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https://issues.apache.org/jira/browse/SPARK-2292?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14046946#comment-14046946
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Patrick Wendell commented on SPARK-2292:
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[~aash] With your example code I was able to narrow this down (slightly). I
think there is something subtle going on here at the byte code level.
Your example links against the spark-1.0.0 binaries in Maven.
1. If I ran your example on a download Spark 1.0.0 cluster (I just went and
downloaded the Spark binaries) it worked fine.
2. If I ran your example on a local Spark cluster that I compiled myself with
SBT, even with the 1.0.0 tag, it didn't work.
I'm wondering if this is something similar to SPARK-2075.
In general, it would be good if people used spark-submit binary that is
compiled at the same time as their cluster to submit jobs. Otherwise, there can
be issues where a closure is created using an internal class name that is
different than that on the cluster.
> NullPointerException in JavaPairRDD.mapToPair
> ---------------------------------------------
>
> Key: SPARK-2292
> URL: https://issues.apache.org/jira/browse/SPARK-2292
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.0.0
> Environment: Spark 1.0.0, Standalone with the master & single slave
> running on Ubuntu on a laptop. 4G mem and 8 cores were available to the
> executor .
> Reporter: Bharath Ravi Kumar
> Attachments: SPARK-2292-aash-repro.tar.gz
>
>
> Correction: Invoking JavaPairRDD.mapToPair results in an NPE:
> {noformat}
> 14/06/26 21:05:35 WARN scheduler.TaskSetManager: Loss was due to
> java.lang.NullPointerException
> java.lang.NullPointerException
> at
> org.apache.spark.api.java.JavaPairRDD$$anonfun$pairFunToScalaFun$1.apply(JavaPairRDD.scala:750)
> at
> org.apache.spark.api.java.JavaPairRDD$$anonfun$pairFunToScalaFun$1.apply(JavaPairRDD.scala:750)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at org.apache.spark.Aggregator.combineValuesByKey(Aggregator.scala:59)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$1.apply(PairRDDFunctions.scala:96)
> at
> org.apache.spark.rdd.PairRDDFunctions$$anonfun$1.apply(PairRDDFunctions.scala:95)
> at org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:582)
> at org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:582)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:158)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
> at org.apache.spark.scheduler.Task.run(Task.scala:51)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603)
> at java.lang.Thread.run(Thread.java:722)
> {noformat}
> This occurs only after migrating to the 1.0.0 API. The details of the code
> the data file used to test are included in this gist :
> https://gist.github.com/reachbach/d8977c8eb5f71f889301
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