paleolimbot commented on code in PR #50419: URL: https://github.com/apache/arrow/pull/50419#discussion_r3560232801
########## docs/source/python/parquet/parquet_type_handling.rst: ########## @@ -0,0 +1,156 @@ +.. 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. + +.. currentmodule:: pyarrow +.. _parquet_type_handling: + + +Data Type Handling +================== + +Reading types as DictionaryArray +-------------------------------- + +The ``read_dictionary`` option in ``read_table`` and ``ParquetDataset`` will +cause columns to be read as ``DictionaryArray``, which will become +``pandas.Categorical`` when converted to pandas. This option is only valid for +string and binary column types, and it can yield significantly lower memory use +and improved performance for columns with many repeated string values. + +.. code-block:: python + + >>> import pyarrow as pa + >>> import pyarrow.parquet as pq + + >>> table = pa.table({'one': [-1, None, 2.5], + ... 'two': ['foo', 'bar', 'baz'], + ... 'three': [True, False, True]}) + ... + >>> pq.write_table(table, 'example.parquet') + + >>> pq.read_table('example.parquet', read_dictionary=['two']) + pyarrow.Table + one: double + two: dictionary<values=string, indices=int32, ordered=0> + three: bool + ---- + one: [[-1,null,2.5]] + two: [ -- dictionary: + ["foo","bar","baz"] -- indices: + [0,1,2]] + three: [[true,false,true]] + +Reading binary and list columns +------------------------------- + +By default, Parquet ``BYTE_ARRAY`` columns are read as Arrow ``binary`` type +and Parquet ``LIST`` columns are read as Arrow ``list`` type, both of which use +32-bit offsets. For very large datasets this can overflow. The ``binary_type`` +and ``list_type`` parameters let you choose a different Arrow type on read. + +``binary_type`` accepts ``pa.binary()`` (default), ``pa.large_binary()``, or +``pa.binary_view()``: + +.. code-block:: python + + >>> import pyarrow as pa + >>> table = pa.table({'data': pa.array([b'hello', b'world'], pa.binary())}) + >>> pq.write_table(table, 'binary.parquet', store_schema=False) + >>> pq.read_table('binary.parquet', binary_type=pa.large_binary()).schema + data: large_binary + +``list_type`` accepts ``pa.ListType`` or ``pa.LargeListType``: + +.. code-block:: python + + >>> table = pa.table({'lists': pa.array([[1, 2], [3]], pa.list_(pa.int32()))}) + >>> pq.write_table(table, 'lists.parquet', store_schema=False) + >>> pq.read_table('lists.parquet', list_type=pa.LargeListType).schema + lists: large_list<element: int32> + child 0, element: int32 + +.. note:: + Both settings are ignored when a serialized Arrow schema is present in the + Parquet file metadata (i.e. when the parquet file was written with + ``store_schema=True``). + +Read in Arrow Extension Types +----------------------------- + +Certain Parquet logical types (JSON, UUID, Geometry, Geography) are supported +and read as Arrow extension types by default (``arrow.json``, ``arrow.uuid`` +and ``geoarrow.wkb`` respectively). This support is enabled via the +``arrow_extensions_enabled`` parameter and is used in :func:`~pyarrow.parquet.read_table`, +:class:`~pyarrow.parquet.ParquetFile`, :class:`~pyarrow.parquet.ParquetDataset`, and +:func:`~pyarrow.parquet.read_schema`. + +To read these Parquet logical types as storage types (default behavior +until PyArrow version ``21.0.0``), set ``arrow_extensions_enabled=False``. + +.. note:: + Reading GEOMETRY/GEOGRAPHY columns as ``geoarrow.wkb`` additionally + requires the ``geoarrow.wkb`` extension type to be registered. For that + you can install Python bindings for GeoArrow + (`geoarrow-pyarrow <https://geoarrow.org/geoarrow-python/main/index.html#installation>`_) + and import ``geoarrow.pyarrow`` module. Review Comment: 🎉 ! -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
