[jira] [Created] (SPARK-15531) spark-class tries to use too much memory when running Launcher

["mathieu longtin (JIRA)" <ji...@apache.org>]

mathieu longtin created SPARK-15531:
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             Summary: spark-class tries to use too much memory when running Launcher
                 Key: SPARK-15531
                 URL: https://issues.apache.org/jira/browse/SPARK-15531
             Project: Spark
          Issue Type: Bug
          Components: Deploy
    Affects Versions: 1.6.1, 2.0.0
         Environment: Linux running in Univa or Sun Grid Engine
            Reporter: mathieu longtin
            Priority: Minor


When running Java on a server with a lot of memory but a rather small virtual memory ulimit, Java will try to allocate a large memory pool and fail:

{code}
# System has 128GB of Ram but ulimit set to 7.5G
$ ulimit -v
7812500
$ java -client
Error occurred during initialization of VM
Could not reserve enough space for object heap
Error: Could not create the Java Virtual Machine.
Error: A fatal exception has occurred. Program will exit.
{code}

This is a known issue with Java, but unlikely to get fixed.

As a result, when starting various Spark process (spark-submit, master or workers), they fail when {{spark-class}} tries to run {{org.apache.spark.launcher.Main}}.

To fix this, add {{-Xmx128m}} to this line
{code}
"$RUNNER" -Xmx128m -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$\@"
{code}
(https://github.com/apache/spark/blob/master/bin/spark-class#L71)

We've been using 128m and that works in our setup. Considering all the launcher does is analyze the arguments and env var and spit out some command, it should be plenty. All other calls to Java seem to include some value for -Xmx, so it is not an issue elsewhere.

I don't mind submitting a PR, but I'm sure somebody has opinions on the 128m (bigger, smaller, configurable, ...), so I'd rather it would be discussed first.



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