spark-instrumented-optimizer/python/pyspark/sql/__init__.py
Reynold Xin 305abe1e57 [Doc] Improve Python DataFrame documentation
Author: Reynold Xin <rxin@databricks.com>

Closes #5287 from rxin/pyspark-df-doc-cleanup-context and squashes the following commits:

1841b60 [Reynold Xin] Lint.
f2007f1 [Reynold Xin] functions and types.
bc3b72b [Reynold Xin] More improvements to DataFrame Python doc.
ac1d4c0 [Reynold Xin] Bug fix.
b163365 [Reynold Xin] Python fix. Added Experimental flag to DataFrameNaFunctions.
608422d [Reynold Xin] [Doc] Cleanup context.py Python docs.
2015-03-31 18:31:36 -07:00

48 lines
1.8 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:
- L{SQLContext}
Main entry point for :class:`DataFrame` and SQL functionality.
- L{DataFrame}
A distributed collection of data grouped into named columns.
- L{Column}
A column expression in a :class:`DataFrame`.
- L{Row}
A row of data in a :class:`DataFrame`.
- L{HiveContext}
Main entry point for accessing data stored in Apache Hive.
- L{GroupedData}
Aggregation methods, returned by :func:`DataFrame.groupBy`.
- L{DataFrameNaFunctions}
Methods for handling missing data (null values).
- L{functions}
List of built-in functions available for :class:`DataFrame`.
- L{types}
List of data types available.
"""
from pyspark.sql.context import SQLContext, HiveContext
from pyspark.sql.types import Row
from pyspark.sql.dataframe import DataFrame, GroupedData, Column, SchemaRDD, DataFrameNaFunctions
__all__ = [
'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row', 'DataFrameNaFunctions'
]