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https://issues.apache.org/jira/browse/HUDI-1839?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Nishith Agarwal updated HUDI-1839:
----------------------------------
Fix Version/s: 0.9.0
> FSUtils getAllPartitions broken by NotSerializableException:
> org.apache.hadoop.fs.Path
> --------------------------------------------------------------------------------------
>
> Key: HUDI-1839
> URL: https://issues.apache.org/jira/browse/HUDI-1839
> Project: Apache Hudi
> Issue Type: Bug
> Reporter: satish
> Priority: Blocker
> Fix For: 0.9.0
>
>
> FSUtils getAllPartitionPaths is expected to work if metadata table is enabled
> or not. It can also be called inside spark context. But looks like we are
> trying to improve parallelism and causing NotSerializableExceptions. There
> are multiple callers using it within spark context (clustering/cleaner).
> See stack trace below
> 21/04/20 17:28:44 INFO yarn.ApplicationMaster: Unregistering
> ApplicationMaster with FAILED (diag message: User class threw exception:
> org.apache.hudi.exception.HoodieException: Error fetching partition paths
> from metadata table
> at org.apache.hudi.common.fs.FSUtils.getAllPartitionPaths(FSUtils.java:321)
> at
> org.apache.hudi.table.action.cluster.strategy.PartitionAwareClusteringPlanStrategy.generateClusteringPlan(PartitionAwareClusteringPlanStrategy.java:67)
> at
> org.apache.hudi.table.action.cluster.SparkClusteringPlanActionExecutor.createClusteringPlan(SparkClusteringPlanActionExecutor.java:71)
> at
> org.apache.hudi.table.action.cluster.BaseClusteringPlanActionExecutor.execute(BaseClusteringPlanActionExecutor.java:56)
> at
> org.apache.hudi.table.HoodieSparkCopyOnWriteTable.scheduleClustering(HoodieSparkCopyOnWriteTable.java:160)
> at
> org.apache.hudi.client.AbstractHoodieWriteClient.scheduleClusteringAtInstant(AbstractHoodieWriteClient.java:873)
> at
> org.apache.hudi.client.AbstractHoodieWriteClient.scheduleClustering(AbstractHoodieWriteClient.java:861)
> at
> com.uber.data.efficiency.hudi.HudiRewriter.rewriteDataUsingHudi(HudiRewriter.java:111)
> at com.uber.data.efficiency.hudi.HudiRewriter.main(HudiRewriter.java:50)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:690)
> Caused by: org.apache.spark.SparkException: Job aborted due to stage
> failure: Failed to serialize task 53, not attempting to retry it. Exception
> during serialization: java.io.NotSerializableException:
> org.apache.hadoop.fs.Path
> Serialization stack:
> - object not serializable (class: org.apache.hadoop.fs.Path, value:
> hdfs://...)
> - element of array (index: 0)
> - array (class [Ljava.lang.Object;, size 1)
> - field (class: scala.collection.mutable.WrappedArray$ofRef, name: array,
> type: class [Ljava.lang.Object;)
> - object (class scala.collection.mutable.WrappedArray$ofRef,
> WrappedArray(hdfs://...))
> - writeObject data (class: org.apache.spark.rdd.ParallelCollectionPartition)
> - object (class org.apache.spark.rdd.ParallelCollectionPartition,
> org.apache.spark.rdd.ParallelCollectionPartition@735)
> - field (class: org.apache.spark.scheduler.ResultTask, name: partition,
> type: interface org.apache.spark.Partition)
> - object (class org.apache.spark.scheduler.ResultTask, ResultTask(1, 0))
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1904)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1892)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1891)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1891)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:935)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:935)
> at scala.Option.foreach(Option.scala:257)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:935)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2125)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2074)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2063)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:746)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2070)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2091)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2110)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2135)
> at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:968)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
> at org.apache.spark.rdd.RDD.collect(RDD.scala:967)
> at org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala:361)
> at
> org.apache.spark.api.java.AbstractJavaRDDLike.collect(JavaRDDLike.scala:45)
> at
> org.apache.hudi.client.common.HoodieSparkEngineContext.map(HoodieSparkEngineContext.java:79)
> at
> org.apache.hudi.metadata.FileSystemBackedTableMetadata.getAllPartitionPaths(FileSystemBackedTableMetadata.java:79)
> at org.apache.hudi.common.fs.FSUtils.getAllPartitionPaths(FSUtils.java:319)
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