Hi Sharad. The array size you (or the serializer) tries to allocate is just too big for the JVM.
You can also split your input further by increasing parallelism. Following is good explanintion https://plumbr.eu/outofmemoryerror/requested-array-size-exceeds-vm-limit regards, Vaquar khan On Sun, Jun 12, 2016 at 5:08 AM, sharad82 <khandelwal.gem...@gmail.com> wrote: > When trying to save the word2vec model trained over 10G of data leads to > below OOM error. > > java.lang.OutOfMemoryError: Requested array size exceeds VM limit > > Spark Version: 1.6 > spark.dynamicAllocation.enable false > spark.executor.memory 75g > spark.driver.memory 150g > spark.driver.cores 10 > > Full Stack Trace: > > java.lang.OutOfMemoryError: Requested array size exceeds VM limit > at java.util.Arrays.copyOf(Arrays.java:3332) > at > > java.lang.AbstractStringBuilder.expandCapacity(AbstractStringBuilder.java:137) > at > > java.lang.AbstractStringBuilder.ensureCapacityInternal(AbstractStringBuilder.java:121) > at > java.lang.AbstractStringBuilder.append(AbstractStringBuilder.java:421) > at java.lang.StringBuilder.append(StringBuilder.java:136) > at java.lang.StringBuilder.append(StringBuilder.java:131) > at > scala.StringContext.standardInterpolator(StringContext.scala:122) > at scala.StringContext.s(StringContext.scala:90) > at > > org.apache.spark.sql.execution.QueryExecution.toString(QueryExecution.scala:70) > at > > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:52) > at > > org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation.run(InsertIntoHadoopFsRelation.scala:108) > at > > org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58) > at > > org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56) > at > org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70) > at > > org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132) > at > > org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130) > at > > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150) > at > org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130) > at > > org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55) > at > > org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55) > at > > org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:256) > at > org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:148) > at > org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:139) > at > org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:334) > at > > org.apache.spark.ml.feature.Word2VecModel$Word2VecModelWriter.saveImpl(Word2Vec.scala:271) > at org.apache.spark.ml.util.MLWriter.save(ReadWrite.scala:91) > at > org.apache.spark.ml.util.MLWritable$class.save(ReadWrite.scala:131) > at > org.apache.spark.ml.feature.Word2VecModel.save(Word2Vec.scala:172) > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/OutOfMemoryError-When-saving-Word2Vec-tp27142.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > > -- Regards, Vaquar Khan +91 830-851-1500
