[jira] [Commented] (SPARK-11798) Datanucleus jars is missing under lib_managed/jars
[
https://issues.apache.org/jira/browse/SPARK-11798?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15924420#comment-15924420
]
Luca Menichetti commented on SPARK-11798:
-
I have exactly the same issue, I had to include all datanucleus-* jar manually
with the --jars command when submitting job in cluster mode. With --master
yarn-client everything is working, so apparently these jars are not
automatically imported.
Spark is compiled with Hive profile and version is 1.6.2.
The logs I see are the following:
WARN metastore.HiveMetaStore: Retrying creating default database after error:
Class org.datanucleus.api.jdo.JDOPersistenceManagerFactory was not found.
javax.jdo.JDOFatalUserException: Class
org.datanucleus.api.jdo.JDOPersistenceManagerFactory was not found.
> Datanucleus jars is missing under lib_managed/jars
> --
>
> Key: SPARK-11798
> URL: https://issues.apache.org/jira/browse/SPARK-11798
> Project: Spark
> Issue Type: Bug
> Components: Build, SQL
>Reporter: Jeff Zhang
>
> I notice the comments in https://github.com/apache/spark/pull/9575 said that
> Datanucleus related jars will still be copied to lib_managed/jars. But I
> don't see any jars under lib_managed/jars. The weird thing is that I see the
> jars on another machine, but could not see jars on my laptop even after I
> delete the whole spark project and start from scratch. Does it related with
> environments ? I try to add the following code in SparkBuild.scala to track
> the issue, it shows that the jars is empty.
> {code}
> deployDatanucleusJars := {
> val jars: Seq[File] = (fullClasspath in assembly).value.map(_.data)
> .filter(_.getPath.contains("org.datanucleus"))
> // this is what I added
> println("*")
> println("fullClasspath:"+fullClasspath)
> println("assembly:"+assembly)
> println("jars:"+jars.map(_.getAbsolutePath()).mkString(","))
> //
> {code}
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[jira] [Comment Edited] (SPARK-4105) FAILED_TO_UNCOMPRESS(5) errors when fetching shuffle data with sort-based shuffle
[
https://issues.apache.org/jira/browse/SPARK-4105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15535884#comment-15535884
]
Luca Menichetti edited comment on SPARK-4105 at 9/30/16 2:25 PM:
-
I have exactly the same problem. It occurs when I process more than one TB of
data.
Splitting the computation in halves it works perfectly, but I need to process
the whole thing together.
{noformat}
java.io.IOException: failed to read chunk
at
org.xerial.snappy.SnappyInputStream.hasNextChunk(SnappyInputStream.java:347)
at
org.xerial.snappy.SnappyInputStream.rawRead(SnappyInputStream.java:158)
at org.xerial.snappy.SnappyInputStream.read(SnappyInputStream.java:142)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:275)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at java.io.DataInputStream.read(DataInputStream.java:149)
at org.spark-project.guava.io.ByteStreams.read(ByteStreams.java:899)
at
org.spark-project.guava.io.ByteStreams.readFully(ByteStreams.java:733)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:119)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:102)
at scala.collection.Iterator$$anon$13.next(Iterator.scala:372)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:30)
at
org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:512)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.(TungstenAggregationIterator.scala:686)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:95)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:86)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
{noformat}
as a consequence, since I am using SparkSQL, the job will fail, reporting
{noformat}
16/09/30 14:40:51 ERROR LiveListenerBus: Listener SQLListener threw an exception
java.lang.NullPointerException
at
org.apache.spark.sql.execution.ui.SQLListener.onTaskEnd(SQLListener.scala:167)
at
org.apache.spark.scheduler.SparkListenerBus$class.onPostEvent(SparkListenerBus.scala:42)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.util.ListenerBus$class.postToAll(ListenerBus.scala:55)
at
org.apache.spark.util.AsynchronousListenerBus.postToAll(AsynchronousListenerBus.scala:37)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(AsynchronousListenerBus.scala:80)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(AsynchronousListenerBus.scala:65)
at
[jira] [Comment Edited] (SPARK-4105) FAILED_TO_UNCOMPRESS(5) errors when fetching shuffle data with sort-based shuffle
[
https://issues.apache.org/jira/browse/SPARK-4105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15535884#comment-15535884
]
Luca Menichetti edited comment on SPARK-4105 at 9/30/16 2:04 PM:
-
I have exactly the same problem. It occurs when I process more than one TB of
data.
