[GitHub] [spark] zero323 commented on a change in pull request #34315: [SPARK-37050][PYTHON] Update Conda installation instructions

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zero323 commented on a change in pull request #34315:
URL: https://github.com/apache/spark/pull/34315#discussion_r731723248



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File path: python/docs/source/getting_started/install.rst
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@@ -83,46 +83,54 @@ Note that this installation way of PySpark with/without a specific Hadoop versio
 Using Conda
 -----------
 
-Conda is an open-source package management and environment management system which is a part of
-the `Anaconda <https://docs.continuum.io/anaconda/>`_ distribution. It is both cross-platform and
-language agnostic. In practice, Conda can replace both `pip <https://pip.pypa.io/en/latest/>`_ and
-`virtualenv <https://virtualenv.pypa.io/en/latest/>`_.
-
-Create new virtual environment from your 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:
+Conda is an open-source package management and environment management system (developed by
+`Anaconda <https://www.anaconda.com/>`_), which is best installed through
+`Miniconda <https://docs.conda.io/en/latest/miniconda.html/>`_ or `Miniforge <https://github.com/conda-forge/miniforge/>`_.
+The tool is both cross-platform and language agnostic, and in practice, conda can replace both
+`pip <https://pip.pypa.io/en/latest/>`_ and `virtualenv <https://virtualenv.pypa.io/en/latest/>`_.
+
+Conda uses so-called channels to distribute packages, and together with the default channels by
+Anaconda itself, the most important channel is `conda-forge <https://conda-forge.org/>`_, which
+is the community-driven packaging effort that is the most extensive & the most current (and also
+serves as the upstream for the Anaconda channels in most cases).
+
+Generally, it is recommended to use *as few channels as possible*. Conda-forge & Anaconda put a
+lot of effort in guaranteeing binary compatibility between packages (e.g. by using compatible
+compilers for all packages and tracking which packages are ABI-relevant). Needlessly mixing in
+other channels can end up breaking those guarantees, which is why conda-forge even recommends
+so-called "strict channel priority":
 
 .. code-block:: bash
 
-    conda env list
+    conda config --add channels conda-forge
+    conda config --set channel_priority strict
 
-Now activate the newly created environment with the following command:
+To create a new conda environment from your terminal and activate it, proceed as shown below:
 
 .. code-block:: bash
 
+    conda create -n pyspark_env
     conda activate pyspark_env
 
-You can install pyspark by `Using PyPI <#using-pypi>`_ to install PySpark in the newly created
-environment, for example as below. It will install PySpark under the new virtual environment
-``pyspark_env`` created above.
+After activating the environment, use the following command to install pyspark,
+a python version of your choice, as well as other packages you want to use in
+the same session as pyspark (you can install in several steps too).
 
 .. code-block:: bash
 
-    pip install pyspark
+    conda install -c conda-forge pyspark python [other packages]  # can also use python=3.8, etc.

Review comment:
       Could we just link to [Using Pip in a Conda Environment](https://www.anaconda.com/blog/using-pip-in-a-conda-environment)?




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