spark-instrumented-optimizer/python/pyspark/sql/__init__.py
Nicholas Chammas 2dd0388617 [SPARK-16772][PYTHON][DOCS] Fix API doc references to UDFRegistration + Update "important classes"
## Proposed Changes

* Update the list of "important classes" in `pyspark.sql` to match 2.0.
* Fix references to `UDFRegistration` so that the class shows up in the docs. It currently [doesn't](http://spark.apache.org/docs/latest/api/python/pyspark.sql.html).
* Remove some unnecessary whitespace in the Python RST doc files.

I reused the [existing JIRA](https://issues.apache.org/jira/browse/SPARK-16772) I created last week for similar API doc fixes.

## How was this patch tested?

* I ran `lint-python` successfully.
* I ran `make clean build` on the Python docs and confirmed the results are as expected locally in my browser.

Author: Nicholas Chammas <nicholas.chammas@gmail.com>

Closes #14496 from nchammas/SPARK-16772-UDFRegistration.
2016-08-06 05:02:59 +01:00

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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, HiveContext, UDFRegistration
from pyspark.sql.session import SparkSession
from pyspark.sql.column import Column
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
__all__ = [
'SparkSession', 'SQLContext', 'HiveContext', 'UDFRegistration',
'DataFrame', 'GroupedData', 'Column', 'Row',
'DataFrameNaFunctions', 'DataFrameStatFunctions', 'Window', 'WindowSpec',
'DataFrameReader', 'DataFrameWriter'
]