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Posted to reviews@spark.apache.org by marmbrus <gi...@git.apache.org> on 2015/12/17 19:34:46 UTC

[GitHub] spark pull request: [SPARK-8861][SPARK-8862][SQL] Add basic instru...

Github user marmbrus commented on a diff in the pull request:

    https://github.com/apache/spark/pull/7774#discussion_r47942483
  
    --- Diff: sql/core/src/test/scala/org/apache/spark/sql/ui/SQLListenerSuite.scala ---
    @@ -0,0 +1,347 @@
    +/*
    + * 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.spark.sql.ui
    +
    +import java.util.Properties
    +
    +import org.apache.spark.{SparkException, SparkContext, SparkConf, SparkFunSuite}
    +import org.apache.spark.executor.TaskMetrics
    +import org.apache.spark.scheduler._
    +import org.apache.spark.sql.{DataFrame, SQLContext}
    +import org.apache.spark.sql.execution.SQLExecution
    +import org.apache.spark.sql.test.TestSQLContext
    +
    +class SQLListenerSuite extends SparkFunSuite {
    +
    +  private def createTestDataFrame: DataFrame = {
    +    import TestSQLContext.implicits._
    +    Seq(
    +      (1, 1),
    +      (2, 2)
    +    ).toDF().filter("_1 > 1")
    +  }
    +
    +  private def createProperties(executionId: Long): Properties = {
    +    val properties = new Properties()
    +    properties.setProperty(SQLExecution.EXECUTION_ID_KEY, executionId.toString)
    +    properties
    +  }
    +
    +  private def createStageInfo(stageId: Int, attemptId: Int): StageInfo = new StageInfo(
    +    stageId = stageId,
    +    attemptId = attemptId,
    +    // The following fields are not used in tests
    +    name = "",
    +    numTasks = 0,
    +    rddInfos = Nil,
    +    parentIds = Nil,
    +    details = ""
    +  )
    +
    +  private def createTaskInfo(taskId: Int, attempt: Int): TaskInfo = new TaskInfo(
    +    taskId = taskId,
    +    attempt = attempt,
    +    // The following fields are not used in tests
    +    index = 0,
    +    launchTime = 0,
    +    executorId = "",
    +    host = "",
    +    taskLocality = null,
    +    speculative = false
    +  )
    +
    +  private def createTaskMetrics(accumulatorUpdates: Map[Long, Any]): TaskMetrics = {
    +    val metrics = new TaskMetrics
    +    metrics.setAccumulatorsUpdater(() => accumulatorUpdates)
    +    metrics.updateAccumulators()
    +    metrics
    +  }
    +
    +  test("basic") {
    +    val listener = new SQLListener(TestSQLContext)
    +    val executionId = 0
    +    val df = createTestDataFrame
    +    val accumulatorIds =
    +      SparkPlanGraph(df.queryExecution.executedPlan).nodes.flatMap(_.metrics.map(_.accumulatorId))
    +    // Assume all accumulators are long
    +    var accumulatorValue = 0L
    +    val accumulatorUpdates = accumulatorIds.map { id =>
    +      accumulatorValue += 1L
    +      (id, accumulatorValue)
    +    }.toMap
    +
    +    listener.onExecutionStart(
    +      executionId,
    +      "test",
    +      "test",
    +      df.queryExecution.toString,
    +      SparkPlanGraph(df.queryExecution.executedPlan),
    +      System.currentTimeMillis())
    +
    +    val executionUIData = listener.executionIdToData(0)
    +
    +    listener.onJobStart(SparkListenerJobStart(
    +      jobId = 0,
    +      time = System.currentTimeMillis(),
    +      stageInfos = Seq(
    +        createStageInfo(0, 0),
    +        createStageInfo(1, 0)
    +      ),
    +      createProperties(executionId)))
    +    listener.onStageSubmitted(SparkListenerStageSubmitted(createStageInfo(0, 0)))
    +
    +    assert(listener.getExecutionMetrics(0).isEmpty)
    +
    +    listener.onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate("", Seq(
    +      // (task id, stage id, stage attempt, metrics)
    +      (0L, 0, 0, createTaskMetrics(accumulatorUpdates)),
