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Tucker Beck authored
## Problem Description

When pyspark is listed as a dependency of another package, installing
the other package will cause an install failure in pyspark. When the
other package is being installed, pyspark's setup_requires requirements
are installed including pypandoc. Thus, the exception handling on
setup.py:152 does not work because the pypandoc module is indeed
available. However, the pypandoc.convert() function fails if pandoc
itself is not installed (in our use cases it is not). This raises an
OSError that is not handled, and setup fails.

The following is a sample failure:
```
$ which pandoc
$ pip freeze | grep pypandoc
pypandoc==1.4
$ pip install pyspark
Collecting pyspark
  Downloading pyspark-2.2.0.post0.tar.gz (188.3MB)
    100% |████████████████████████████████| 188.3MB 16.8MB/s
    Complete output from command python setup.py egg_info:
    Maybe try:

        sudo apt-get install pandoc
    See http://johnmacfarlane.net/pandoc/installing.html
    for installation options
    ---------------------------------------------------------------

    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "/tmp/pip-build-mfnizcwa/pyspark/setup.py", line 151, in <module>
        long_description = pypandoc.convert('README.md', 'rst')
      File "/home/tbeck/.virtualenvs/cem/lib/python3.5/site-packages/pypandoc/__init__.py", line 69, in convert
        outputfile=outputfile, filters=filters)
      File "/home/tbeck/.virtualenvs/cem/lib/python3.5/site-packages/pypandoc/__init__.py", line 260, in _convert_input
        _ensure_pandoc_path()
      File "/home/tbeck/.virtualenvs/cem/lib/python3.5/site-packages/pypandoc/__init__.py", line 544, in _ensure_pandoc_path
        raise OSError("No pandoc was found: either install pandoc and add it\n"
    OSError: No pandoc was found: either install pandoc and add it
    to your PATH or or call pypandoc.download_pandoc(...) or
    install pypandoc wheels with included pandoc.

    ----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-build-mfnizcwa/pyspark/
```

## What changes were proposed in this pull request?

This change simply adds an additional exception handler for the OSError
that is raised. This allows pyspark to be installed client-side without requiring pandoc to be installed.

## How was this patch tested?

I tested this by building a wheel package of pyspark with the change applied. Then, in a clean virtual environment with pypandoc installed but pandoc not available on the system, I installed pyspark from the wheel.

Here is the output

```
$ pip freeze | grep pypandoc
pypandoc==1.4
$ which pandoc
$ pip install --no-cache-dir ../spark/python/dist/pyspark-2.3.0.dev0-py2.py3-none-any.whl
Processing /home/tbeck/work/spark/python/dist/pyspark-2.3.0.dev0-py2.py3-none-any.whl
Requirement already satisfied: py4j==0.10.6 in /home/tbeck/.virtualenvs/cem/lib/python3.5/site-packages (from pyspark==2.3.0.dev0)
Installing collected packages: pyspark
Successfully installed pyspark-2.3.0.dev0
```

Author: Tucker Beck <tucker.beck@rentrakmail.com>

Closes #18981 from dusktreader/dusktreader/fix-pandoc-dependency-issue-in-setup_py.
aad21254
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Apache Spark

Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.

http://spark.apache.org/

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the project web page

Python Packaging

This README file only contains basic information related to pip installed PySpark. This packaging is currently experimental and may change in future versions (although we will do our best to keep compatibility). Using PySpark requires the Spark JARs, and if you are building this from source please see the builder instructions at "Building Spark".

The Python packaging for Spark is not intended to replace all of the other use cases. This Python packaged version of Spark is suitable for interacting with an existing cluster (be it Spark standalone, YARN, or Mesos) - but does not contain the tools required to setup your own standalone Spark cluster. You can download the full version of Spark from the Apache Spark downloads page.

NOTE: If you are using this with a Spark standalone cluster you must ensure that the version (including minor version) matches or you may experience odd errors.

Python Requirements

At its core PySpark depends on Py4J (currently version 0.10.6), but additional sub-packages have their own requirements (including numpy and pandas).