java.lang.OutOfMemoryError: Java heap space

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via oracle.com by Unknown author

An easy way to solve OutOfMemoryError in java is to increase the maximum heap size by using JVM options -Xmx512M, this will immediately solve your OutOfMemoryError.

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via Stack Overflow by Eugene Yokota

In Eclipse : go to Run --> Run Configurations --> then select the project under maven build --> then select the tab "JRE" --> then enter -Xmx1024m

This should increase the memory heap for all the builds/projects. The above memory size is 1 GB

Solutions on the web

via spark-user by leosandylh@gmail.com, 1 year ago
Java heap space
via spark-user by leosandylh@gmail.com, 1 year ago
Java heap space
via apache.org by Unknown author, 1 year ago
via Google Groups by Kim Trang Le, 10 months ago
via Google Groups by Kim Trang Le, 1 year ago
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:2271)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
at java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1876)
at java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1785)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1188)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:44)
at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:84)
at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:301)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:294)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:122)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2032)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:703)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:702)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:306)
at org.apache.spark.mllib.tree.DecisionTree$.findBestSplits(DecisionTree.scala:625)
at org.apache.spark.mllib.tree.RandomForest.run(RandomForest.scala:235)
at org.apache.spark.mllib.tree.RandomForest$.trainRegressor(RandomForest.scala:380)
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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)

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