a76c2e128b
This PR makes the types module in `pyspark/sql/types` work with pylint static analysis by removing the dynamic naming of the `pyspark/sql/_types` module to `pyspark/sql/types`.
Tests are now loaded using `$PYSPARK_DRIVER_PYTHON -m module` rather than `$PYSPARK_DRIVER_PYTHON module.py`. The old method adds the location of `module.py` to `sys.path`, so this change prevents accidental use of relative paths in Python.
Author: Michael Nazario <mnazario@palantir.com>
Closes #6439 from mnazario/feature/SPARK-7899 and squashes the following commits:
366ef30 [Michael Nazario] Remove hack on random.py
bb8b04d [Michael Nazario] Make doctests consistent with other tests
6ee4f75 [Michael Nazario] Change test scripts to use "-m"
673528f [Michael Nazario] Move _types back to types
65 lines
2.6 KiB
Python
65 lines
2.6 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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- :class:`pyspark.sql.SQLContext`
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Main entry point for :class:`DataFrame` and SQL functionality.
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- :class:`pyspark.sql.DataFrame`
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A distributed collection of data grouped into named columns.
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- :class:`pyspark.sql.Column`
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A column expression in a :class:`DataFrame`.
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- :class:`pyspark.sql.Row`
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A row of data in a :class:`DataFrame`.
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- :class:`pyspark.sql.HiveContext`
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Main entry point for accessing data stored in Apache Hive.
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- :class:`pyspark.sql.GroupedData`
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Aggregation methods, returned by :func:`DataFrame.groupBy`.
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- :class:`pyspark.sql.DataFrameNaFunctions`
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Methods for handling missing data (null values).
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- :class:`pyspark.sql.DataFrameStatFunctions`
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Methods for statistics functionality.
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- :class:`pyspark.sql.functions`
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List of built-in functions available for :class:`DataFrame`.
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- :class:`pyspark.sql.types`
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List of data types available.
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- :class:`pyspark.sql.Window`
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For working with window functions.
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"""
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from __future__ import absolute_import
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def since(version):
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def deco(f):
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f.__doc__ = f.__doc__.rstrip() + "\n\n.. versionadded:: %s" % version
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return f
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return deco
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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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from pyspark.sql.readwriter import DataFrameReader, DataFrameWriter
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from pyspark.sql.window import Window, WindowSpec
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__all__ = [
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'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row',
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'DataFrameNaFunctions', 'DataFrameStatFunctions', 'Window', 'WindowSpec',
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]
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