8164fbc255
dataframe.py is splited into column.py, group.py and dataframe.py:
```
360 column.py
1223 dataframe.py
183 group.py
```
Author: Davies Liu <davies@databricks.com>
Closes #6201 from davies/split_df and squashes the following commits:
fc8f5ab [Davies Liu] split dataframe.py into multiple files
(cherry picked from commit d7b69946cb)
Signed-off-by: Reynold Xin <rxin@databricks.com>
66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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Important classes of Spark SQL and DataFrames:
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- L{SQLContext}
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Main entry point for :class:`DataFrame` and SQL functionality.
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- L{DataFrame}
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A distributed collection of data grouped into named columns.
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- L{Column}
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A column expression in a :class:`DataFrame`.
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- L{Row}
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A row of data in a :class:`DataFrame`.
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- L{HiveContext}
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Main entry point for accessing data stored in Apache Hive.
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- L{GroupedData}
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Aggregation methods, returned by :func:`DataFrame.groupBy`.
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- L{DataFrameNaFunctions}
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Methods for handling missing data (null values).
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- L{DataFrameStatFunctions}
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Methods for statistics functionality.
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- L{functions}
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List of built-in functions available for :class:`DataFrame`.
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- L{types}
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List of data types available.
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"""
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from __future__ import absolute_import
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# fix the module name conflict for Python 3+
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import sys
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from . import _types as types
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modname = __name__ + '.types'
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types.__name__ = modname
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# update the __module__ for all objects, make them picklable
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for v in types.__dict__.values():
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if hasattr(v, "__module__") and v.__module__.endswith('._types'):
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v.__module__ = modname
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sys.modules[modname] = types
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del modname, sys
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from pyspark.sql.types import Row
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from pyspark.sql.context import SQLContext, HiveContext
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from pyspark.sql.column import Column
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from pyspark.sql.dataframe import DataFrame, SchemaRDD, DataFrameNaFunctions, DataFrameStatFunctions
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from pyspark.sql.group import GroupedData
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__all__ = [
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'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row',
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'DataFrameNaFunctions', 'DataFrameStatFunctions'
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]
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