spark-instrumented-optimizer/python/pyspark/sql/__init__.py
Burak Yavuz 4dc8d74491 [SPARK-7240][SQL] Single pass covariance calculation for dataframes
Added the calculation of covariance between two columns to DataFrames.

cc mengxr rxin

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #5825 from brkyvz/df-cov and squashes the following commits:

cb18046 [Burak Yavuz] changed to sample covariance
f2e862b [Burak Yavuz] fixed failed test
51e39b8 [Burak Yavuz] moved implementation
0c6a759 [Burak Yavuz] addressed math comments
8456eca [Burak Yavuz] fix pyStyle3
aa2ad29 [Burak Yavuz] fix pyStyle2
4e97a50 [Burak Yavuz] Merge branch 'master' of github.com:apache/spark into df-cov
e3b0b85 [Burak Yavuz] addressed comments v0.1
a7115f1 [Burak Yavuz] fix python style
7dc6dbc [Burak Yavuz] reorder imports
408cb77 [Burak Yavuz] initial commit
2015-05-01 13:29:17 -07:00

63 lines
2.3 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 __future__ import absolute_import
# fix the module name conflict for Python 3+
import sys
from . import _types as types
modname = __name__ + '.types'
types.__name__ = modname
# update the __module__ for all objects, make them picklable
for v in types.__dict__.values():
if hasattr(v, "__module__") and v.__module__.endswith('._types'):
v.__module__ = modname
sys.modules[modname] = types
del modname, sys
from pyspark.sql.types import Row
from pyspark.sql.context import SQLContext, HiveContext
from pyspark.sql.dataframe import DataFrame, GroupedData, Column, SchemaRDD, DataFrameNaFunctions
from pyspark.sql.dataframe import DataFrameStatFunctions
__all__ = [
'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row',
'DataFrameNaFunctions', 'DataFrameStatFunctions'
]