[SPARK-12004] Preserve the RDD partitioner through RDD checkpointing #9983
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@zsxwing @andrewor14 Can you take a look at this. |
| @@ -55,25 +55,7 @@ private[spark] class ReliableRDDCheckpointData[T: ClassTag](@transient private v | |||
| * This is called immediately after the first action invoked on this RDD has completed. | |||
| */ | |||
| protected override def doCheckpoint(): CheckpointRDD[T] = { | |||
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All this code has been moved in the ReliableCheckpointRDD.createCheckpointedRDD
| /** | ||
| * Write a RDD partition's data to a checkpoint file. | ||
| */ | ||
| def writePartitionToCheckpointFile[T: ClassTag]( |
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LGTM. Just style and naming nits. |
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Test build #46724 has finished for PR 9983 at commit
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jenkins test this please |
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Test build #2132 has finished for PR 9983 at commit
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Test build #46931 has finished for PR 9983 at commit
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Test build #46935 has finished for PR 9983 at commit
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retest this please |
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Test build #46969 has finished for PR 9983 at commit
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m1.6 |
asfgit
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The solution is the save the RDD partitioner in a separate file in the RDD checkpoint directory. That is, `<checkpoint dir>/_partitioner`. In most cases, whether the RDD partitioner was recovered or not, does not affect the correctness, only reduces performance. So this solution makes a best-effort attempt to save and recover the partitioner. If either fails, the checkpointing is not affected. This makes this patch safe and backward compatible. Author: Tathagata Das <[email protected]> Closes #9983 from tdas/SPARK-12004. (cherry picked from commit 60b541e) Signed-off-by: Andrew Or <[email protected]>
asfgit
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Dec 7, 2015
…ner not present The reason is that TrackStateRDDs generated by trackStateByKey expect the previous batch's TrackStateRDDs to have a partitioner. However, when recovery from DStream checkpoints, the RDDs recovered from RDD checkpoints do not have a partitioner attached to it. This is because RDD checkpoints do not preserve the partitioner (SPARK-12004). While #9983 solves SPARK-12004 by preserving the partitioner through RDD checkpoints, there may be a non-zero chance that the saving and recovery fails. To be resilient, this PR repartitions the previous state RDD if the partitioner is not detected. Author: Tathagata Das <[email protected]> Closes #9988 from tdas/SPARK-11932.
asfgit
pushed a commit
that referenced
this pull request
Dec 7, 2015
…ner not present The reason is that TrackStateRDDs generated by trackStateByKey expect the previous batch's TrackStateRDDs to have a partitioner. However, when recovery from DStream checkpoints, the RDDs recovered from RDD checkpoints do not have a partitioner attached to it. This is because RDD checkpoints do not preserve the partitioner (SPARK-12004). While #9983 solves SPARK-12004 by preserving the partitioner through RDD checkpoints, there may be a non-zero chance that the saving and recovery fails. To be resilient, this PR repartitions the previous state RDD if the partitioner is not detected. Author: Tathagata Das <[email protected]> Closes #9988 from tdas/SPARK-11932. (cherry picked from commit 5d80d8c) Signed-off-by: Tathagata Das <[email protected]>
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The solution is the save the RDD partitioner in a separate file in the RDD checkpoint directory. That is,
<checkpoint dir>/_partitioner. In most cases, whether the RDD partitioner was recovered or not, does not affect the correctness, only reduces performance. So this solution makes a best-effort attempt to save and recover the partitioner. If either fails, the checkpointing is not affected. This makes this patch safe and backward compatible.