GitHub user davies opened a pull request: https://github.com/apache/spark/pull/1460
[SPARK-2538] [PySpark] Hash based disk spilling aggregation During aggregation in Python worker, if the memory usage is above spark.executor.memory, it will do disk spilling aggregation. It will split the aggregation into multiple stage, in each stage, it will partition the aggregated data by hash and dump them into disks. After all the data are aggregated, it will merge all the stages together (partition by partition). You can merge this pull request into a Git repository by running: $ git pull https://github.com/davies/spark spill Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/1460.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #1460 ---- commit f933713ed628779309fab0da76045f8750d6b350 Author: Davies Liu <davies....@gmail.com> Date: 2014-07-17T08:03:32Z Hash based disk spilling aggregation ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. ---