     }
@@ -515,7 +515,7 @@
         sql("SELECT input_file_name() as file FROM external_parquet").head().getString(0)
       assert(answer3.contains("external_parquet"))
 
-      val count3 = sql("SELECT input_file_name() as file FROM external_parquet").distinct().count
+      val count3 = sql("SELECT input_file_name() as file FROM external_parquet").distinct().count()
       assert(count3 == 1)
       sql("DROP TABLE external_parquet")
     }
@@ -527,7 +527,7 @@
       sql("SELECT input_file_name() as file FROM parquet_tmp").head().getString(0)
     assert(answer4.contains("parquet_tmp"))
 
-    val count4 = sql("SELECT input_file_name() as file FROM parquet_tmp").distinct().count
+    val count4 = sql("SELECT input_file_name() as file FROM parquet_tmp").distinct().count()
     assert(count4 == 1)
     sql("DROP TABLE parquet_tmp")
   }
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
index 0ede331..d8c28e1 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
@@ -149,8 +149,8 @@
         Order(1, "Atlas", "MTB", 434, "2015-01-07", "John D", "Pacifica", "CA", 20151),
         Order(11, "Swift", "YFlikr", 137, "2015-01-23", "John D", "Hayward", "CA", 20151))
 
-      orders.toDF.createOrReplaceTempView("orders1")
-      orderUpdates.toDF.createOrReplaceTempView("orderupdates1")
+      orders.toDF().createOrReplaceTempView("orders1")
+      orderUpdates.toDF().createOrReplaceTempView("orderupdates1")
 
       withTable("orders", "orderupdates") {
         sql(
@@ -356,7 +356,7 @@
 
   test("explode nested Field") {
     withTempView("nestedArray") {
-      Seq(NestedArray1(NestedArray2(Seq(1, 2, 3)))).toDF.createOrReplaceTempView("nestedArray")
+      Seq(NestedArray1(NestedArray2(Seq(1, 2, 3)))).toDF().createOrReplaceTempView("nestedArray")
       checkAnswer(
         sql("SELECT ints FROM nestedArray LATERAL VIEW explode(a.b) a AS ints"),
         Row(1) :: Row(2) :: Row(3) :: Nil)
@@ -1410,7 +1410,7 @@
 
   test("run sql directly on files - hive") {
     withTempPath(f => {
-      spark.range(100).toDF.write.parquet(f.getCanonicalPath)
+      spark.range(100).toDF().write.parquet(f.getCanonicalPath)
 
       checkError(
         exception = intercept[AnalysisException] {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/UDAQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/UDAQuerySuite.scala
index 0bd6b14..2eff462 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/UDAQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/UDAQuerySuite.scala
@@ -129,8 +129,8 @@
     s1
   }
   def finish(s: Array[Double]): Array[Double] = s
-  def bufferEncoder: Encoder[Array[Double]] = ExpressionEncoder[Array[Double]]
-  def outputEncoder: Encoder[Array[Double]] = ExpressionEncoder[Array[Double]]
+  def bufferEncoder: Encoder[Array[Double]] = ExpressionEncoder[Array[Double]]()
+  def outputEncoder: Encoder[Array[Double]] = ExpressionEncoder[Array[Double]]()
 }
 
 abstract class UDAQuerySuite extends QueryTest with SQLTestUtils with TestHiveSingleton {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala
index 43bcee5..0330ce5 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala
@@ -88,7 +88,7 @@
     withTempPath { dir =>
       withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql(s"SELECT CAST(value as ${dataType.sql}) id FROM t1"))
 
@@ -117,7 +117,7 @@
     withTempPath { dir =>
       withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(
           dir,
@@ -148,7 +148,7 @@
     withTempPath { dir =>
       withTempTable("t1", "nativeOrcTable", "hiveOrcTable") {
         import spark.implicits._
-        spark.range(values).map(_ => Random.nextLong).createOrReplaceTempView("t1")
+        spark.range(values).map(_ => Random.nextLong()).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT value % 2 AS p, value AS id FROM t1"), Some("p"))
 
