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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/02/08 08:05:39 UTC
[jira] [Commented] (SPARK-13230) HashMap.merged not working
properly with Spark
[ https://issues.apache.org/jira/browse/SPARK-13230?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15136654#comment-15136654 ]
Sean Owen commented on SPARK-13230:
-----------------------------------
That's a weird one. This is a little simpler as
{code}
sc.parallelize(input).reduce((m1,m2) => m1.merged(m2) { case ((k,v1),(_,v2)) => (k, v1+v2) })
{code}
which yields on the driver
{code}
Caused by: scala.MatchError: (null,null) (of class scala.Tuple2)
at $anonfun$1$$anonfun$apply$1.apply(<console>:28)
at $anonfun$1$$anonfun$apply$1.apply(<console>:28)
at scala.collection.immutable.HashMap$$anon$2$$anon$3.apply(HashMap.scala:150)
at scala.collection.immutable.HashMap$HashMap1.updated0(HashMap.scala:200)
at scala.collection.immutable.HashMap$HashTrieMap.updated0(HashMap.scala:322)
at scala.collection.immutable.HashMap$HashMap1.merge0(HashMap.scala:225)
at scala.collection.immutable.HashMap.merged(HashMap.scala:117)
at $anonfun$1.apply(<console>:28)
at $anonfun$1.apply(<console>:28)
at org.apache.spark.rdd.RDD$$anonfun$reduce$1$$anonfun$15.apply(RDD.scala:926)
at org.apache.spark.rdd.RDD$$anonfun$reduce$1$$anonfun$15.apply(RDD.scala:923)
at org.apache.spark.scheduler.JobWaiter.taskSucceeded(JobWaiter.scala:57)
at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:1185)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1658)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1620)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1609)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
{code}
It occurs when reducing the partition and I can't figure out how it would be fed a null. collecting or taking the RDD is fine. I suspect something strange related to the merged method which is only on immutable.HashMap, but there's no good reason that would be a problem.
I would suggest trying a different snippet of Scala code to merge the maps for now, since that seems to work.
> HashMap.merged not working properly with Spark
> ----------------------------------------------
>
> Key: SPARK-13230
> URL: https://issues.apache.org/jira/browse/SPARK-13230
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.0
> Environment: Ubuntu 14.04.3, Scala 2.11.7, Spark 1.6.0
> Reporter: Alin Treznai
>
> Using HashMap.merged with Spark fails with NullPointerException.
> {noformat}
> import org.apache.spark.{SparkConf, SparkContext}
> import scala.collection.immutable.HashMap
> object MergeTest {
> def mergeFn:(HashMap[String, Long], HashMap[String, Long]) => HashMap[String, Long] = {
> case (m1, m2) => m1.merged(m2){ case (x,y) => (x._1, x._2 + y._2) }
> }
> def main(args: Array[String]) = {
> val input = Seq(HashMap("A" -> 1L), HashMap("A" -> 2L, "B" -> 3L),HashMap("A" -> 2L, "C" -> 4L))
> val conf = new SparkConf().setAppName("MergeTest").setMaster("local[*]")
> val sc = new SparkContext(conf)
> val result = sc.parallelize(input).reduce(mergeFn)
> println(s"Result=$result")
> sc.stop()
> }
> }
> {noformat}
> Error message:
> org.apache.spark.SparkDriverExecutionException: Execution error
> at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:1169)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1637)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1952)
> at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:1025)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
> at org.apache.spark.rdd.RDD.reduce(RDD.scala:1007)
> at MergeTest$.main(MergeTest.scala:21)
> at MergeTest.main(MergeTest.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> Caused by: java.lang.NullPointerException
> at MergeTest$$anonfun$mergeFn$1$$anonfun$apply$1.apply(MergeTest.scala:12)
> at MergeTest$$anonfun$mergeFn$1$$anonfun$apply$1.apply(MergeTest.scala:12)
> at scala.collection.immutable.HashMap$$anon$2.apply(HashMap.scala:148)
> at scala.collection.immutable.HashMap$HashMap1.updated0(HashMap.scala:200)
> at scala.collection.immutable.HashMap$HashTrieMap.updated0(HashMap.scala:322)
> at scala.collection.immutable.HashMap$HashTrieMap.merge0(HashMap.scala:463)
> at scala.collection.immutable.HashMap.merged(HashMap.scala:117)
> at MergeTest$$anonfun$mergeFn$1.apply(MergeTest.scala:12)
> at MergeTest$$anonfun$mergeFn$1.apply(MergeTest.scala:11)
> at org.apache.spark.rdd.RDD$$anonfun$reduce$1$$anonfun$15.apply(RDD.scala:1020)
> at org.apache.spark.rdd.RDD$$anonfun$reduce$1$$anonfun$15.apply(RDD.scala:1017)
> at org.apache.spark.scheduler.JobWaiter.taskSucceeded(JobWaiter.scala:56)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:1165)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1637)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
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