77ab49b857
Author: Reynold Xin <rxin@databricks.com> Closes #10559 from rxin/remove-deprecated-sql.
61 lines
2.4 KiB
Python
61 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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- :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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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, 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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'DataFrameReader', 'DataFrameWriter'
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]
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