@@ -272,7 +272,7 @@
         import spark.implicits._
         val middle = width / 2
         val selectExpr = (1 to width).map(i => s"value as c$i")
-        spark.range(values).map(_ => Random.nextLong).toDF()
+        spark.range(values).map(_ => Random.nextLong()).toDF()
           .selectExpr(selectExpr: _*).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT * FROM t1"))
@@ -304,7 +304,7 @@
         import spark.implicits._
         val selectExprCore = (1 to width).map(i => s"'f$i', value").mkString(",")
         val selectExpr = Seq(s"named_struct($selectExprCore) as c1")
-        spark.range(values).map(_ => Random.nextLong).toDF()
+        spark.range(values).map(_ => Random.nextLong()).toDF()
           .selectExpr(selectExpr: _*).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT * FROM t1"))
@@ -343,7 +343,7 @@
           .map(_ => s"$structExpr").mkString(",")
         val selectExpr = Seq(s"array($arrayExprElements) as c1")
         print(s"select expression is $selectExpr\n")
-        spark.range(values).map(_ => Random.nextLong).toDF()
+        spark.range(values).map(_ => Random.nextLong()).toDF()
           .selectExpr(selectExpr: _*).createOrReplaceTempView("t1")
 
         prepareTable(dir, spark.sql("SELECT * FROM t1"))
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/Interval.scala b/streaming/src/main/scala/org/apache/spark/streaming/Interval.scala
index 3f5be78..e1bd6df 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/Interval.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/Interval.scala
@@ -32,7 +32,7 @@
   }
 
   def < (that: Interval): Boolean = {
-    if (this.duration != that.duration) {
+    if (this.duration() != that.duration()) {
       throw new Exception("Comparing two intervals with different durations [" + this + ", "
         + that + "]")
     }
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/State.scala b/streaming/src/main/scala/org/apache/spark/streaming/State.scala
index c4cd1a9..fbfb910 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/State.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/State.scala
@@ -120,10 +120,10 @@
   /**
    * Get the state as a `scala.Option`. It will be `Some(state)` if it exists, otherwise `None`.
    */
-  @inline final def getOption(): Option[S] = if (exists) Some(get()) else None
+  @inline final def getOption(): Option[S] = if (exists()) Some(get()) else None
 
   @inline final override def toString(): String = {
-    getOption.map { _.toString }.getOrElse("<state not set>")
+    getOption().map { _.toString }.getOrElse("<state not set>")
   }
 }
 
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/SocketInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/SocketInputDStream.scala
index 9d3facc..883d56c 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/SocketInputDStream.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/SocketInputDStream.scala
@@ -88,7 +88,7 @@
   def receive(): Unit = {
     try {
       val iterator = bytesToObjects(socket.getInputStream())
-      while(!isStopped && iterator.hasNext) {
+      while(!isStopped() && iterator.hasNext) {
         store(iterator.next())
       }
       if (!isStopped()) {
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/rdd/MapWithStateRDD.scala b/streaming/src/main/scala/org/apache/spark/streaming/rdd/MapWithStateRDD.scala
index 662312b..097eb9d 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/rdd/MapWithStateRDD.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/rdd/MapWithStateRDD.scala
@@ -55,10 +55,10 @@
     dataIterator.foreach { case (key, value) =>
       wrappedState.wrap(newStateMap.get(key))
       val returned = mappingFunction(batchTime, key, Some(value), wrappedState)
-      if (wrappedState.isRemoved) {
+      if (wrappedState.isRemoved()) {
         newStateMap.remove(key)
-      } else if (wrappedState.isUpdated
-          || (wrappedState.exists && timeoutThresholdTime.isDefined)) {
+      } else if (wrappedState.isUpdated()
+          || (wrappedState.exists() && timeoutThresholdTime.isDefined)) {
         newStateMap.put(key, wrappedState.get(), batchTime.milliseconds)
       }
       mappedData ++= returned
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala
index 7a561ec..7087f16 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala
@@ -82,7 +82,7 @@
         val countIterator = new CountingIterator(iterator)
         val putResult = blockManager.putIterator(blockId, countIterator, storageLevel,
           tellMaster = true)
-        numRecords = countIterator.count
+        numRecords = countIterator.count()
         putResult
       case ByteBufferBlock(byteBuffer) =>
         blockManager.putBytes(
@@ -178,7 +178,7 @@
       case IteratorBlock(iterator) =>
         val countIterator = new CountingIterator(iterator)
         val serializedBlock = serializerManager.dataSerialize(blockId, countIterator)
-        numRecords = countIterator.count
+        numRecords = countIterator.count()
         serializedBlock
       case ByteBufferBlock(byteBuffer) =>
         new ChunkedByteBuffer(byteBuffer.duplicate())
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManager.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManager.scala
index 1037950..5aa2a9d 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManager.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManager.scala
@@ -128,7 +128,7 @@
     logDebug(s"Executors (${allExecIds.size}) = ${allExecIds}")
 
