/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.griffin.measure.sink

import org.apache.spark.sql.{DataFrame, Row}
import org.apache.spark.sql.types._
import org.scalatest.{FlatSpec, Matchers}

import org.apache.griffin.measure.{Loggable, SparkSuiteBase}
import org.apache.griffin.measure.configuration.dqdefinition.SinkParam
import org.apache.griffin.measure.configuration.enums.ProcessType.BatchProcessType
import org.apache.griffin.measure.context.{ContextId, DQContext}

trait SinkTestBase extends FlatSpec with Matchers with SparkSuiteBase with Loggable {

  var sinkParams: Seq[SinkParam]

  def getDqContext(name: String = "test-context"): DQContext = {
    DQContext(ContextId(System.currentTimeMillis), name, Nil, sinkParams, BatchProcessType)(spark)
  }

  def createDataFrame(arr: Seq[Int]): DataFrame = {
    val schema = StructType(
      Array(
        StructField("id", LongType),
        StructField("name", StringType),
        StructField("sex", StringType),
        StructField("age", IntegerType)))
    val rows = arr.map { i =>
      Row(i.toLong, s"name_$i", if (i % 2 == 0) "man" else "women", i + 15)
    }
    val rowRdd = spark.sparkContext.parallelize(rows)
    spark.createDataFrame(rowRdd, schema)
  }
}