Hi. You can increase the memory given to Flink by increasing JVM Heap memory in local. If you are using Eclipse as IDE, add “-Xmx<HEAPSIZE>” option in run configuration. [1]. Although you are using IntelliJ IDEA as IDE, you can increase JVM Heap using the same way. [2]
[1] http://help.eclipse.org/luna/index.jsp?topic=%2Forg.eclipse.jdt.doc.user%2Ftasks%2Ftasks-java-local-configuration.htm [2] https://www.jetbrains.com/idea/help/creating-and-editing-run-debug-configurations.html Regards, Chiwan Park > On Jun 17, 2015, at 2:01 PM, Sebastian <s...@apache.org> wrote: > > Hi, > > Flink has memory problems when I run an algorithm from my local IDE on a 2GB > graph. Is there any way that I can increase the memory given to Flink? > > Best, > Sebastian > > Caused by: java.lang.RuntimeException: Memory ran out. numPartitions: 32 > minPartition: 4 maxPartition: 4 number of overflow segments: 151 bucketSize: > 146 Overall memory: 14024704 Partition memory: 4194304 > at > org.apache.flink.runtime.operators.hash.CompactingHashTable.getNextBuffer(CompactingHashTable.java:784) > at > org.apache.flink.runtime.operators.hash.CompactingHashTable.insertBucketEntryFromSearch(CompactingHashTable.java:668) > at > org.apache.flink.runtime.operators.hash.CompactingHashTable.insertOrReplaceRecord(CompactingHashTable.java:538) > at > org.apache.flink.runtime.operators.hash.CompactingHashTable.buildTableWithUniqueKey(CompactingHashTable.java:347) > at > org.apache.flink.runtime.iterative.task.IterationHeadPactTask.readInitialSolutionSet(IterationHeadPactTask.java:209) > at > org.apache.flink.runtime.iterative.task.IterationHeadPactTask.run(IterationHeadPactTask.java:270) > at > org.apache.flink.runtime.operators.RegularPactTask.invoke(RegularPactTask.java:362) > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:559) > at java.lang.Thread.run(Thread.java:745)