     if (allExecIds.nonEmpty && allExecIds.size > minNumExecutors) {
-      val execIdsWithReceivers = receiverTracker.allocatedExecutors.values.flatten.toSeq
+      val execIdsWithReceivers = receiverTracker.allocatedExecutors().values.flatten.toSeq
       logInfo(s"Executors with receivers (${execIdsWithReceivers.size}): ${execIdsWithReceivers}")
 
       val removableExecIds = allExecIds.diff(execIdsWithReceivers)
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala
index 13d10ec..29bccc7 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala
@@ -78,7 +78,7 @@
 
     // attach rate controllers of input streams to receive batch completion updates
     for {
-      inputDStream <- ssc.graph.getInputStreams
+      inputDStream <- ssc.graph.getInputStreams()
       rateController <- inputDStream.rateController
     } ssc.addStreamingListener(rateController)
 
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala
index 07c9e63..c3f2a04 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala
@@ -59,7 +59,7 @@
   import FileBasedWriteAheadLog._
 
   private val pastLogs = new ArrayBuffer[LogInfo]
-  private val callerName = getCallerName
+  private val callerName = getCallerName()
 
   private val threadpoolName = {
     "WriteAheadLogManager" + callerName.map(c => s" for $c").getOrElse("")
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/RecurringTimer.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/RecurringTimer.scala
index 3ffb2c1..3ebe39f 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/util/RecurringTimer.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/util/RecurringTimer.scala
@@ -26,7 +26,7 @@
 
   private val thread = new Thread("RecurringTimer - " + name) {
     setDaemon(true)
-    override def run(): Unit = { loop }
+    override def run(): Unit = { loop() }
   }
 
   @volatile private var prevTime = -1L
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala
index 4429cde..9060828 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/BasicOperationsSuite.scala
@@ -775,7 +775,7 @@
 
         // verify that the latest input blocks are present but the earliest blocks have been removed
         assert(latestBlockRdd.isValid)
-        assert(latestBlockRdd.collect != null)
+        assert(latestBlockRdd.collect() != null)
         assert(!earliestBlockRdd.isValid)
         earliestBlockRdd.blockIds.foreach { blockId =>
           assert(!ssc.sparkContext.env.blockManager.master.contains(blockId))
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala
index 6757cb7..9760682 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala
@@ -168,7 +168,7 @@
 
       eventually(timeout(10.seconds)) {
         val checkpointFilesOfLatestTime = Checkpoint.getCheckpointFiles(checkpointDir).filter {
-          _.getName.contains(clock.getTimeMillis.toString)
+          _.getName.contains(clock.getTimeMillis().toString)
         }
         // Checkpoint files are written twice for every batch interval. So assert that both
         // are written to make sure that both of them have been written.
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
index 2a22433..ca8307b 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
@@ -322,7 +322,7 @@
     // set up the network stream using the test receiver
     withStreamingContext(new StreamingContext(conf, batchDuration)) { ssc =>
       val networkStream = ssc.receiverStream[Int](testReceiver)
-      val countStream = networkStream.count
+      val countStream = networkStream.count()
 
