Spark java.lang.OutOfMemoryError: Java heap space

Question

My cluster: 1 master, 11 slaves, each node has 6 GB memory.

My settings:

spark.executor.memory=4g, Dspark.akka.frameSize=512

Answer 1

To add a use case to this that is often not discussed, I will pose a solution when submitting a Spark application via spark-submit in local mode.

According to the gitbook Mastering Apache Spark by Jacek Laskowski:

You can run Spark in local mode. In this non-distributed single-JVM deployment mode, Spark spawns all the execution components - driver, executor, backend, and master - in the same JVM. This is the only mode where a driver is used for execution.

Thus, if you are experiencing OOM errors with the heap, it suffices to adjust the driver-memory rather than the executor-memory.

Here is an example:

spark-1.6.1/bin/spark-submit
  --class "MyClass"
  --driver-memory 12g
  --master local[*] 
  target/scala-2.10/simple-project_2.10-1.0.jar