spark-instrumented-optimizer/python/pyspark/sql/__init__.py
Chris Martin 76791b89f5 [SPARK-27463][PYTHON][FOLLOW-UP] Miscellaneous documentation and code cleanup of cogroup pandas UDF
Follow up from https://github.com/apache/spark/pull/24981 incorporating some comments from HyukjinKwon.

Specifically:

- Adding `CoGroupedData` to `pyspark/sql/__init__.py __all__` so that documentation is generated.
- Added pydoc, including example, for the use case whereby the user supplies a cogrouping function including a key.
- Added the boilerplate for doctests to cogroup.py.  Note that cogroup.py only contains the apply() function which has doctests disabled as per the  other Pandas Udfs.
- Restricted the newly exposed RelationalGroupedDataset constructor parameters to access only by the sql package.
- Some minor  formatting tweaks.

This was tested by running the appropriate unit tests.  I'm unsure as to how to check that my change will cause the documentation to be generated correctly, but it someone can describe how I can do this I'd be happy to check.

Closes #25939 from d80tb7/SPARK-27463-fixes.

Authored-by: Chris Martin <chris@cmartinit.co.uk>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2019-09-30 22:25:35 +09:00

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Python

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"""
Important classes of Spark SQL and DataFrames:
- :class:`pyspark.sql.SparkSession`
Main entry point for :class:`DataFrame` and SQL functionality.
- :class:`pyspark.sql.DataFrame`
A distributed collection of data grouped into named columns.
- :class:`pyspark.sql.Column`
A column expression in a :class:`DataFrame`.
- :class:`pyspark.sql.Row`
A row of data in a :class:`DataFrame`.
- :class:`pyspark.sql.GroupedData`
Aggregation methods, returned by :func:`DataFrame.groupBy`.
- :class:`pyspark.sql.DataFrameNaFunctions`
Methods for handling missing data (null values).
- :class:`pyspark.sql.DataFrameStatFunctions`
Methods for statistics functionality.
- :class:`pyspark.sql.functions`
List of built-in functions available for :class:`DataFrame`.
- :class:`pyspark.sql.types`
List of data types available.
- :class:`pyspark.sql.Window`
For working with window functions.
"""
from __future__ import absolute_import
from pyspark.sql.types import Row
from pyspark.sql.context import SQLContext, UDFRegistration
from pyspark.sql.session import SparkSession
from pyspark.sql.column import Column
from pyspark.sql.catalog import Catalog
from pyspark.sql.dataframe import DataFrame, DataFrameNaFunctions, DataFrameStatFunctions
from pyspark.sql.group import GroupedData
from pyspark.sql.readwriter import DataFrameReader, DataFrameWriter
from pyspark.sql.window import Window, WindowSpec
from pyspark.sql.cogroup import CoGroupedData
__all__ = [
'SparkSession', 'SQLContext', 'UDFRegistration',
'DataFrame', 'GroupedData', 'Column', 'Catalog', 'Row',
'DataFrameNaFunctions', 'DataFrameStatFunctions', 'Window', 'WindowSpec',
'DataFrameReader', 'DataFrameWriter', 'CoGroupedData'
]