GitHub user justinuang opened a pull request:
https://github.com/apache/spark/pull/8662
[SPARK-8632] [SQL] [PYSPARK] Poor Python UDF performance because of Râ¦
â¦DD caching
- I wanted to reuse most of the logic from PythonRDD, so I pulled out
two methods, writeHeaderToStream and readPythonProcessSocket
- The worker.py now has a switch where it reads an int that either tells
it to go into normal pyspark RDD mode, which is meant for a streaming
two thread workflow, and pyspark UDF mode, which is meant to be called
synchronously
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/justinuang/spark feature/pyspark_udf
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/8662.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 #8662
----
commit af5254b0fd4a11696f248d148c650f157496af6e
Author: Justin Uang <[email protected]>
Date: 2015-09-08T04:23:14Z
[SPARK-8632] [SQL] [PYSPARK] Poor Python UDF performance because of RDD
caching
- I wanted to reuse most of the logic from PythonRDD, so I pulled out
two methods, writeHeaderToStream and readPythonProcessSocket
- The worker.py now has a switch where it reads an int that either tells
it to go into normal pyspark RDD mode, which is meant for a streaming
two thread workflow, and pyspark UDF mode, which is meant to be called
synchronously
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