Joseph Tang created SPARK-4846:
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Summary: 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)
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