Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

update proportion of memory #66

Closed
wants to merge 1 commit into from
Closed
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions docs/tuning.md
Original file line number Diff line number Diff line change
Expand Up @@ -163,8 +163,8 @@ their work directories), *not* on your driver program.
**Cache Size Tuning**

One important configuration parameter for GC is the amount of memory that should be used for caching RDDs.
By default, Spark uses 66% of the configured executor memory (`spark.executor.memory` or `SPARK_MEM`) to
cache RDDs. This means that 33% of memory is available for any objects created during task execution.
By default, Spark uses 60% of the configured executor memory (`spark.executor.memory` or `SPARK_MEM`) to
cache RDDs. This means that 40% of memory is available for any objects created during task execution.

In case your tasks slow down and you find that your JVM is garbage-collecting frequently or running out of
memory, lowering this value will help reduce the memory consumption. To change this to say 50%, you can call
Expand Down