Hi,
I have a Spark workflow that when run on a relatively small portion of data works fine, but when run on big data fails with strange errors. In the log files of failed executors I found the following errors: Firstly > Managed memory leak detected; size = 263403077 bytes, TID = 6524 And then a series of > java.lang.OutOfMemoryError: Unable to acquire 241 bytes of memory, got 0 > at > org.apache.spark.memory.MemoryConsumer.allocatePage(MemoryConsumer.java:120) > at > org.apache.spark.shuffle.sort.ShuffleExternalSorter.acquireNewPageIfNecessary(ShuffleExternalSorter.java:346) > at > org.apache.spark.shuffle.sort.ShuffleExternalSorter.insertRecord(ShuffleExternalSorter.java:367) > at > org.apache.spark.shuffle.sort.UnsafeShuffleWriter.insertRecordIntoSorter(UnsafeShuffleWriter.java:237) > at > org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:164) > at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73) > at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) > at org.apache.spark.scheduler.Task.run(Task.scala:89) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) The job keeps failing in the same way (I tried a few times). What could be causing such error? I have a feeling that I'm not providing enough context necessary to understand the issue. Please ask for any other information needed. Thank you, Dusan