       val outputStream = new TestOutputStream(countStream, outputQueue)
       outputStream.register()
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/MapWithStateSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/MapWithStateSuite.scala
index 09048c8..e88aab2b 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/MapWithStateSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/MapWithStateSuite.scala
@@ -66,17 +66,17 @@
         shouldBeTimingOut: Boolean = false
       ): Unit = {
       if (expectedData.isDefined) {
-        assert(state.exists)
+        assert(state.exists())
         assert(state.get() === expectedData.get)
         assert(state.getOption() === expectedData)
-        assert(state.getOption.getOrElse(-1) === expectedData.get)
+        assert(state.getOption().getOrElse(-1) === expectedData.get)
       } else {
-        assert(!state.exists)
+        assert(!state.exists())
         intercept[NoSuchElementException] {
           state.get()
         }
         assert(state.getOption() === None)
-        assert(state.getOption.getOrElse(-1) === -1)
+        assert(state.getOption().getOrElse(-1) === -1)
       }
 
       assert(state.isTimingOut() === shouldBeTimingOut)
@@ -161,7 +161,7 @@
 
     // state maintains running count, and updated count is returned
     val mappingFunc = (key: String, value: Option[Int], state: State[Int]) => {
-      val sum = value.getOrElse(0) + state.getOption.getOrElse(0)
+      val sum = value.getOrElse(0) + state.getOption().getOrElse(0)
       state.update(sum)
       sum
     }
@@ -206,7 +206,7 @@
 
     // state maintains running count, key string doubled and returned
     val mappingFunc = (batchTime: Time, key: String, value: Option[Int], state: State[Int]) => {
-      val sum = value.getOrElse(0) + state.getOption.getOrElse(0)
+      val sum = value.getOrElse(0) + state.getOption().getOrElse(0)
       state.update(sum)
       Some(key * 2)
     }
@@ -298,7 +298,7 @@
       )
 
     val mappingFunc = (time: Time, key: String, value: Option[Int], state: State[Int]) => {
-      val sum = value.getOrElse(0) + state.getOption.getOrElse(0)
+      val sum = value.getOrElse(0) + state.getOption().getOrElse(0)
       val output = (key, sum)
       state.update(sum)
       Some(output)
@@ -336,7 +336,7 @@
       )
 
     val mappingFunc = (time: Time, key: String, value: Option[Int], state: State[Int]) => {
-      val sum = value.getOrElse(0) + state.getOption.getOrElse(0)
+      val sum = value.getOrElse(0) + state.getOption().getOrElse(0)
       val output = (key, sum)
       state.update(sum)
       None.asInstanceOf[Option[Int]]
@@ -385,7 +385,7 @@
       )
 
     val mappingFunc = (time: Time, key: String, value: Option[Int], state: State[Int]) => {
-      if (state.exists) {
+      if (state.exists()) {
         state.remove()
         Some(key)
       } else {
@@ -413,7 +413,7 @@
       if (value.isDefined) {
         state.update(1)
       }
-      if (state.isTimingOut) {
+      if (state.isTimingOut()) {
         Some(key)
       } else {
         None
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala b/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala
index c1af91a..ffaa82d 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/MasterFailureTest.scala
@@ -333,7 +333,7 @@
     try {
       // If it is the first killing, then allow the first checkpoint to be created
       val minKillWaitTime = if (MasterFailureTest.killCount == 0) 5000 else 2000
-      val killWaitTime = minKillWaitTime + math.abs(Random.nextLong % maxKillWaitTime)
+      val killWaitTime = minKillWaitTime + math.abs(Random.nextLong() % maxKillWaitTime)
       logInfo("Kill wait time = " + killWaitTime)
       Thread.sleep(killWaitTime)
       logInfo(
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala
index 1913552..1bf74e6 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala
@@ -361,7 +361,7 @@
     }
 
     def dataToByteBuffer(b: Seq[String]) =
-      serializerManager.dataSerialize(generateBlockId, b.iterator)
+      serializerManager.dataSerialize(generateBlockId(), b.iterator)
 
     val blocks = data.grouped(10).toSeq
 
@@ -425,7 +425,7 @@
       handler: ReceivedBlockHandler,
       block: ReceivedBlock
     ): (StreamBlockId, ReceivedBlockStoreResult) = {
-    val blockId = generateBlockId
+    val blockId = generateBlockId()
     val blockStoreResult = handler.storeBlock(blockId, block)
     logDebug("Done inserting")
     (blockId, blockStoreResult)
@@ -435,7 +435,8 @@
     getLogFilesInDirectory(checkpointDirToLogDir(tempDirectory.toString, streamId))
   }
 
