[ https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14188354#comment-14188354 ]
Ilya Ganelin commented on SPARK-3080: ------------------------------------- Hello Xiangrui - happy to hear that you're on this! With regards to the first question, I have not seen any spillage to disk but I have seen executor loss (on a relatively frequent basis). I have not known whether this is a function of use on our cluster or an internal spark issue. With regards to upgrading ALS, can I simply replace the old SimpleALS.scala with the new one or will there be additional dependencies? I am interested in doing a piece-meal upgrade of ML Lib (without upgrading the rest of Spark from version 1.1). I want to do this to maintain compatibility with CDH 5.2. Please let me know, thank you. > ArrayIndexOutOfBoundsException in ALS for Large datasets > -------------------------------------------------------- > > Key: SPARK-3080 > URL: https://issues.apache.org/jira/browse/SPARK-3080 > Project: Spark > Issue Type: Bug > Components: MLlib > Reporter: Burak Yavuz > > The stack trace is below: > {quote} > java.lang.ArrayIndexOutOfBoundsException: 2716 > > org.apache.spark.mllib.recommendation.ALS$$anonfun$org$apache$spark$mllib$recommendation$ALS$$updateBlock$1.apply$mcVI$sp(ALS.scala:543) > scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:141) > > org.apache.spark.mllib.recommendation.ALS.org$apache$spark$mllib$recommendation$ALS$$updateBlock(ALS.scala:537) > > org.apache.spark.mllib.recommendation.ALS$$anonfun$org$apache$spark$mllib$recommendation$ALS$$updateFeatures$2.apply(ALS.scala:505) > > org.apache.spark.mllib.recommendation.ALS$$anonfun$org$apache$spark$mllib$recommendation$ALS$$updateFeatures$2.apply(ALS.scala:504) > > org.apache.spark.rdd.MappedValuesRDD$$anonfun$compute$1.apply(MappedValuesRDD.scala:31) > > org.apache.spark.rdd.MappedValuesRDD$$anonfun$compute$1.apply(MappedValuesRDD.scala:31) > scala.collection.Iterator$$anon$11.next(Iterator.scala:328) > scala.collection.Iterator$$anon$11.next(Iterator.scala:328) > > org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:138) > > org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159) > > org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:158) > > scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772) > > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > > scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771) > org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:158) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > > org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > {quote} > This happened after the dataset was sub-sampled. > Dataset properties: ~12B ratings > Setup: 55 r3.8xlarge ec2 instances -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org