| /* |
| 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.context |
| |
| import org.apache.spark.sql.{DataFrame, Row} |
| import org.apache.spark.sql.types._ |
| import org.scalatest._ |
| |
| import org.apache.griffin.measure.SparkSuiteBase |
| |
| class DataFrameCacheTest extends FlatSpec with Matchers with SparkSuiteBase { |
| |
| def createDataFrame(arr: Seq[Int]): DataFrame = { |
| val schema = StructType(Array( |
| StructField("id", LongType), |
| StructField("name", StringType), |
| StructField("age", IntegerType) |
| )) |
| val rows = arr.map { i => |
| Row(i.toLong, s"name_$i", i + 15) |
| } |
| val rowRdd = spark.sparkContext.parallelize(rows) |
| spark.createDataFrame(rowRdd, schema) |
| } |
| |
| "data frame cache" should "be able to cache and uncache data frames" in { |
| val dfCache = DataFrameCache() |
| val df1 = createDataFrame(1 to 5) |
| val df2 = createDataFrame(1 to 10) |
| val df3 = createDataFrame(1 to 15) |
| |
| // cache |
| dfCache.cacheDataFrame("t1", df1) |
| dfCache.cacheDataFrame("t2", df2) |
| dfCache.cacheDataFrame("t3", df3) |
| dfCache.dataFrames.get("t2") should be (Some(df2)) |
| |
| // uncache |
| dfCache.uncacheDataFrame("t2") |
| dfCache.dataFrames.get("t2") should be (None) |
| dfCache.trashDataFrames.toList should be (df2 :: Nil) |
| |
| // uncache all |
| dfCache.uncacheAllDataFrames() |
| dfCache.dataFrames.toMap should be (Map[String, DataFrame]()) |
| dfCache.trashDataFrames.toList should be (df2 :: df1 :: df3 :: Nil) |
| |
| // clear all trash |
| dfCache.clearAllTrashDataFrames() |
| dfCache.trashDataFrames.toList should be (Nil) |
| } |
| |
| |
| } |