spark-instrumented-optimizer/python/pyspark/sql/__init__.py
Reynold Xin ce320cb2db [SPARK-8060] Improve DataFrame Python test coverage and documentation.
Author: Reynold Xin <rxin@databricks.com>

Closes #6601 from rxin/python-read-write-test-and-doc and squashes the following commits:

baa8ad5 [Reynold Xin] Code review feedback.
f081d47 [Reynold Xin] More documentation updates.
c9902fa [Reynold Xin] [SPARK-8060] Improve DataFrame Python reader/writer interface doc and testing.
2015-06-03 00:23:34 -07:00

76 lines
2.9 KiB
Python

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""
Important classes of Spark SQL and DataFrames:
- :class:`pyspark.sql.SQLContext`
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.HiveContext`
Main entry point for accessing data stored in Apache Hive.
- :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
def since(version):
"""
A decorator that annotates a function to append the version of Spark the function was added.
"""
import re
indent_p = re.compile(r'\n( +)')
def deco(f):
indents = indent_p.findall(f.__doc__)
indent = ' ' * (min(len(m) for m in indents) if indents else 0)
f.__doc__ = f.__doc__.rstrip() + "\n\n%s.. versionadded:: %s" % (indent, version)
return f
return deco
from pyspark.sql.types import Row
from pyspark.sql.context import SQLContext, HiveContext
from pyspark.sql.column import Column
from pyspark.sql.dataframe import DataFrame, SchemaRDD, DataFrameNaFunctions, DataFrameStatFunctions
from pyspark.sql.group import GroupedData
from pyspark.sql.readwriter import DataFrameReader, DataFrameWriter
from pyspark.sql.window import Window, WindowSpec
__all__ = [
'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row',
'DataFrameNaFunctions', 'DataFrameStatFunctions', 'Window', 'WindowSpec',
'DataFrameReader', 'DataFrameWriter'
]