Is it a streaming job? On Sat, Sep 7, 2019, 5:04 AM Ankit Khettry <justankit2...@gmail.com> wrote:
> I have a Spark job that consists of a large number of Window operations > and hence involves large shuffles. I have roughly 900 GiBs of data, > although I am using a large enough cluster (10 * m5.4xlarge instances). I > am using the following configurations for the job, although I have tried > various other combinations without any success. > > spark.yarn.driver.memoryOverhead 6g > spark.storage.memoryFraction 0.1 > spark.executor.cores 6 > spark.executor.memory 36g > spark.memory.offHeap.size 8g > spark.memory.offHeap.enabled true > spark.executor.instances 10 > spark.driver.memory 14g > spark.yarn.executor.memoryOverhead 10g > > I keep running into the following OOM error: > > org.apache.spark.memory.SparkOutOfMemoryError: Unable to acquire 16384 > bytes of memory, got 0 > at org.apache.spark.memory.MemoryConsumer.throwOom(MemoryConsumer.java:157) > at > org.apache.spark.memory.MemoryConsumer.allocateArray(MemoryConsumer.java:98) > at > org.apache.spark.util.collection.unsafe.sort.UnsafeInMemorySorter.<init>(UnsafeInMemorySorter.java:128) > at > org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.<init>(UnsafeExternalSorter.java:163) > > I see there are a large number of JIRAs in place for similar issues and a > great many of them are even marked resolved. > Can someone guide me as to how to approach this problem? I am using > Databricks Spark 2.4.1. > > Best Regards > Ankit Khettry >
