[SPARK-4846] When the vocabulary size is large, Word2Vec may yield "OutOfMemoryError: Requested array size exceeds VM limit"

• Type: Bug
• Status: Resolved
• Priority: Minor
• Resolution: Fixed
• Affects Version/s: 1.1.1, 1.2.0
• Fix Version/s: 1.3.0
• Component/s: MLlib

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.

• Target Version/s: 1.1.2, 1.2.1, 1.3.0
• Assignee: Joseph Tang
• Reporter: Joseph Tang
• Created: 15/Dec/14 05:26
• Updated: 29/Jan/16 02:15
• Resolved: 30/Jan/15 18:07

Description

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)

Issue Links

• is duplicated by: SPARK-5261 In some cases ,The value of word's vector representation is too big
• links to: [Github] Pull Request #3697 (jinntrance)
• links to: [Github] Pull Request #4247 (jinntrance)