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#
# 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{DataFrameStatFunctions}
Methods for statistics functionality.
- 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.column import Column
from pyspark.sql.dataframe import DataFrame, SchemaRDD, DataFrameNaFunctions, DataFrameStatFunctions
from pyspark.sql.group import GroupedData
__all__ = [
'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row',
'DataFrameNaFunctions', 'DataFrameStatFunctions'
]
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