GitHub user JoshRosen opened a pull request:
https://github.com/apache/spark/pull/17927
[SPARK-20685] Fix BatchPythonEvaluation bug in case of single UDF w/
repeated arg.
## What changes were proposed in this pull request?
There's a latent corner-case bug in PySpark UDF evaluation where executing
a `BatchPythonEvaluation` with a single multi-argument UDF where _at least one
argument value is repeated_ will crash at execution with a confusing error.
This problem was introduced in #12057: there code there has a fast path for
handling a "batch UDF evaluation consisting of a single Python UDF", but that
branch incorrectly assumes that a single UDF won't have repeated arguments and
therefore skips the code for unpacking arguments from the input row (whose
schema may not necessarily match the UDF inputs due to de-duplication of
repeated arguments which occurred in the JVM before sending UDF inputs to
Python).
This fix here is simply to remove this special-casing: it turns out that
the code in the "multiple UDFs" branch just so happens to work for the
single-UDF case because Python treats `(x)` as equivalent to `x`, not as a
single-argument tuple.
## How was this patch tested?
New regression test in `pyspark.python.sql.tests` module (tested and
confirmed that it fails before my fix).
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/JoshRosen/spark SPARK-20685
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17927.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 #17927
----
commit 6912cb205125b0e8e70a440d4b73252551b9c35d
Author: Josh Rosen <joshro...@databricks.com>
Date: 2017-05-09T21:53:08Z
Add (failing) regression test.
commit 17e69b5c10eeb9a6138a50985ed891ebae398619
Author: Josh Rosen <joshro...@databricks.com>
Date: 2017-05-09T22:15:17Z
Fix SPARK-20685
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