HyukjinKwon commented on a change in pull request #29410: URL: https://github.com/apache/spark/pull/29410#discussion_r472899455
########## File path: python/docs/source/getting_started/installation.rst ########## @@ -0,0 +1,84 @@ +.. 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 +============ + +Using PyPI +~~~~~~~~~~ +PySpark installation using `PyPI <https://pypi.org/project/pyspark/>`_:: + + pip install pyspark + +Using Miniconda +~~~~~~~~~~~~~~~ +Pyspark is available in Conda but it is not a part of an official release. Conda can be used to create a virtual environment from terminal as shown below:: + + conda create -n ENV_NAME python==PYTHON_VERSION + +After the virtual environment is created, it should be visible under the list of conda environments which can be seen using the following command:: + + conda env list + +The newly created environment can be accessed using the following command:: + + source activate ENV_NAME + +On Windows, the command is:: + + conda activate ENV_NAME + +PySpark can be installed in this newly created environment using PyPI as shown before:: + + pip install pyspark + +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:: + + 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 ``$SPARK_HOME/python/lib``, one example of doing this is shown below:: + + cd spark-3.0.0-bin-hadoop2.7 + + export SPARK_HOME=`pwd` + + export PYTHONPATH=$(ZIPS=("$SPARK_HOME"/python/lib/*.zip); IFS=:; echo "${ZIPS[*]}"):$PYTHONPATH + +Installing from source +~~~~~~~~~~~~~~~~~~~~~~ + +To install PySpark from source, refer `Building Spark <https://spark.apache.org/docs/latest/building-spark.html>`__. + +* Steps for defining ``PYTHONPATH`` is same as described in `Official release channel` section above. + + +Dependencies +------------ +============= ========================= +Package Minimum supported version +============= ========================= +`pandas` 0.23.2 +`NumPy` 1.7 +`pyarrow` 0.15.1 +`Py4J` 0.10.9 Review comment: Let's add another column to describe what is required and what is optional. `pandas` and `pyarrow` is optional for SQL related features. NumPy is required to use it in ML. `Py4J` is required to run PySpark. ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
