[
https://issues.apache.org/jira/browse/SPARK-4846?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14246337#comment-14246337
]
Apache Spark commented on SPARK-4846:
-------------------------------------
User 'jinntrance' has created a pull request for this issue:
https://github.com/apache/spark/pull/3697
> When the vocabulary size is large, Word2Vec may yield "OutOfMemoryError:
> Requested array size exceeds VM limit"
> ---------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-4846
> URL: https://issues.apache.org/jira/browse/SPARK-4846
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.1.0
> Environment: Use Word2Vec to process a corpus(sized 3.5G) with one
> partition.
> The corpus contains about 300 million words and its vocabulary size is about
> 10 million.
> Reporter: Joseph Tang
> Priority: Critical
>
> Exception in thread "Driver" java.lang.reflect.InvocationTargetException
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:162)
> Caused by: java.lang.OutOfMemoryError: Requested array size exceeds VM limit
> at java.util.Arrays.copyOf(Arrays.java:2271)
> at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113)
> at
> java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
> at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:140)
> at
> java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1870)
> at
> java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1779)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1186)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
> at
> org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:42)
> at
> org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:73)
> at
> org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:164)
> at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158)
> at org.apache.spark.SparkContext.clean(SparkContext.scala:1242)
> at org.apache.spark.rdd.RDD.mapPartitionsWithIndex(RDD.scala:610)
> at
> org.apache.spark.mllib.feature.Word2Vec$$anonfun$fit$1.apply$mcVI$sp(Word2Vec.scala:291)
> at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:141)
> at org.apache.spark.mllib.feature.Word2Vec.fit(Word2Vec.scala:290)
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]