Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/7774#discussion_r47942980
--- 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 --
Sure. Will fix it.
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