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https://issues.apache.org/jira/browse/SPARK-17885?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16189403#comment-16189403
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Vishal John commented on SPARK-17885:
-------------------------------------
Hello all,
Our application also suffers from the same problem. Our application uses Spark
states(mapWithState) and checkpointed RDDs are getting created in the specified
checkpoint folder. But when the application is killed then the directory
containing the checkpointed RDDs is cleared.
When I launch the application again, it fails because it cannot find the
checkpoint directory.
This is the error 'java.lang.IllegalArgumentException: requirement failed:
Checkpoint directory does not exist:
hdfs://nameservice1/user/my-user/checkpoints/my-application/77b1dd15-f904-4e80-a5ed-5018224b4df0/rdd-6833'
The applications uses Spark 2.0.2 and it's deployed on Cloudera YARN
(2.5.0-cdh5.2.0)
Because of this error we are unable to use the checkpointed RDDs and Spark
states. Can this issue be taken up as priority ?
Please let me know if you require any additional information.
[~tdas][~srowen]
thanks a lot,
Vishal
> Spark Streaming deletes checkpointed RDD then tries to load it after restart
> ----------------------------------------------------------------------------
>
> Key: SPARK-17885
> URL: https://issues.apache.org/jira/browse/SPARK-17885
> Project: Spark
> Issue Type: Bug
> Components: DStreams
> Affects Versions: 1.5.1
> Reporter: Cosmin Ciobanu
>
> The issue is that the Spark driver checkpoints an RDD, deletes it, the job
> restarts, and the new driver tries to load the deleted checkpoint RDD.
> The application is run in YARN, which attempts to restart the application a
> number of times (100 in our case), all of which fail due to missing the
> deleted RDD.
> Here is a Splunk log which shows the inconsistency in checkpoint behaviour:
> *2016-10-09 02:48:43,533* [streaming-job-executor-0] INFO
> org.apache.spark.rdd.ReliableRDDCheckpointData - Done checkpointing RDD 73847
> to
> hdfs://proc-job/checkpoint/cadf8dcf-ebc2-4366-a2e1-0939976c6ce1/*rdd-73847*,
> new parent is RDD 73872
> host = ip-10-1-1-13.ec2.internal
> *2016-10-09 02:53:14,696* [JobGenerator] INFO
> org.apache.spark.streaming.dstream.DStreamCheckpointData - Deleted checkpoint
> file
> 'hdfs://proc-job/checkpoint/cadf8dcf-ebc2-4366-a2e1-0939976c6ce1/*rdd-73847*'
> for time 1475981310000 ms
> host = ip-10-1-1-13.ec2.internal
> *Job restarts here, notice driver host change from ip-10-1-1-13.ec2.internal
> to ip-10-1-1-25.ec2.internal.*
> *2016-10-09 02:53:30,175* [Driver] INFO
> org.apache.spark.streaming.dstream.DStreamCheckpointData - Restoring
> checkpointed RDD for time 1475981310000 ms from file
> 'hdfs://proc-job/checkpoint/cadf8dcf-ebc2-4366-a2e1-0939976c6ce1/*rdd-73847*'
> host = ip-10-1-1-25.ec2.internal
> *2016-10-09 02:53:30,491* [Driver] ERROR
> org.apache.spark.deploy.yarn.ApplicationMaster - User class threw exception:
> java.lang.IllegalArgumentException: requirement failed: Checkpoint directory
> does not exist:
> hdfs://proc-job/checkpoint/cadf8dcf-ebc2-4366-a2e1-0939976c6ce1/*rdd-73847*
> java.lang.IllegalArgumentException: requirement failed: Checkpoint directory
> does not exist:
> hdfs://proc-job/checkpoint/cadf8dcf-ebc2-4366-a2e1-0939976c6ce1/*rdd-73847*
> host = ip-10-1-1-25.ec2.internal
> Spark streaming is configured with a microbatch interval of 30 seconds,
> checkpoint interval of 120 seconds, and cleaner.ttl of 28800 (8 hours), but
> as far as I can tell, this TTL only affects metadata cleanup interval. RDDs
> seem to be deleted every 4-5 minutes after being checkpointed.
> Running on top of Spark 1.5.1.
> There are at least two possible issues here:
> - In case of a driver restart the new driver tries to load checkpointed RDDs
> which the previous driver had just deleted;
> - Spark loads stale checkpointed data - the logs show that the deleted RDD
> was initially checkpointed 4 minutes and 31 seconds before deletion, and 4
> minutes and 47 seconds before the new driver tries to load it. Given the fact
> the checkpointing interval is 120 seconds, it makes no sense to load data
> older than that.
> P.S. Looking at the source code with the event loop that handles checkpoint
> updates and cleanup, nothing seems to have changed in more recent versions of
> Spark, so the bug is likely present in 2.0.1 as well.
> P.P.S. The issue is difficult to reproduce - it only occurs once in every 10
> or so restarts, and only in clusters with high-load.
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