Skip to content
Snippets Groups Projects
user avatar
Prabeesh K authored
This PR is based on #4229, thanks prabeesh.

Closes #4229

Author: Prabeesh K <prabsmails@gmail.com>
Author: zsxwing <zsxwing@gmail.com>
Author: prabs <prabsmails@gmail.com>
Author: Prabeesh K <prabeesh.k@namshi.com>

Closes #7833 from zsxwing/pr4229 and squashes the following commits:

9570bec [zsxwing] Fix the variable name and check null in finally
4a9c79e [zsxwing] Fix pom.xml indentation
abf5f18 [zsxwing] Merge branch 'master' into pr4229
935615c [zsxwing] Fix the flaky MQTT tests
47278c5 [zsxwing] Include the project class files
478f844 [zsxwing] Add unpack
5f8a1d4 [zsxwing] Make the maven build generate the test jar for Python MQTT tests
734db99 [zsxwing] Merge branch 'master' into pr4229
126608a [Prabeesh K] address the comments
b90b709 [Prabeesh K] Merge pull request #1 from zsxwing/pr4229
d07f454 [zsxwing] Register StreamingListerner before starting StreamingContext; Revert unncessary changes; fix the python unit test
a6747cb [Prabeesh K] wait for starting the receiver before publishing data
87fc677 [Prabeesh K] address the comments:
97244ec [zsxwing] Make sbt build the assembly test jar for streaming mqtt
80474d1 [Prabeesh K] fix
1f0cfe9 [Prabeesh K] python style fix
e1ee016 [Prabeesh K] scala style fix
a5a8f9f [Prabeesh K] added Python test
9767d82 [Prabeesh K] implemented Python-friendly class
a11968b [Prabeesh K] fixed python style
795ec27 [Prabeesh K] address comments
ee387ae [Prabeesh K] Fix assembly jar location of mqtt-assembly
3f4df12 [Prabeesh K] updated version
b34c3c1 [prabs] adress comments
3aa7fff [prabs] Added Python streaming mqtt word count example
b7d42ff [prabs] Mqtt streaming support in Python
853809e9
History

Welcome to the Spark documentation!

This readme will walk you through navigating and building the Spark documentation, which is included here with the Spark source code. You can also find documentation specific to release versions of Spark at http://spark.apache.org/documentation.html.

Read on to learn more about viewing documentation in plain text (i.e., markdown) or building the documentation yourself. Why build it yourself? So that you have the docs that corresponds to whichever version of Spark you currently have checked out of revision control.

Prerequisites

The Spark documentation build uses a number of tools to build HTML docs and API docs in Scala, Python and R. To get started you can run the following commands

$ sudo gem install jekyll
$ sudo gem install jekyll-redirect-from
$ sudo pip install Pygments
$ sudo pip install sphinx
$ Rscript -e 'install.packages(c("knitr", "devtools"), repos="http://cran.stat.ucla.edu/")'

Generating the Documentation HTML

We include the Spark documentation as part of the source (as opposed to using a hosted wiki, such as the github wiki, as the definitive documentation) to enable the documentation to evolve along with the source code and be captured by revision control (currently git). This way the code automatically includes the version of the documentation that is relevant regardless of which version or release you have checked out or downloaded.

In this directory you will find textfiles formatted using Markdown, with an ".md" suffix. You can read those text files directly if you want. Start with index.md.

Execute jekyll build from the docs/ directory to compile the site. Compiling the site with Jekyll will create a directory called _site containing index.html as well as the rest of the compiled files.

$ cd docs
$ jekyll build

You can modify the default Jekyll build as follows:

# Skip generating API docs (which takes a while)
$ SKIP_API=1 jekyll build
# Serve content locally on port 4000
$ jekyll serve --watch
# Build the site with extra features used on the live page
$ PRODUCTION=1 jekyll build

API Docs (Scaladoc, Sphinx, roxygen2)

You can build just the Spark scaladoc by running build/sbt unidoc from the SPARK_PROJECT_ROOT directory.

Similarly, you can build just the PySpark docs by running make html from the SPARK_PROJECT_ROOT/python/docs directory. Documentation is only generated for classes that are listed as public in __init__.py. The SparkR docs can be built by running SPARK_PROJECT_ROOT/R/create-docs.sh.

When you run jekyll in the docs directory, it will also copy over the scaladoc for the various Spark subprojects into the docs directory (and then also into the _site directory). We use a jekyll plugin to run build/sbt unidoc before building the site so if you haven't run it (recently) it may take some time as it generates all of the scaladoc. The jekyll plugin also generates the PySpark docs Sphinx.

NOTE: To skip the step of building and copying over the Scala, Python, R API docs, run SKIP_API=1 jekyll.