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https://issues.apache.org/jira/browse/SPARK-22184?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sergey Zhemzhitsky reopened SPARK-22184:
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> GraphX fails in case of insufficient memory and checkpoints enabled
> -------------------------------------------------------------------
>
> Key: SPARK-22184
> URL: https://issues.apache.org/jira/browse/SPARK-22184
> Project: Spark
> Issue Type: Bug
> Components: GraphX
> Affects Versions: 2.2.0
> Environment: spark 2.2.0
> scala 2.11
> Reporter: Sergey Zhemzhitsky
>
> GraphX fails with FileNotFoundException in case of insufficient memory when
> checkpoints are enabled.
> Here is the stacktrace
> {code}
> Job aborted due to stage failure: Task creation failed:
> java.io.FileNotFoundException: File
> file:/tmp/spark-90119695-a126-47b5-b047-d656fee10c17/9b16e2a9-6c80-45eb-8736-bbb6eb840146/rdd-28/part-00000
> does not exist
> java.io.FileNotFoundException: File
> file:/tmp/spark-90119695-a126-47b5-b047-d656fee10c17/9b16e2a9-6c80-45eb-8736-bbb6eb840146/rdd-28/part-00000
> does not exist
> at
> org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLocalFileSystem.java:539)
> at
> org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:752)
> at
> org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:529)
> at
> org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:409)
> at
> org.apache.spark.rdd.ReliableCheckpointRDD.getPreferredLocations(ReliableCheckpointRDD.scala:89)
> at
> org.apache.spark.rdd.RDD$$anonfun$preferredLocations$1.apply(RDD.scala:274)
> at
> org.apache.spark.rdd.RDD$$anonfun$preferredLocations$1.apply(RDD.scala:274)
> at scala.Option.map(Option.scala:146)
> at org.apache.spark.rdd.RDD.preferredLocations(RDD.scala:274)
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$getPreferredLocsInternal(DAGScheduler.scala:1697)
> ...
> {code}
> As GraphX uses cached RDDs intensively, the issue is only reproducible when
> previously cached and checkpointed Vertex and Edge RDDs are evicted from
> memory and forced to be read from disk.
> For testing purposes the following parameters may be set to emulate low
> memory environment
> {code}
> val sparkConf = new SparkConf()
> .set("spark.graphx.pregel.checkpointInterval", "2")
> // set testing memory to evict cached RDDs from it and force
> // reading checkpointed RDDs from disk
> .set("spark.testing.reservedMemory", "128")
> .set("spark.testing.memory", "256")
> {code}
> This issue also includes SPARK-22150 and cannot be fixed until SPARK-22150 is
> fixed too.
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