[do not review][wip] Trying to reduce the flakyness of BlockManagerDecommissionIntegrationSuite

core/src/test/resources/log4j.properties

@@ -17,7 +17,7 @@
 
 # Set everything to be logged to the file target/unit-tests.log
 test.appender=file
-log4j.rootCategory=INFO, ${test.appender}
+log4j.rootCategory=DEBUG, ${test.appender}
 log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file.append=true
 log4j.appender.file.file=target/unit-tests.log

core/src/test/scala/org/apache/spark/storage/BlockManagerDecommissionIntegrationSuite.scala

@@ -57,6 +57,9 @@ class BlockManagerDecommissionIntegrationSuite extends SparkFunSuite with LocalS
       .set(config.STORAGE_DECOMMISSION_ENABLED, true)
       .set(config.STORAGE_DECOMMISSION_RDD_BLOCKS_ENABLED, persist)
       .set(config.STORAGE_DECOMMISSION_SHUFFLE_BLOCKS_ENABLED, shuffle)
+      .set(config.EXECUTOR_CORES.key, "1")
+      .set(config.CPUS_PER_TASK.key, "1")
+      .set(config.EXECUTOR_MEMORY.key, "1024m")
       // Just replicate blocks as fast as we can during testing, there isn't another
       // workload we need to worry about.
       .set(config.STORAGE_DECOMMISSION_REPLICATION_REATTEMPT_INTERVAL, 1L)
@@ -90,6 +93,7 @@ class BlockManagerDecommissionIntegrationSuite extends SparkFunSuite with LocalS
     val taskStartSem = new Semaphore(0)
     val broadcastSem = new Semaphore(0)
     val executorRemovedSem = new Semaphore(0)
+    val taskStartEvents = ArrayBuffer.empty[SparkListenerTaskStart]
     val taskEndEvents = ArrayBuffer.empty[SparkListenerTaskEnd]
     val blocksUpdated = ArrayBuffer.empty[SparkListenerBlockUpdated]
     sc.addSparkListener(new SparkListener {
@@ -99,6 +103,7 @@ class BlockManagerDecommissionIntegrationSuite extends SparkFunSuite with LocalS
       }
 
       override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = {
+        taskStartEvents.append(taskStart)
         taskStartSem.release()
       }
 
@@ -145,8 +150,10 @@ class BlockManagerDecommissionIntegrationSuite extends SparkFunSuite with LocalS
     assert(execs.size == numExecs, s"Expected ${numExecs} executors but found ${execs.size}")
 
     val execToDecommission = execs.head
-    logDebug(s"Decommissioning executor ${execToDecommission}")
-    sched.decommissionExecutor(execToDecommission, ExecutorDecommissionInfo("", false))
+    val withTasks = taskStartEvents.map(_.taskInfo.executorId).toSet
+    val msg = s"Decommissioning executor ${execToDecommission} of $execs $withTasks"
+    logInfo(msg)
+    sched.decommissionExecutor(execToDecommission, ExecutorDecommissionInfo(msg, false))
 
     // Wait for job to finish.
     val asyncCountResult = ThreadUtils.awaitResult(asyncCount, 15.seconds)
@@ -178,7 +185,7 @@ class BlockManagerDecommissionIntegrationSuite extends SparkFunSuite with LocalS
         val blocksToManagers = blockLocs.groupBy(_._1).mapValues(_.size)
         assert(!blocksToManagers.filter(_._2 > 1).isEmpty,
           s"We should have a block that has been on multiple BMs in rdds:\n ${rddUpdates} from:\n" +
-          s"${blocksUpdated}\n but instead we got:\n ${blocksToManagers}")
+          s"${blocksUpdated}\n but instead we got:\n ${blocksToManagers}\n$msg")
       }
       // If we're migrating shuffles we look for any shuffle block updates
       // as there is no block update on the initial shuffle block write.
@@ -191,11 +198,13 @@ class BlockManagerDecommissionIntegrationSuite extends SparkFunSuite with LocalS
           val blockId = update.blockUpdatedInfo.blockId
           blockId.isInstanceOf[ShuffleIndexBlockId]
         }.size
-        assert(numDataLocs === 1, s"Expect shuffle data block updates in ${blocksUpdated}")
-        assert(numIndexLocs === 1, s"Expect shuffle index block updates in ${blocksUpdated}")
+        assert(numDataLocs === 1, s"Expect shuffle data block updates in ${blocksUpdated}\n$msg")
+        assert(numIndexLocs === 1, s"Expect shuffle index block updates in ${blocksUpdated}\n$msg")
       }
     }
 
+    logInfo(s"Blocks updated is $blocksUpdated")
+
     // Since the RDD is cached or shuffled so further usage of same RDD should use the
     // cached data. Original RDD partitions should not be recomputed i.e. accum
     // should have same value like before