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Posted to issues@spark.apache.org by "Maciej Szymkiewicz (JIRA)" <ji...@apache.org> on 2017/01/10 20:57:58 UTC
[jira] [Updated] (SPARK-19161) Improving UDF Docstrings
[ https://issues.apache.org/jira/browse/SPARK-19161?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Maciej Szymkiewicz updated SPARK-19161:
---------------------------------------
Affects Version/s: (was: 1.5.0)
> Improving UDF Docstrings
> ------------------------
>
> Key: SPARK-19161
> URL: https://issues.apache.org/jira/browse/SPARK-19161
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 1.6.0, 2.0.0, 2.1.0, 2.2.0
> Reporter: Maciej Szymkiewicz
>
> Current state
> Right now `udf` returns an `UserDefinedFunction` object which doesn't provide meaningful docstring:
> {code}
> In [1]: from pyspark.sql.types import IntegerType
> In [2]: from pyspark.sql.functions import udf
> In [3]: def _add_one(x):
> """Adds one"""
> if x is not None:
> return x + 1
> ...:
> In [4]: add_one = udf(_add_one, IntegerType())
> In [5]: ?add_one
> Type: UserDefinedFunction
> String form: <pyspark.sql.functions.UserDefinedFunction object at 0x7f281ed2d198>
> File: ~/Spark/spark-2.0/python/pyspark/sql/functions.py
> Signature: add_one(*cols)
> Docstring:
> User defined function in Python
> .. versionadded:: 1.3
> In [6]: help(add_one)
> Help on UserDefinedFunction in module pyspark.sql.functions object:
> class UserDefinedFunction(builtins.object)
> | User defined function in Python
> |
> | .. versionadded:: 1.3
> |
> | Methods defined here:
> |
> | __call__(self, *cols)
> | Call self as a function.
> |
> | __del__(self)
> |
> | __init__(self, func, returnType, name=None)
> | Initialize self. See help(type(self)) for accurate signature.
> |
> | ----------------------------------------------------------------------
> | Data descriptors defined here:
> |
> | __dict__
> | dictionary for instance variables (if defined)
> |
> | __weakref__
> | list of weak references to the object (if defined)
> (END)
> {code}
> It is possible to extract the function:
> {code}
> In [7]: ?add_one.func
> Signature: add_one.func(x)
> Docstring: Adds one
> File: ~/Spark/spark-2.0/<ipython-input-3-d2d8e4c530ac>
> Type: function
> In [8]: help(add_one.func)
> Help on function _add_one in module __main__:
> _add_one(x)
> Adds one
> {code}
> but it assumes that the final user is aware of the distinction between UDF and built-in functions.
> Proposed
> Copy input functions docstring to the UDF object or function wrapper.
> {code}
> In [1]: from pyspark.sql.types import IntegerType
> In [2]: from pyspark.sql.functions import udf
> In [3]: def _add_one(x):
> """Adds one"""
> if x is not None:
> return x + 1
> ...:
> In [4]: add_one = udf(_add_one, IntegerType())
> In [5]: ?add_one
> Signature: add_one(x)
> Docstring:
> Adds one
> SQL Type: IntegerType
> File: ~/Workspace/spark/<ipython-input-3-d2d8e4c530ac>
> Type: function
> In [6]: help(add_one)
> Help on function _add_one in module __main__:
> _add_one(x)
> Adds one
>
> SQL Type: IntegerType
> (END)
> {code}
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