GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/4629
[SPARK-5785] [PySpark] narrow dependency for cogroup/join in PySpark
Currently, PySpark does not support narrow dependency during cogroup/join
when the two RDDs have the partitioner, another unnecessary shuffle stage will
come in.
The Python implementation of cogroup/join is different than Scala one, it
depends on union() and partitionBy(). This patch will try to use
PartitionerAwareUnionRDD() in union(), when all the RDDs have the same
partitioner. It also fix `reservePartitioner` in all the map() or
mapPartitions(), then partitionBy() can skip the unnecessary shuffle stage.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/davies/spark narrow
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/4629.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 #4629
----
commit eb26c62f4a3dc5920df2d2624918826d32d97bb5
Author: Davies Liu <dav...@databricks.com>
Date: 2015-02-16T21:17:11Z
narrow dependency in PySpark
----
---
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.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
