[GitHub] [spark] HyukjinKwon commented on a change in pull request #29410: [SPARK-32180][PYTHON][DOCS] Installation page in Getting Started in PySpark documentation

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HyukjinKwon commented on a change in pull request #29410:
URL: https://github.com/apache/spark/pull/29410#discussion_r482721489



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File path: python/docs/source/getting_started/installation.rst
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+..  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.
+
+============
+Installation
+============
+
+The official release channel is to download it from https://spark.apache.org/downloads.html but we can install it via ``pip`` as well from PyPI. PyPI installation is usually to use standalone locally or as a client to connect to a cluster. 
+ 
+Instruction for downloading PySpark using PyPI, Conda, Official Release Channel and Source are available in this document.
+
+Python Version Supported
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+Python 3.6, 3.7 and 3.8
+
+Using PyPI
+~~~~~~~~~~
+
+PySpark installation using `PyPI <https://pypi.org/project/pyspark/>`_
+
+.. code-block:: bash
+
+    pip install pyspark
+	
+Using Conda  
+~~~~~~~~~~~
+
+Conda is an open-source package management and environment management system which is a part of `Anaconda <https://docs.continuum.io/anaconda/>`_ distribution. It is both cross-platform and language agnostic.
+  
+Conda can be used to create a virtual environment from terminal as shown below:
+
+.. code-block:: bash
+
+	conda create -n pyspark_env 
+
+After the virtual environment is created, it should be visible under the list of conda environments which can be seen using the following command:
+
+.. code-block:: bash
+
+	conda env list
+
+The newly created environment can be accessed using the following command:
+
+.. code-block:: bash
+
+	conda activate pyspark_env
+
+In lower Conda version, the following command might be used:
+
+.. code-block:: bash
+
+	source activate pyspark_env
+
+PySpark installation using ``pip`` under Conda environment is official. 
+
+PySpark can be installed in this newly created environment using PyPI as shown before:
+
+
+.. code-block:: bash
+
+	pip install pyspark
+
+`PySpark at Conda <https://anaconda.org/conda-forge/pyspark>`__ is not the official release.
+
+Official Release Channel
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+Different flavor of PySpark is available in `the official release channel <https://spark.apache.org/downloads.html>`__.
+Any suitable version can be downloaded and extracted as below:
+
+.. code-block:: bash
+
+    tar xzvf spark-3.0.0-bin-hadoop2.7.tgz
+
+An important step is to ensure ``SPARK_HOME`` environment variable points to the directory where the code has been extracted. 
+The next step is to properly define ``PYTHONPATH`` such that it can find the PySpark and 
+Py4J under ``$SPARK_HOME/python/lib``, one example of doing this is shown below:
+
+.. code-block:: bash
+
+    cd spark-3.0.0-bin-hadoop2.7
+

Review comment:
       Let's remove empty newlines here.




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