-  private def generateBlockId(): StreamBlockId = StreamBlockId(streamId, scala.util.Random.nextLong)
+  private def generateBlockId(): StreamBlockId =
+    StreamBlockId(streamId, scala.util.Random.nextLong())
 }
 
 class ReceivedBlockHandlerSuite extends BaseReceivedBlockHandlerSuite(false)
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala
index ada6a9a..e221a3a 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala
@@ -385,7 +385,7 @@
   /** Generate blocks infos using random ids */
   def generateBlockInfos(blockCount: Int = 5): Seq[ReceivedBlockInfo] = {
     List.fill(blockCount)(ReceivedBlockInfo(streamId, Some(0L), None,
-      BlockManagerBasedStoreResult(StreamBlockId(streamId, math.abs(Random.nextInt)), Some(0L))))
+      BlockManagerBasedStoreResult(StreamBlockId(streamId, math.abs(Random.nextInt())), Some(0L))))
   }
 
   /**
@@ -416,7 +416,7 @@
    * Get all the data written in the given write ahead log files. By default, it will read all
    * files in the test log directory.
    */
-  def getWrittenLogData(logFiles: Seq[String] = getWriteAheadLogFiles)
+  def getWrittenLogData(logFiles: Seq[String] = getWriteAheadLogFiles())
     : Seq[ReceivedBlockTrackerLogEvent] = {
     logFiles.flatMap {
       file => new FileBasedWriteAheadLogReader(file, hadoopConf).toSeq
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
index b07fd73..afe6c73 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala
@@ -74,8 +74,8 @@
 
     // Verify that receiver was started
     assert(receiver.callsRecorder.calls === Seq("onStart"))
-    assert(executor.isReceiverStarted)
-    assert(receiver.isStarted)
+    assert(executor.isReceiverStarted())
+    assert(receiver.isStarted())
     assert(!receiver.isStopped())
     assert(receiver.otherThread.isAlive)
     eventually(timeout(100.milliseconds), interval(10.milliseconds)) {
@@ -111,8 +111,8 @@
     receiver.restart("restarting", null, 100)
     eventually(timeout(10.seconds), interval(10.milliseconds)) {
       // below verification ensures for now receiver is already restarted
-      assert(receiver.isStarted)
-      assert(!receiver.isStopped)
+      assert(receiver.isStarted())
+      assert(!receiver.isStopped())
       assert(receiver.receiving)
 
       // both receiver supervisor and receiver should be stopped first, and started
@@ -127,7 +127,7 @@
     // Verify that stopping actually stops the thread
     failAfter(1.second) {
       receiver.stop("test")
-      assert(receiver.isStopped)
+      assert(receiver.isStopped())
       assert(!receiver.otherThread.isAlive)
 
       // The thread that started the executor should complete
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
index 29eb1db..c704a41 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala
@@ -177,7 +177,7 @@
       ssc.start()
     }
     assert(ssc.getState() === StreamingContextState.STOPPED)
-    assert(ssc.scheduler.isStarted === false)
+    assert(ssc.scheduler.isStarted() === false)
   }
 
   test("start should set local properties of streaming jobs correctly") {
@@ -600,7 +600,7 @@
       newContextCreated = true
       val newSsc = new StreamingContext(sc, batchDuration)
       val input = addInputStream(newSsc)
-      input.foreachRDD { rdd => rdd.count }
+      input.foreachRDD { rdd => rdd.count() }
       newSsc
     }
 
@@ -641,7 +641,7 @@
     // getActiveOrCreate and getActive should return independently created context after activating
     testGetActiveOrCreate {
       val sc = new SparkContext(conf)
-      ssc = creatingFunc(sc)  // Create
+      ssc = creatingFunc(sc)()  // Create
       assert(StreamingContext.getActive().isEmpty,
         "new initialized context returned before starting")
       ssc.start()
@@ -733,13 +733,13 @@
       conf.clone.set("spark.streaming.clock", "org.apache.spark.util.ManualClock"))
     ssc = new StreamingContext(sc, Seconds(1))
     val input = addInputStream(ssc)
-    input.foreachRDD { rdd => rdd.count }
+    input.foreachRDD { rdd => rdd.count() }
     ssc.start()
 