    +      (1L, 0, 0, createTaskMetrics(accumulatorUpdates))
    +    )))
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 2))
    +
    +    listener.onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate("", Seq(
    +      // (task id, stage id, stage attempt, metrics)
    +      (0L, 0, 0, createTaskMetrics(accumulatorUpdates)),
    +      (1L, 0, 0, createTaskMetrics(accumulatorUpdates.mapValues(_ * 2)))
    +    )))
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 3))
    +
    +    // Retrying a stage should reset the metrics
    +    listener.onStageSubmitted(SparkListenerStageSubmitted(createStageInfo(0, 1)))
    +
    +    listener.onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate("", Seq(
    +      // (task id, stage id, stage attempt, metrics)
    +      (0L, 0, 1, createTaskMetrics(accumulatorUpdates)),
    +      (1L, 0, 1, createTaskMetrics(accumulatorUpdates))
    +    )))
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 2))
    +
    +    // Ignore the task end for the first attempt
    +    listener.onTaskEnd(SparkListenerTaskEnd(
    +      stageId = 0,
    +      stageAttemptId = 0,
    +      taskType = "",
    +      reason = null,
    +      createTaskInfo(0, 0),
    +      createTaskMetrics(accumulatorUpdates.mapValues(_ * 100))))
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 2))
    +
    +    // Finish two tasks
    +    listener.onTaskEnd(SparkListenerTaskEnd(
    +      stageId = 0,
    +      stageAttemptId = 1,
    +      taskType = "",
    +      reason = null,
    +      createTaskInfo(0, 0),
    +      createTaskMetrics(accumulatorUpdates.mapValues(_ * 2))))
    +    listener.onTaskEnd(SparkListenerTaskEnd(
    +      stageId = 0,
    +      stageAttemptId = 1,
    +      taskType = "",
    +      reason = null,
    +      createTaskInfo(1, 0),
    +      createTaskMetrics(accumulatorUpdates.mapValues(_ * 3))))
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 5))
    +
    +    // Summit a new stage
    +    listener.onStageSubmitted(SparkListenerStageSubmitted(createStageInfo(1, 0)))
    +
    +    listener.onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate("", Seq(
    +      // (task id, stage id, stage attempt, metrics)
    +      (0L, 1, 0, createTaskMetrics(accumulatorUpdates)),
    +      (1L, 1, 0, createTaskMetrics(accumulatorUpdates))
    +    )))
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 7))
    +
    +    // Finish two tasks
    +    listener.onTaskEnd(SparkListenerTaskEnd(
    +      stageId = 1,
    +      stageAttemptId = 0,
    +      taskType = "",
    +      reason = null,
    +      createTaskInfo(0, 0),
    +      createTaskMetrics(accumulatorUpdates.mapValues(_ * 3))))
    +    listener.onTaskEnd(SparkListenerTaskEnd(
    +      stageId = 1,
    +      stageAttemptId = 0,
    +      taskType = "",
    +      reason = null,
    +      createTaskInfo(1, 0),
    +      createTaskMetrics(accumulatorUpdates.mapValues(_ * 3))))
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 11))
    +
    +    assert(executionUIData.runningJobs === Seq(0))
    +    assert(executionUIData.succeededJobs.isEmpty)
    +    assert(executionUIData.failedJobs.isEmpty)
    +
    +    listener.onJobEnd(SparkListenerJobEnd(
    +      jobId = 0,
    +      time = System.currentTimeMillis(),
    +      JobSucceeded
    +    ))
    +    listener.onExecutionEnd(executionId, System.currentTimeMillis())
    +
    +    assert(executionUIData.runningJobs.isEmpty)
    +    assert(executionUIData.succeededJobs === Seq(0))
    +    assert(executionUIData.failedJobs.isEmpty)
    +
    +    assert(listener.getExecutionMetrics(0) === accumulatorUpdates.mapValues(_ * 11))
    +  }
    +
    +  test("onExecutionEnd happens before onJobEnd(JobSucceeded)") {
    +    val listener = new SQLListener(TestSQLContext)
    +    val executionId = 0
