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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 05:35:24 UTC
[jira] [Updated] (SPARK-5480) GraphX pageRank:
java.lang.ArrayIndexOutOfBoundsException:
[ https://issues.apache.org/jira/browse/SPARK-5480?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-5480:
--------------------------------
Labels: bulk-closed (was: )
> GraphX pageRank: java.lang.ArrayIndexOutOfBoundsException:
> -----------------------------------------------------------
>
> Key: SPARK-5480
> URL: https://issues.apache.org/jira/browse/SPARK-5480
> Project: Spark
> Issue Type: Bug
> Components: GraphX
> Affects Versions: 1.2.0, 1.3.1
> Environment: Yarn client
> Reporter: Stephane Maarek
> Priority: Major
> Labels: bulk-closed
>
> Running the following code:
> val subgraph = graph.subgraph (
> vpred = (id,article) => //working predicate)
> ).cache()
> println( s"Subgraph contains ${subgraph.vertices.count} nodes and ${subgraph.edges.count} edges")
> val prGraph = subgraph.staticPageRank(5).cache
> val titleAndPrGraph = subgraph.outerJoinVertices(prGraph.vertices) {
> (v, title, rank) => (rank.getOrElse(0.0), title)
> }
> titleAndPrGraph.vertices.top(13) {
> Ordering.by((entry: (VertexId, (Double, _))) => entry._2._1)
> }.foreach(t => println(t._2._2._1 + ": " + t._2._1 + ", id:" + t._1))
> Returns a graph with 5000 nodes and 4000 edges.
> Then it crashes during the PageRank with the following:
> 15/01/29 05:51:07 INFO scheduler.TaskSetManager: Starting task 125.0 in stage 39.0 (TID 1808, *HIDDEN, PROCESS_LOCAL, 2059 bytes)
> 15/01/29 05:51:07 WARN scheduler.TaskSetManager: Lost task 107.0 in stage 39.0 (TID 1794, *HIDDEN): java.lang.ArrayIndexOutOfBoundsException: -1
> at org.apache.spark.graphx.util.collection.GraphXPrimitiveKeyOpenHashMap$mcJI$sp.apply$mcJI$sp(GraphXPrimitiveKeyOpenHashMap.scala:64)
> at org.apache.spark.graphx.impl.EdgePartition.updateVertices(EdgePartition.scala:91)
> at org.apache.spark.graphx.impl.ReplicatedVertexView$$anonfun$2$$anonfun$apply$1.apply(ReplicatedVertexView.scala:75)
> at org.apache.spark.graphx.impl.ReplicatedVertexView$$anonfun$2$$anonfun$apply$1.apply(ReplicatedVertexView.scala:73)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at org.apache.spark.graphx.impl.EdgeRDDImpl$$anonfun$mapEdgePartitions$1.apply(EdgeRDDImpl.scala:110)
> at org.apache.spark.graphx.impl.EdgeRDDImpl$$anonfun$mapEdgePartitions$1.apply(EdgeRDDImpl.scala:108)
> at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:601)
> at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:601)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:228)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
> at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
> at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
> at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:61)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:228)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> 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:744)
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