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https://issues.apache.org/jira/browse/SPARK-15822?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15325417#comment-15325417
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Davies Liu commented on SPARK-15822:
------------------------------------
The latest stacktrace is different than previous one, it seems that the
UnsafeRow in aggregate hash map is corrupt.
How large is your dataset? It will be great if we can reproduce it (currently
no luck).
> segmentation violation in o.a.s.unsafe.types.UTF8String
> --------------------------------------------------------
>
> Key: SPARK-15822
> URL: https://issues.apache.org/jira/browse/SPARK-15822
> Project: Spark
> Issue Type: Bug
> Affects Versions: 2.0.0
> Environment: linux amd64
> openjdk version "1.8.0_91"
> OpenJDK Runtime Environment (build 1.8.0_91-b14)
> OpenJDK 64-Bit Server VM (build 25.91-b14, mixed mode)
> Reporter: Pete Robbins
> Assignee: Herman van Hovell
> Priority: Blocker
>
> Executors fail with segmentation violation while running application with
> spark.memory.offHeap.enabled true
> spark.memory.offHeap.size 512m
> Also now reproduced with
> spark.memory.offHeap.enabled false
> {noformat}
> #
> # A fatal error has been detected by the Java Runtime Environment:
> #
> # SIGSEGV (0xb) at pc=0x00007f4559b4d4bd, pid=14182, tid=139935319750400
> #
> # JRE version: OpenJDK Runtime Environment (8.0_91-b14) (build 1.8.0_91-b14)
> # Java VM: OpenJDK 64-Bit Server VM (25.91-b14 mixed mode linux-amd64
> compressed oops)
> # Problematic frame:
> # J 4816 C2
> org.apache.spark.unsafe.types.UTF8String.compareTo(Lorg/apache/spark/unsafe/types/UTF8String;)I
> (64 bytes) @ 0x00007f4559b4d4bd [0x00007f4559b4d460+0x5d]
> {noformat}
> We initially saw this on IBM java on PowerPC box but is recreatable on linux
> with OpenJDK. On linux with IBM Java 8 we see a null pointer exception at the
> same code point:
> {noformat}
> 16/06/08 11:14:58 ERROR Executor: Exception in task 1.0 in stage 5.0 (TID 48)
> java.lang.NullPointerException
> at
> org.apache.spark.unsafe.types.UTF8String.compareTo(UTF8String.java:831)
> at org.apache.spark.unsafe.types.UTF8String.compare(UTF8String.java:844)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.findNextInnerJoinRows$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$doExecute$2$$anon$2.hasNext(WholeStageCodegenExec.scala:377)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at
> scala.collection.convert.Wrappers$IteratorWrapper.hasNext(Wrappers.scala:30)
> at org.spark_project.guava.collect.Ordering.leastOf(Ordering.java:664)
> at org.apache.spark.util.collection.Utils$.takeOrdered(Utils.scala:37)
> at
> org.apache.spark.rdd.RDD$$anonfun$takeOrdered$1$$anonfun$30.apply(RDD.scala:1365)
> at
> org.apache.spark.rdd.RDD$$anonfun$takeOrdered$1$$anonfun$30.apply(RDD.scala:1362)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:757)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:757)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1153)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
> at java.lang.Thread.run(Thread.java:785)
> {noformat}
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