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
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commit f933713ed628779309fab0da76045f8750d6b350
Author: Davies Liu <[email protected]>
Date: 2014-07-17T08:03:32Z
Hash based disk spilling aggregation
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