GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/12127
[SPARK-12981] [SQL] extract Pyhton UDF in physical plan
## What changes were proposed in this pull request?
Currently we extract Python UDFs into a special logical plan EvaluatePython
in analyzer, But EvaluatePython is not part of catalyst, many rules have no
knowledge of it , which will break many things (for example, filter push down
or column pruning).
We should treat Python UDFs as normal expressions, until we want to
evaluate in physical plan, we could extract them in end of optimizer, or
physical plan.
This PR extract Python UDFs in physical plan.
Closes #10935
## How was this patch tested?
Added regression tests.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/davies/spark py_udf
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/12127.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 #12127
----
commit c10d80d6dda6a534a6916d10bd418afbf9761dfb
Author: Davies Liu <[email protected]>
Date: 2016-04-02T06:39:42Z
extract Pyhton UDF in physical plan
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