    +    val df = createTestDataFrame
    +    listener.onExecutionStart(
    +      executionId,
    +      "test",
    +      "test",
    +      df.queryExecution.toString,
    +      SparkPlanGraph(df.queryExecution.executedPlan),
    +      System.currentTimeMillis())
    +    listener.onJobStart(SparkListenerJobStart(
    +      jobId = 0,
    +      time = System.currentTimeMillis(),
    +      stageInfos = Nil,
    +      createProperties(executionId)))
    +    listener.onExecutionEnd(executionId, System.currentTimeMillis())
    +    listener.onJobEnd(SparkListenerJobEnd(
    +      jobId = 0,
    +      time = System.currentTimeMillis(),
    +      JobSucceeded
    +    ))
    +
    +    val executionUIData = listener.executionIdToData(0)
    +    assert(executionUIData.runningJobs.isEmpty)
    +    assert(executionUIData.succeededJobs === Seq(0))
    +    assert(executionUIData.failedJobs.isEmpty)
    +  }
    +
    +  test("onExecutionEnd happens before multiple onJobEnd(JobSucceeded)s") {
    +    val listener = new SQLListener(TestSQLContext)
    +    val executionId = 0
    +    val df = createTestDataFrame
    +    listener.onExecutionStart(
    +      executionId,
    +      "test",
    +      "test",
    +      df.queryExecution.toString,
    +      SparkPlanGraph(df.queryExecution.executedPlan),
    +      System.currentTimeMillis())
    +    listener.onJobStart(SparkListenerJobStart(
    +      jobId = 0,
    +      time = System.currentTimeMillis(),
    +      stageInfos = Nil,
    +      createProperties(executionId)))
    +    listener.onJobEnd(SparkListenerJobEnd(
    +        jobId = 0,
    +        time = System.currentTimeMillis(),
    +        JobSucceeded
    +    ))
    +
    +    listener.onJobStart(SparkListenerJobStart(
    +      jobId = 1,
    +      time = System.currentTimeMillis(),
    +      stageInfos = Nil,
    +      createProperties(executionId)))
    +    listener.onExecutionEnd(executionId, System.currentTimeMillis())
    +    listener.onJobEnd(SparkListenerJobEnd(
    +      jobId = 1,
    +      time = System.currentTimeMillis(),
    +      JobSucceeded
    +    ))
    +
    +    val executionUIData = listener.executionIdToData(0)
    +    assert(executionUIData.runningJobs.isEmpty)
    +    assert(executionUIData.succeededJobs.sorted === Seq(0, 1))
    +    assert(executionUIData.failedJobs.isEmpty)
    +  }
    +
    +  test("onExecutionEnd happens before onJobEnd(JobFailed)") {
    +    val listener = new SQLListener(TestSQLContext)
    +    val executionId = 0
    +    val df = createTestDataFrame
    +    listener.onExecutionStart(
    +      executionId,
    +      "test",
    +      "test",
    +      df.queryExecution.toString,
    +      SparkPlanGraph(df.queryExecution.executedPlan),
    +      System.currentTimeMillis())
    +    listener.onJobStart(SparkListenerJobStart(
    +      jobId = 0,
    +      time = System.currentTimeMillis(),
    +      stageInfos = Seq.empty,
    +      createProperties(executionId)))
    +    listener.onExecutionEnd(executionId, System.currentTimeMillis())
    +    listener.onJobEnd(SparkListenerJobEnd(
    +      jobId = 0,
    +      time = System.currentTimeMillis(),
    +      JobFailed(new RuntimeException("Oops"))
    +    ))
    +
    +    val executionUIData = listener.executionIdToData(0)
    +    assert(executionUIData.runningJobs.isEmpty)
    +    assert(executionUIData.succeededJobs.isEmpty)
    +    assert(executionUIData.failedJobs === Seq(0))
    +  }
    +
    +  ignore("no memory leak") {
    --- End diff --
    
    This test floods the logs with stack traces.  Could we use [`quietly`](https://github.com/apache/spark/blob/d83c2f9f0b08d6d5d369d9fae04cdb15448e7f0d/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/package.scala#L27) to avoid making them hard to read?


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