Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/7753#discussion_r45927972
--- Diff:
core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala
---
@@ -122,6 +122,105 @@ class EventLoggingListenerSuite extends SparkFunSuite
with LocalSparkContext wit
"a fine:mind$dollar{bills}.1", None, Some("lz4")))
}
+ test("test event logger logging executor metrics") {
+ import org.apache.spark.scheduler.cluster._
+ import org.apache.spark.ui.memory._
+ val conf = EventLoggingListenerSuite.getLoggingConf(testDirPath)
+ val eventLogger = new EventLoggingListener("test-memListener", None,
testDirPath.toUri(), conf)
+ val execId = "exec-1"
+ val hostName = "host-1"
+
+ eventLogger.start()
+ eventLogger.onExecutorAdded(SparkListenerExecutorAdded(
+ 0L, execId, new ExecutorInfo(hostName, 1, Map.empty)))
+
+ // stage 1 and stage 2 submitted
+
eventLogger.onStageSubmitted(MemoryListenerSuite.createStageStartEvent(1))
+
eventLogger.onStageSubmitted(MemoryListenerSuite.createStageStartEvent(2))
+ val execMetrics1 = MemoryListenerSuite.createExecutorMetrics(hostName,
1L, 20, 10)
+
eventLogger.onExecutorMetricsUpdate(MemoryListenerSuite.createExecutorMetricsUpdateEvent(
+ execId, execMetrics1))
+ val execMetrics2 = MemoryListenerSuite.createExecutorMetrics(hostName,
2L, 30, 10)
+
eventLogger.onExecutorMetricsUpdate(MemoryListenerSuite.createExecutorMetricsUpdateEvent(
+ execId, execMetrics2))
+ // stage1 completed
+
eventLogger.onStageCompleted(MemoryListenerSuite.createStageEndEvent(1))
+ // stage3 submitted
+
eventLogger.onStageSubmitted(MemoryListenerSuite.createStageStartEvent(3))
+ val execMetrics3 = MemoryListenerSuite.createExecutorMetrics(hostName,
3L, 30, 30)
+
eventLogger.onExecutorMetricsUpdate(MemoryListenerSuite.createExecutorMetricsUpdateEvent(
+ execId, execMetrics3))
+ val execMetrics4 = MemoryListenerSuite.createExecutorMetrics(hostName,
4L, 20, 25)
+
eventLogger.onExecutorMetricsUpdate(MemoryListenerSuite.createExecutorMetricsUpdateEvent(
+ execId, execMetrics4))
+ // stage 2 completed
+
eventLogger.onStageCompleted(MemoryListenerSuite.createStageEndEvent(2))
+ val execMetrics5 = MemoryListenerSuite.createExecutorMetrics(hostName,
5L, 15, 15)
+
eventLogger.onExecutorMetricsUpdate(MemoryListenerSuite.createExecutorMetricsUpdateEvent(
+ execId, execMetrics5))
+ val execMetrics6 = MemoryListenerSuite.createExecutorMetrics(hostName,
6L, 25, 10)
+
eventLogger.onExecutorMetricsUpdate(MemoryListenerSuite.createExecutorMetricsUpdateEvent(
+ execId, execMetrics6))
+ // stage 3 completed
+
eventLogger.onStageCompleted(MemoryListenerSuite.createStageEndEvent(3))
+
+ eventLogger.onExecutorRemoved(SparkListenerExecutorRemoved(7L, execId,
""))
+
+ // Totally there are 15 logged events, including:
+ // 2 events of executor Added/Removed
+ // 6 events of stage Submitted/Completed
+ // 7 events of executorMetrics update (3 combined metrics and 4
original metrics)
+ assert(eventLogger.loggedEvents.size === 15)
+ eventLogger.stop()
+
+ val logData = EventLoggingListener.openEventLog(new
Path(eventLogger.logPath), fileSystem)
+ val lines = readLines(logData)
+ Utils.tryWithSafeFinally {
+ // totally there are 15 lines, including SparkListenerLogStart event
and 14 other events
+ assert(lines.size === 16)
+
+ // 4 executor metrics that is the latest metrics updated before
stage submit and complete
+ val jsonMetrics = JsonProtocol.sparkEventFromJson(parse(lines(5)))
--- End diff --
another idea: write an integration test, which pumps the parsed events back
into the `MemoryListener`, and make sure it has the right status for each
stage. I actually think that might be a better idea for gaining confidence.
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