     // Creating another streaming context should not create errors
     val anotherSsc = new StreamingContext(sc, Seconds(10))
     val anotherInput = addInputStream(anotherSsc)
-    anotherInput.foreachRDD { rdd => rdd.count }
+    anotherInput.foreachRDD { rdd => rdd.count() }
 
     val exception = intercept[IllegalStateException] {
       anotherSsc.start()
@@ -760,7 +760,7 @@
     require(ssc.getState() === StreamingContextState.INITIALIZED)
     val input = addInputStream(ssc)
     val transformed = input.map { x => x}
-    transformed.foreachRDD { rdd => rdd.count }
+    transformed.foreachRDD { rdd => rdd.count() }
 
     def testForException(clue: String, expectedErrorMsg: String)(body: => Unit): Unit = {
       withClue(clue) {
@@ -927,7 +927,7 @@
     val thread = new Thread() {
       override def run(): Unit = {
         logInfo("Receiving started")
-        while (!isStopped) {
+        while (!isStopped()) {
           store(TestReceiver.counter.getAndIncrement)
         }
         logInfo("Receiving stopped at count value of " + TestReceiver.counter.get())
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
index 2ec4b5b..63899f9 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala
@@ -117,7 +117,7 @@
   test("receiver info reporting") {
     ssc = new StreamingContext("local[2]", "test", Milliseconds(1000))
     val inputStream = ssc.receiverStream(new StreamingListenerSuiteReceiver)
-    inputStream.foreachRDD(_.count)
+    inputStream.foreachRDD(_.count())
 
     val collector = new ReceiverInfoCollector
     ssc.addStreamingListener(collector)
@@ -163,7 +163,7 @@
   test("don't call ssc.stop in listener") {
     ssc = new StreamingContext("local[2]", "ssc", Milliseconds(1000))
     val inputStream = ssc.receiverStream(new StreamingListenerSuiteReceiver)
-    inputStream.foreachRDD(_.count)
+    inputStream.foreachRDD(_.count())
 
     startStreamingContextAndCallStop(ssc)
   }
@@ -171,7 +171,7 @@
   test("onBatchCompleted with successful batch") {
     ssc = new StreamingContext("local[2]", "test", Milliseconds(1000))
     val inputStream = ssc.receiverStream(new StreamingListenerSuiteReceiver)
-    inputStream.foreachRDD(_.count)
+    inputStream.foreachRDD(_.count())
 
     val failureReasons = startStreamingContextAndCollectFailureReasons(ssc)
     assert(failureReasons != null && failureReasons.isEmpty,
@@ -220,7 +220,7 @@
     ssc = new StreamingContext("local[2]", "test", Milliseconds(1000))
     ssc.addStreamingListener(streamingListener)
     val inputStream = ssc.receiverStream(new StreamingListenerSuiteReceiver)
-    inputStream.foreachRDD(_.count)
+    inputStream.foreachRDD(_.count())
     ssc.start()
     ssc.stop()
 
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
index 55e4a46..dc6ebaf 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala
@@ -404,7 +404,7 @@
     logInfo("numBatches = " + numBatches + ", numExpectedOutput = " + numExpectedOutput)
 
     // Get the output buffer
-    val outputStream = ssc.graph.getOutputStreams.
+    val outputStream = ssc.graph.getOutputStreams().
       filter(_.isInstanceOf[TestOutputStreamWithPartitions[_]]).
       head.asInstanceOf[TestOutputStreamWithPartitions[V]]
     val output = outputStream.output
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala
index 979cfde..eab8012 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala
@@ -80,7 +80,7 @@
       try {
         rdd.foreach { _ =>
           // Failing the task with id 15 to ensure only one task fails
-          if (TaskContext.get.taskAttemptId() % 15 == 0) {
+          if (TaskContext.get().taskAttemptId() % 15 == 0) {
             throw new RuntimeException("Oops")
           }
         }
@@ -97,7 +97,7 @@
 
       val sparkUI = ssc.sparkContext.ui.get
 
-      sparkUI.getDelegatingHandlers.count(_.getContextPath.contains("/streaming")) should be (5)
+      sparkUI.getDelegatingHandlers.count(_.getContextPath().contains("/streaming")) should be (5)
 
       eventually(timeout(10.seconds), interval(50.milliseconds)) {
         go to (sparkUI.webUrl.stripSuffix("/"))
@@ -212,7 +212,7 @@
 
       ssc.stop(false)
 
