spark-instrumented-optimizer/python/pyspark/sql/__init__.py
gatorsmile b9eafcb526 [SPARK-31088][SQL] Add back HiveContext and createExternalTable
### What changes were proposed in this pull request?
Based on the discussion in the mailing list [[Proposal] Modification to Spark's Semantic Versioning Policy](http://apache-spark-developers-list.1001551.n3.nabble.com/Proposal-Modification-to-Spark-s-Semantic-Versioning-Policy-td28938.html) , this PR is to add back the following APIs whose maintenance cost are relatively small.

- HiveContext
- createExternalTable APIs

### Why are the changes needed?

Avoid breaking the APIs that are commonly used.

### Does this PR introduce any user-facing change?
Adding back the APIs that were removed in 3.0 branch does not introduce the user-facing changes, because Spark 3.0 has not been released.

### How was this patch tested?

add a new test suite for createExternalTable APIs.

Closes #27815 from gatorsmile/addAPIsBack.

Lead-authored-by: gatorsmile <gatorsmile@gmail.com>
Co-authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
2020-03-26 23:51:15 -07:00

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2.6 KiB
Python

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"""
Important classes of Spark SQL and DataFrames:
- :class:`pyspark.sql.SparkSession`
Main entry point for :class:`DataFrame` and SQL functionality.
- :class:`pyspark.sql.DataFrame`
A distributed collection of data grouped into named columns.
- :class:`pyspark.sql.Column`
A column expression in a :class:`DataFrame`.
- :class:`pyspark.sql.Row`
A row of data in a :class:`DataFrame`.
- :class:`pyspark.sql.GroupedData`
Aggregation methods, returned by :func:`DataFrame.groupBy`.
- :class:`pyspark.sql.DataFrameNaFunctions`
Methods for handling missing data (null values).
- :class:`pyspark.sql.DataFrameStatFunctions`
Methods for statistics functionality.
- :class:`pyspark.sql.functions`
List of built-in functions available for :class:`DataFrame`.
- :class:`pyspark.sql.types`
List of data types available.
- :class:`pyspark.sql.Window`
For working with window functions.
"""
from __future__ import absolute_import
from pyspark.sql.types import Row
from pyspark.sql.context import SQLContext, HiveContext, UDFRegistration
from pyspark.sql.session import SparkSession
from pyspark.sql.column import Column
from pyspark.sql.catalog import Catalog
from pyspark.sql.dataframe import DataFrame, DataFrameNaFunctions, DataFrameStatFunctions
from pyspark.sql.group import GroupedData
from pyspark.sql.readwriter import DataFrameReader, DataFrameWriter
from pyspark.sql.window import Window, WindowSpec
from pyspark.sql.pandas.group_ops import PandasCogroupedOps
__all__ = [
'SparkSession', 'SQLContext', 'HiveContext', 'UDFRegistration',
'DataFrame', 'GroupedData', 'Column', 'Catalog', 'Row',
'DataFrameNaFunctions', 'DataFrameStatFunctions', 'Window', 'WindowSpec',
'DataFrameReader', 'DataFrameWriter', 'PandasCogroupedOps'
]