Splitting the computation in halves it works perfectly, but I need to process
the whole thing together.
{noformat}
java.io.IOException: failed to read chunk
at
org.xerial.snappy.SnappyInputStream.hasNextChunk(SnappyInputStream.java:347)
at
org.xerial.snappy.SnappyInputStream.rawRead(SnappyInputStream.java:158)
at org.xerial.snappy.SnappyInputStream.read(SnappyInputStream.java:142)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:275)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at java.io.DataInputStream.read(DataInputStream.java:149)
at org.spark-project.guava.io.ByteStreams.read(ByteStreams.java:899)
at
org.spark-project.guava.io.ByteStreams.readFully(ByteStreams.java:733)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:119)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:102)
at scala.collection.Iterator$$anon$13.next(Iterator.scala:372)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:30)
at
org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:512)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.(TungstenAggregationIterator.scala:686)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:95)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:86)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
{noformat}
as a consequence, since I am using SparkSQL, the job will fail, reporting
{noformat}
16/09/30 14:40:51 ERROR LiveListenerBus: Listener SQLListener threw an exception
java.lang.NullPointerException
at
org.apache.spark.sql.execution.ui.SQLListener.onTaskEnd(SQLListener.scala:167)
at
org.apache.spark.scheduler.SparkListenerBus$class.onPostEvent(SparkListenerBus.scala:42)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.util.ListenerBus$class.postToAll(ListenerBus.scala:55)
at
org.apache.spark.util.AsynchronousListenerBus.postToAll(AsynchronousListenerBus.scala:37)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(AsynchronousListenerBus.scala:80)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(AsynchronousListenerBus.scala:65)
at
[jira] [Comment Edited] (SPARK-4105) FAILED_TO_UNCOMPRESS(5) errors when fetching shuffle data with sort-based shuffle
[
https://issues.apache.org/jira/browse/SPARK-4105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15535884#comment-15535884
]
Luca Menichetti edited comment on SPARK-4105 at 9/30/16 1:54 PM:
-
I have exactly the same problem. It occurs when I process more than one TB of
data.
Splitting the computation in halves it works perfectly, but I need to process
the whole thing together.
{noformat}
java.io.IOException: failed to read chunk
at
org.xerial.snappy.SnappyInputStream.hasNextChunk(SnappyInputStream.java:347)
at
org.xerial.snappy.SnappyInputStream.rawRead(SnappyInputStream.java:158)
at org.xerial.snappy.SnappyInputStream.read(SnappyInputStream.java:142)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:275)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at java.io.DataInputStream.read(DataInputStream.java:149)
at org.spark-project.guava.io.ByteStreams.read(ByteStreams.java:899)
at
org.spark-project.guava.io.ByteStreams.readFully(ByteStreams.java:733)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:119)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:102)
at scala.collection.Iterator$$anon$13.next(Iterator.scala:372)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:30)
at
org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:512)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.(TungstenAggregationIterator.scala:686)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:95)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:86)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
{noformat}
as a consequence, since I am using SparkSQL, the job will fail, reporting
{noformat}
16/09/30 14:40:51 ERROR LiveListenerBus: Listener SQLListener threw an exception
java.lang.NullPointerException
at
org.apache.spark.sql.execution.ui.SQLListener.onTaskEnd(SQLListener.scala:167)
at
org.apache.spark.scheduler.SparkListenerBus$class.onPostEvent(SparkListenerBus.scala:42)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.util.ListenerBus$class.postToAll(ListenerBus.scala:55)
at
org.apache.spark.util.AsynchronousListenerBus.postToAll(AsynchronousListenerBus.scala:37)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(AsynchronousListenerBus.scala:80)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(AsynchronousListenerBus.scala:65)
at
[jira] [Comment Edited] (SPARK-4105) FAILED_TO_UNCOMPRESS(5) errors when fetching shuffle data with sort-based shuffle
[
https://issues.apache.org/jira/browse/SPARK-4105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15535884#comment-15535884
]
Luca Menichetti edited comment on SPARK-4105 at 9/30/16 12:43 PM:
--
I have exactly the same problem. It occurs when I process more than one TB of
data.
Splitting the computation in halves it works perfectly, but I need to process
the whole thing together.
