ARROW-356: Add documentation about reading Parquet

Change-Id: I1810ccbb021a79f1da1474cc1b952ab98503f010

python/doc/index.rst

@@ -31,14 +31,14 @@ additional functionality such as reading Apache Parquet files into Arrow
 structures.
 
 .. toctree::
-   :maxdepth: 4
-   :hidden:
+   :maxdepth: 2
+   :caption: Getting Started
 
    Module Reference <modules.rst>
 
-Indices and tables
-==================
+.. toctree::
+   :maxdepth: 2
+   :caption: Additional Features
+
+   Parquet format <parquet.rst>
 
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`

python/doc/parquet.rst

@@ -0,0 +1,65 @@
+.. 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.
+
+Reading/Writing Parquet files
+=============================
+
+If you have built ``pyarrow`` with Parquet support, i.e. ``parquet-cpp`` was
+found during the build, you can read files in the Parquet format to/from Arrow
+memory structures. The Parquet support code is located in the
+:mod:`pyarrow.parquet` module.
+
+Reading Parquet
+---------------
+
+To read a Parquet file into Arrow memory, you can use the following code
+snippet. It will read the whole Parquet file into memory as an
+:class:`pyarrow.table.Table`.
+
+.. code-block:: python
+
+    import pyarrow
+    import pyarrow.parquet
+
+    A = pyarrow
+
+    table = A.parquet.read_table('<filename>')
+
+Writing Parquet
+---------------
+
+Given an instance of :class:`pyarrow.table.Table`, the most simple way to
+persist it to Parquet is by using the :meth:`pyarrow.parquet.write_table`
+method.
+
+.. code-block:: python
+
+    import pyarrow
+    import pyarrow.parquet
+
+    A = pyarrow
+
+    table = A.Table(..)
+    A.parquet.write_table(table, '<filename>')
+
+By default this will write the Table as a single RowGroup using ``DICTIONARY``
+encoding. To increase the potential of parallelism a query engine can process
+a Parquet file, set the ``chunk_size`` to a fraction of the total number of rows.
+
+If you also want to compress the columns, you can select a compression
+method using the ``compression`` argument. Typically, ``GZIP`` is the choice if
+you want to minimize size and ``SNAPPY`` for performance.