[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14298192#comment-14298192
]
Michael Hynes commented on SPARK-3080:
--
What is the status of this SimpleALS.scala rewrite? Are you planning to merge
it into the master branch to replace the current implementation?
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
Affects Versions: 1.1.0, 1.2.0
Reporter: Burak Yavuz
Assignee: Xiangrui Meng
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14212815#comment-14212815
]
Xiangrui Meng commented on SPARK-3080:
--
Thanks for the confirmation! If [~ilganeli] also confirms that this is the root
cause, I'm going to close this JIRA as not a problem because this is the only
way I could reproduce the issue.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14212822#comment-14212822
]
Ilya Ganelin commented on SPARK-3080:
-
Hi Xiangrui - I was not doing any sort of randomization or sampling in the code
that produced this issue.
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
Affects Versions: 1.1.0
Reporter: Burak Yavuz
Assignee: Xiangrui Meng
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14211702#comment-14211702
]
Xiangrui Meng commented on SPARK-3080:
--
[~ilganeli] and [~derenrich], one more question: is there any non-deterministic
factor in your job? For example, if you generate random numbers without fixing
the seed per partition, the partition cannot be reproduced exactly.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14211881#comment-14211881
]
Daniel Erenrich commented on SPARK-3080:
Yes I am using random numbers. The random numbers I'm using should only affect
entries in the matrix I'm factorizing but not the number of non-zero entries.
(For clarity I'm using random numbers to sample 0s in my matrix which otherwise
is all 1s or blank. I need to do this since my input only tells me when an
action is taken not when it is not taken)
I won't have time for a little while to test if using a fixed seed would solve
this problem.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14211898#comment-14211898
]
Xiangrui Meng commented on SPARK-3080:
--
I see. If the procedure of sample negatives is not deterministic (by
deterministic I mean it cannot be re-computed), then the problem may occur.
For example,
{code}
rdd.filter(x = random.nextDouble() 0.2)
{code}
is not deterministic (which violates the assumption of RDD), while
{code}
rdd.mapPartitionsWithIndex { (idx, iter) =
val random = new Random(idx) // fixed seed
iter.filter(x = random.nextDouble() 0.2)
}
{code}
is deterministic.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14211986#comment-14211986
]
Daniel Erenrich commented on SPARK-3080:
Yes I understand. I am definitely doing it wrong. Didn't realize this would
break things.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14194058#comment-14194058
]
Daniel Erenrich commented on SPARK-3080:
Bumping RAM and changing parallelism did fix the issue for me.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14188928#comment-14188928
]
Xiangrui Meng commented on SPARK-3080:
--
SimpleALS is not merged yet. You need to build it and submit it as an
application: http://spark.apache.org/docs/latest/submitting-applications.html
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14189039#comment-14189039
]
Ilya Ganelin commented on SPARK-3080:
-
Hi all - I have managed to make some substantial progress! What I discovered is
that the default parallelization setting is critical. I did two things that got
me around this blocker:
1) I increased the amount of memory available to nodes - by itself this did not
solve the problem
2) I set .set(spark.default.parallelism,300)
I believe the latter is critical because even if I partitioned the data before
feeding it into ALS.train, the internal operations would produce RDDs that are
coalesced into fewer partitions. Consequently, I believe these smaller (but
presumably large in memory) partitions would create memory issues ultimately
leading to this and other hard to pin-down issues. Forcing default parallelism
ensured that even these internal operations would shard appropriately.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14189093#comment-14189093
]
Xiangrui Meng commented on SPARK-3080:
--
Btw, the `ArrayIndexOutOfBoundsException` is from the driver log. Could you
also check the executor logs? It may contain the root cause.
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
Affects Versions: 1.1.0
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14188012#comment-14188012
]
Xiangrui Meng commented on SPARK-3080:
--
Thanks for confirming the issue! I guess this could be a serialization issue.
Did you observe any executor loss during the computation or in-memory cached
RDDs switching to on-disk storage?
[~derenrich] Which public dataset are you using? Could you also let me know all
the ALS parameters and custom Spark settings you used? Thanks!
[~ilganeli] If you do need to run ALS on the full dataset, I recommend using
the new ALS implementation at
https://github.com/mengxr/spark-als/blob/master/src/main/scala/org/apache/spark/ml/SimpleALS.scala
It should perform better. But it is not merged yet.
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14185846#comment-14185846
]
Ilya Ganelin commented on SPARK-3080:
-
I've seen the same error on a dataset of ~200 million ratings. I have tried
lowering the number of iterations but unfortunately sub-sampling is not a
viable solution in our case.
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
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[jira] [Commented] (SPARK-3080) ArrayIndexOutOfBoundsException in ALS for Large datasets
[
https://issues.apache.org/jira/browse/SPARK-3080?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14168842#comment-14168842
]
Daniel Erenrich commented on SPARK-3080:
I ran into a similar bug. My datascale is smaller (only a few million entries
on 5 r3.xlarges) but subsampling causes the bug to go away as does lowering the
number of iterations. My dataset is public so if needed I could provide a test
case.
I'll probably look into this when I have some free time.
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
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