{noformat}
java.io.IOException: failed to read chunk
at
org.xerial.snappy.SnappyInputStream.hasNextChunk(SnappyInputStream.java:347)
at
org.xerial.snappy.SnappyInputStream.rawRead(SnappyInputStream.java:158)
at org.xerial.snappy.SnappyInputStream.read(SnappyInputStream.java:142)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:275)
at java.io.BufferedInputStream.read(BufferedInputStream.java:334)
at java.io.DataInputStream.read(DataInputStream.java:149)
at org.spark-project.guava.io.ByteStreams.read(ByteStreams.java:899)
at
org.spark-project.guava.io.ByteStreams.readFully(ByteStreams.java:733)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:119)
at
org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:102)
at scala.collection.Iterator$$anon$13.next(Iterator.scala:372)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:30)
at
org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:512)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.(TungstenAggregationIterator.scala:686)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:95)
at
org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:86)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
{noformat}
as a consequence, since I am using SparkSQL, the job will fail, reporting
{noformat}
16/09/30 14:40:51 ERROR LiveListenerBus: Listener SQLListener threw an exception
java.lang.NullPointerException
at
org.apache.spark.sql.execution.ui.SQLListener.onTaskEnd(SQLListener.scala:167)
at
org.apache.spark.scheduler.SparkListenerBus$class.onPostEvent(SparkListenerBus.scala:42)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31)
at
org.apache.spark.util.ListenerBus$class.postToAll(ListenerBus.scala:55)
at
org.apache.spark.util.AsynchronousListenerBus.postToAll(AsynchronousListenerBus.scala:37)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(AsynchronousListenerBus.scala:80)
at
org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(AsynchronousListenerBus.scala:65)
at
[jira] [Commented] (SPARK-4105) FAILED_TO_UNCOMPRESS(5) errors when fetching shuffle data with sort-based shuffle
[ https://issues.apache.org/jira/browse/SPARK-4105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15535884#comment-15535884 ] Luca Menichetti commented on SPARK-4105: I have exactly the same problem. It occurs when I process more than one TB of data. Splitting the computation in halves it will work perfectly, but I need to process the whole thing together. ``` java.io.IOException: failed to read chunk at org.xerial.snappy.SnappyInputStream.hasNextChunk(SnappyInputStream.java:347) at org.xerial.snappy.SnappyInputStream.rawRead(SnappyInputStream.java:158) at org.xerial.snappy.SnappyInputStream.read(SnappyInputStream.java:142) at java.io.BufferedInputStream.fill(BufferedInputStream.java:235) at java.io.BufferedInputStream.read1(BufferedInputStream.java:275) at java.io.BufferedInputStream.read(BufferedInputStream.java:334) at java.io.DataInputStream.read(DataInputStream.java:149) at org.spark-project.guava.io.ByteStreams.read(ByteStreams.java:899) at org.spark-project.guava.io.ByteStreams.readFully(ByteStreams.java:733) at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:119) at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$3$$anon$1.next(UnsafeRowSerializer.scala:102) at scala.collection.Iterator$$anon$13.next(Iterator.scala:372) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:30) at org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.processInputs(TungstenAggregationIterator.scala:512) at org.apache.spark.sql.execution.aggregate.TungstenAggregationIterator.(TungstenAggregationIterator.scala:686) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:95) at org.apache.spark.sql.execution.aggregate.TungstenAggregate$$anonfun$doExecute$1$$anonfun$2.apply(TungstenAggregate.scala:86) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710) at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.run(Task.scala:89) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) ``` as a consequence, since I am using SparkSQL, the job will fail, reporting ``` 16/09/30 14:40:51 ERROR LiveListenerBus: Listener SQLListener threw an exception java.lang.NullPointerException at org.apache.spark.sql.execution.ui.SQLListener.onTaskEnd(SQLListener.scala:167) at org.apache.spark.scheduler.SparkListenerBus$class.onPostEvent(SparkListenerBus.scala:42) at org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31) at org.apache.spark.scheduler.LiveListenerBus.onPostEvent(LiveListenerBus.scala:31) at org.apache.spark.util.ListenerBus$class.postToAll(ListenerBus.scala:55) at org.apache.spark.util.AsynchronousListenerBus.postToAll(AsynchronousListenerBus.scala:37) at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(AsynchronousListenerBus.scala:80) at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(AsynchronousListenerBus.scala:65) at org.apache.spark.util.AsynchronousListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(AsynchronousListenerBus.scala:65) at
