Repository: spark Updated Branches: refs/heads/master d6e1958a2 -> 091a000d2
[SPARK-23053][CORE] taskBinarySerialization and task partitions calculate in DagScheduler.submitMissingTasks should keep the same RDD checkpoint status ## What changes were proposed in this pull request? When we run concurrent jobs using the same rdd which is marked to do checkpoint. If one job has finished running the job, and start the process of RDD.doCheckpoint, while another job is submitted, then submitStage and submitMissingTasks will be called. In [submitMissingTasks](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala#L961), will serialize taskBinaryBytes and calculate task partitions which are both affected by the status of checkpoint, if the former is calculated before doCheckpoint finished, while the latter is calculated after doCheckpoint finished, when run task, rdd.compute will be called, for some rdds with particular partition type such as [UnionRDD](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala) who will do partition type cast, will get a ClassCastException because the part params is actually a CheckpointRDDPartition. This error occurs because rdd.doCheckpoint occurs in the same thread that called sc.runJob, while the task serialization occurs in the DAGSchedulers event loop. ## How was this patch tested? the exist uts and also add a test case in DAGScheduerSuite to show the exception case. Author: huangtengfei <huangtengfei@huangtengfeideMacBook-Pro.local> Closes #20244 from ivoson/branch-taskpart-mistype. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/091a000d Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/091a000d Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/091a000d Branch: refs/heads/master Commit: 091a000d27f324de8c5c527880854ecfcf5de9a4 Parents: d6e1958 Author: huangtengfei <huangtengfei@huangtengfeideMacBook-Pro.local> Authored: Tue Feb 13 09:59:21 2018 -0600 Committer: Imran Rashid <iras...@cloudera.com> Committed: Tue Feb 13 09:59:21 2018 -0600 ---------------------------------------------------------------------- .../apache/spark/scheduler/DAGScheduler.scala | 27 +++++++++++++------- 1 file changed, 18 insertions(+), 9 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/091a000d/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala ---------------------------------------------------------------------- diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index 199937b..8c46a84 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -39,7 +39,7 @@ import org.apache.spark.internal.Logging import org.apache.spark.internal.config import org.apache.spark.network.util.JavaUtils import org.apache.spark.partial.{ApproximateActionListener, ApproximateEvaluator, PartialResult} -import org.apache.spark.rdd.RDD +import org.apache.spark.rdd.{RDD, RDDCheckpointData} import org.apache.spark.rpc.RpcTimeout import org.apache.spark.storage._ import org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat @@ -1016,15 +1016,24 @@ class DAGScheduler( // might modify state of objects referenced in their closures. This is necessary in Hadoop // where the JobConf/Configuration object is not thread-safe. var taskBinary: Broadcast[Array[Byte]] = null + var partitions: Array[Partition] = null try { // For ShuffleMapTask, serialize and broadcast (rdd, shuffleDep). // For ResultTask, serialize and broadcast (rdd, func). - val taskBinaryBytes: Array[Byte] = stage match { - case stage: ShuffleMapStage => - JavaUtils.bufferToArray( - closureSerializer.serialize((stage.rdd, stage.shuffleDep): AnyRef)) - case stage: ResultStage => - JavaUtils.bufferToArray(closureSerializer.serialize((stage.rdd, stage.func): AnyRef)) + var taskBinaryBytes: Array[Byte] = null + // taskBinaryBytes and partitions are both effected by the checkpoint status. We need + // this synchronization in case another concurrent job is checkpointing this RDD, so we get a + // consistent view of both variables. + RDDCheckpointData.synchronized { + taskBinaryBytes = stage match { + case stage: ShuffleMapStage => + JavaUtils.bufferToArray( + closureSerializer.serialize((stage.rdd, stage.shuffleDep): AnyRef)) + case stage: ResultStage => + JavaUtils.bufferToArray(closureSerializer.serialize((stage.rdd, stage.func): AnyRef)) + } + + partitions = stage.rdd.partitions } taskBinary = sc.broadcast(taskBinaryBytes) @@ -1049,7 +1058,7 @@ class DAGScheduler( stage.pendingPartitions.clear() partitionsToCompute.map { id => val locs = taskIdToLocations(id) - val part = stage.rdd.partitions(id) + val part = partitions(id) stage.pendingPartitions += id new ShuffleMapTask(stage.id, stage.latestInfo.attemptNumber, taskBinary, part, locs, properties, serializedTaskMetrics, Option(jobId), @@ -1059,7 +1068,7 @@ class DAGScheduler( case stage: ResultStage => partitionsToCompute.map { id => val p: Int = stage.partitions(id) - val part = stage.rdd.partitions(p) + val part = partitions(p) val locs = taskIdToLocations(id) new ResultTask(stage.id, stage.latestInfo.attemptNumber, taskBinary, part, locs, id, properties, serializedTaskMetrics, --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
