GitHub user BryanCutler opened a pull request:
https://github.com/apache/spark/pull/17193
[SPARK-19348][PYTHON] PySpark keyword_only decorator is not thread-safe
## What changes were proposed in this pull request?
The `@keyword_only` decorator in PySpark is not thread-safe. It writes
kwargs to a static class variable in the decorator, which is then retrieved
later in the class method as `_input_kwargs`. If multiple threads are
constructing the same class with different kwargs, it becomes a race condition
to read from the static class variable before it's overwritten. See
[SPARK-19348](https://issues.apache.org/jira/browse/SPARK-19348) for
reproduction code.
This change will write the kwargs to a member variable so that multiple
threads can operate on separate instances without the race condition. It does
not protect against multiple threads operating on a single instance, but that
is better left to the user to synchronize.
## How was this patch tested?
Added new unit tests for using the keyword_only decorator and a regression
test that verifies `_input_kwargs` can be overwritten from different class
instances.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/BryanCutler/spark
pyspark-keyword_only-threadsafe-SPARK-19348-2_1
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17193.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 #17193
----
commit 945c54d0f125346dd6d0ad4739665e6529d19712
Author: Bryan Cutler <[email protected]>
Date: 2017-03-07T18:53:51Z
made keyword_only decorator thread-safe by saving _input_kwargs to self
commit 7700f076a3bc7117ae274a7963d6262e54d38696
Author: Bryan Cutler <[email protected]>
Date: 2017-03-07T18:55:22Z
added keyword_only tests, including a regression test
commit 7056b4d5cf160b9ef047f2fffc3591b145c44995
Author: Bryan Cutler <[email protected]>
Date: 2017-03-07T18:57:50Z
updated _input_kwargs usage in pyspark-ml
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