-      sparkUI.getDelegatingHandlers.count(_.getContextPath.contains("/streaming")) should be (0)
+      sparkUI.getDelegatingHandlers.count(_.getContextPath().contains("/streaming")) should be (0)
 
       eventually(timeout(10.seconds), interval(50.milliseconds)) {
         go to (sparkUI.webUrl.stripSuffix("/"))
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/rdd/MapWithStateRDDSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/rdd/MapWithStateRDDSuite.scala
index 1b59a8c..0250ec9 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/rdd/MapWithStateRDDSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/rdd/MapWithStateRDDSuite.scala
@@ -108,7 +108,7 @@
           case Some("get-state") =>
             Some(state.getOption().getOrElse(-1))
           case Some("update-state") =>
-            if (state.exists) state.update(state.get + 1) else state.update(0)
+            if (state.exists()) state.update(state.get() + 1) else state.update(0)
             None
           case Some("remove-state") =>
             removedStates += state.get()
@@ -232,7 +232,7 @@
         // else if the data is 2, remove the state if it exists
         data match {
           case Some(1) =>
-            if (state.exists()) { state.update(state.get + 1) }
+            if (state.exists()) { state.update(state.get() + 1) }
             else state.update(0)
           case Some(2) =>
             state.remove()
@@ -303,7 +303,7 @@
     def rddCollectFunc(rdd: RDD[MapWithStateRDDRecord[Int, Int, Int]])
       : Set[(List[(Int, Int, Long)], List[Int])] = {
       rdd.map { record => (record.stateMap.getAll().toList, record.mappedData.toList) }
-         .collect.toSet
+        .collect().toSet
     }
 
     /** Generate MapWithStateRDD with data RDD having a long lineage */
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManagerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManagerSuite.scala
index c2b0392..7d9dfb1 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManagerSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/scheduler/ExecutorAllocationManagerSuite.scala
@@ -61,7 +61,7 @@
     withAllocationManager(numReceivers = 1, conf = conf) {
       case (receiverTracker, allocationManager) =>
 
-      when(receiverTracker.allocatedExecutors).thenReturn(Map(1 -> Some("1")))
+      when(receiverTracker.allocatedExecutors()).thenReturn(Map(1 -> Some("1")))
 
       /** Add data point for batch processing time and verify executor allocation */
       def addBatchProcTimeAndVerifyAllocation(batchProcTimeMs: Double)(body: => Unit): Unit = {
@@ -239,7 +239,7 @@
 
       reset(allocationClient)
       when(allocationClient.getExecutorIds()).thenReturn(execIds)
-      when(receiverTracker.allocatedExecutors).thenReturn(receiverExecIds)
+      when(receiverTracker.allocatedExecutors()).thenReturn(receiverExecIds)
       killExecutor(allocationManager)
       if (expectedKilledExec.nonEmpty) {
         verify(allocationClient, times(1)).killExecutor(meq(expectedKilledExec.get))
diff --git a/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala b/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala
index a46a7fb..07157da 100644
--- a/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala
+++ b/tools/src/main/scala/org/apache/spark/tools/GenerateMIMAIgnore.scala
@@ -126,7 +126,7 @@
       .writeAll(previousContents + privateClasses.mkString("\n"))
     // scalastyle:off println
     println("Created : .generated-mima-class-excludes in current directory.")
-    val previousMembersContents = Try(File(".generated-mima-member-excludes").lines)
+    val previousMembersContents = Try(File(".generated-mima-member-excludes").lines())
       .getOrElse(Iterator.empty).mkString("\n")
     File(".generated-mima-member-excludes").writeAll(previousMembersContents +
       privateMembers.mkString("\n"))
@@ -150,7 +150,7 @@
   private def getClasses(packageName: String): Set[String] = {
     val finder = ClassFinder(maybeOverrideAsmVersion = Some(Opcodes.ASM7))
     finder
-      .getClasses
+      .getClasses()
       .map(_.name)
       .filter(_.startsWith(packageName))
       .filterNot(shouldExclude)