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 https://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 correspond to whichever version of Spark you currently have checked out of revision control.
The Spark documentation build uses a number of tools to build HTML docs and API docs in Scala, Java, Python, R and SQL.
$ sudo gem install jekyll jekyll-redirect-from rouge # Following is needed only for generating API docs $ sudo pip install sphinx pypandoc mkdocs $ sudo Rscript -e 'install.packages(c("knitr", "devtools", "rmarkdown"), repos="https://cloud.r-project.org/")' $ sudo Rscript -e 'devtools::install_version("roxygen2", version = "5.0.1", repos="https://cloud.r-project.org/")' $ sudo Rscript -e 'devtools::install_version("testthat", version = "1.0.2", repos="https://cloud.r-project.org/")'
Note: If you are on a system with both Ruby 1.9 and Ruby 2.0 you may need to replace gem with gem2.0.
Note: Other versions of roxygen2 might work in SparkR documentation generation but
RoxygenNote field in
$SPARK_HOME/R/pkg/DESCRIPTION is 5.0.1, which is updated if the version is mismatched.
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 text files formatted using Markdown, with an ".md" suffix. You can read those text files directly if you want. Start with
jekyll build from the
docs/ directory to compile the site. Compiling the site with Jekyll will create a directory called
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
You can build just the Spark scaladoc and javadoc by running
./build/sbt unidoc from the
Similarly, you can build just the PySpark docs by running
make html from the
$SPARK_HOME/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_HOME/R/create-docs.sh, and the SQL docs can be built by running
$SPARK_HOME/sql/create-docs.sh after building Spark first.
When you run
jekyll build in the
docs directory, it will also copy over the scaladoc and javadoc for the various Spark subprojects into the
docs directory (and then also into the
_site directory). We use a jekyll plugin to run
./build/sbt unidoc before building the site so if you haven't run it (recently) it may take some time as it generates all of the scaladoc and javadoc using Unidoc. The jekyll plugin also generates the PySpark docs using Sphinx, SparkR docs using roxygen2 and SQL docs using MkDocs.
NOTE: To skip the step of building and copying over the Scala, Java, Python, R and SQL API docs, run
SKIP_API=1 jekyll build. In addition,
SKIP_SQLDOC=1 can be used to skip a single step of the corresponding language.
SKIP_SCALADOC indicates skipping both the Scala and Java docs.
jekyll serve --watch will only watch what's in
docs/, and it won't follow symlinks. That means it won't monitor your API docs under
python/docs or elsewhere.
To work around this limitation for Python, install
entr and run the following in a separate shell:
cd "$SPARK_HOME/python/docs" find .. -type f -name '*.py' \ | entr -s 'make html && cp -r _build/html/. ../../docs/api/python'
Whenever there is a change to your Python code,
entr will automatically rebuild the Python API docs and copy them to
docs/, thus triggering a Jekyll update.