spark-instrumented-optimizer/docs
Manish Amde 07d72fe696 Decision Tree documentation for MLlib programming guide
Added documentation for user to use the decision tree algorithms for classification and regression in Spark 1.0 release.

Apart from a general review, I need specific input on the following:
* I had to move a lot of the existing documentation under the *linear methods* umbrella to accommodate decision trees. I wonder if there is a better way to organize the programming guide given we are so close to the release.
* I have not looked closely at pyspark but I am wondering new mllib algorithms are automatically plugged in or do we need to some extra work to call mllib functions from pyspark. I will add to the pyspark examples based upon the advice I get.

cc: @mengxr, @hirakendu, @etrain, @atalwalkar

Author: Manish Amde <manish9ue@gmail.com>

Closes #402 from manishamde/tree_doc and squashes the following commits:

022485a [Manish Amde] more documentation
865826e [Manish Amde] minor: grammar
dbb0e5e [Manish Amde] minor improvements to text
b9ef6c4 [Manish Amde] basic decision tree code examples
6e297d7 [Manish Amde] added subsections
f427e84 [Manish Amde] renaming sections
9c0c4be [Manish Amde] split candidate
6925275 [Manish Amde] impurity and information gain
94fd2f9 [Manish Amde] more reorg
b93125c [Manish Amde] more subsection reorg
3ecb2ad [Manish Amde] minor text addition
1537dd3 [Manish Amde] added placeholders and some doc
d06511d [Manish Amde] basic skeleton
2014-04-15 11:14:28 -07:00
..
_layouts SPARK-1251 Support for optimizing and executing structured queries 2014-03-20 18:03:20 -07:00
_plugins SPARK-1374: PySpark API for SparkSQL 2014-04-15 00:07:55 -07:00
css SPARK-1093: Annotate developer and experimental API's 2014-04-09 01:14:46 -07:00
img Merge pull request #497 from tdas/docs-update 2014-01-28 21:51:05 -08:00
js SPARK-1093: Annotate developer and experimental API's 2014-04-09 01:14:46 -07:00
_config.yml Revert "SPARK-1433: Upgrade Mesos dependency to 0.17.0" 2014-04-10 14:43:29 -07:00
api.md Soften wording about GraphX superseding Bagel 2014-01-10 23:48:32 -08:00
bagel-programming-guide.md Removed reference to incubation in Spark user docs. 2014-02-27 21:13:22 -08:00
building-with-maven.md SPARK-1387. Update build plugins, avoid plugin version warning, centralize versions 2014-04-06 17:41:01 -07:00
cluster-overview.md SPARK-1375. Additional spark-submit cleanup 2014-04-04 13:28:42 -07:00
configuration.md SPARK-1202 - Add a "cancel" button in the UI for stages 2014-04-10 17:10:11 -07:00
contributing-to-spark.md Work in progress: 2013-09-08 00:29:11 -07:00
ec2-scripts.md fix persistent-hdfs 2013-11-01 17:47:37 -07:00
graphx-programming-guide.md SPARK-1183. Don't use "worker" to mean executor 2014-03-13 12:11:33 -07:00
hadoop-third-party-distributions.md Code review feedback 2014-01-05 22:05:30 -08:00
hardware-provisioning.md Change port from 3030 to 4040 2013-09-11 10:01:38 -07:00
index.md Some clean up in build/docs 2014-04-11 10:45:27 -07:00
java-programming-guide.md [java8API] SPARK-964 Investigate the potential for using JDK 8 lambda expressions for the Java/Scala APIs 2014-03-03 22:31:30 -08:00
job-scheduling.md SPARK-1183. Don't use "worker" to mean executor 2014-03-13 12:11:33 -07:00
mllib-classification-regression.md Decision Tree documentation for MLlib programming guide 2014-04-15 11:14:28 -07:00
mllib-clustering.md Merge pull request #552 from martinjaggi/master. Closes #552. 2014-02-08 11:39:13 -08:00
mllib-collaborative-filtering.md Merge pull request #552 from martinjaggi/master. Closes #552. 2014-02-08 11:39:13 -08:00
mllib-guide.md Decision Tree documentation for MLlib programming guide 2014-04-15 11:14:28 -07:00
mllib-linear-algebra.md Principal Component Analysis 2014-03-20 10:39:20 -07:00
mllib-optimization.md Merge pull request #566 from martinjaggi/copy-MLlib-d. 2014-02-09 15:19:50 -08:00
monitoring.md [SPARK-1276] Add a HistoryServer to render persisted UI 2014-04-10 10:39:34 -07:00
python-programming-guide.md SPARK-1426: Make MLlib work with NumPy versions older than 1.7 2014-04-15 00:19:43 -07:00
quick-start.md small fix ( proogram -> program ) 2014-04-04 21:32:00 -07:00
README.md SPARK-1374: PySpark API for SparkSQL 2014-04-15 00:07:55 -07:00
running-on-mesos.md Updated docs for SparkConf and handled review comments 2013-12-30 22:17:28 -05:00
running-on-yarn.md SPARK-1376. In the yarn-cluster submitter, rename "args" option to "arg" 2014-04-01 08:26:31 +05:30
scala-programming-guide.md SPARK-1099: Introduce local[*] mode to infer number of cores 2014-04-07 13:06:30 -07:00
security.md SPARK-1189: Add Security to Spark - Akka, Http, ConnectionManager, UI use servlets 2014-03-06 18:27:50 -06:00
spark-debugger.md Removed reference to incubation in Spark user docs. 2014-02-27 21:13:22 -08:00
spark-standalone.md SPARK-1126. spark-app preliminary 2014-03-29 14:41:36 -07:00
sql-programming-guide.md SPARK-1374: PySpark API for SparkSQL 2014-04-15 00:07:55 -07:00
streaming-custom-receivers.md Merge pull request #577 from hsaputra/fix_simple_streaming_doc. 2014-02-11 14:46:22 -08:00
streaming-programming-guide.md maintain arbitrary state data for each key 2014-03-09 22:42:12 -07:00
tuning.md Update tuning.md 2014-04-10 14:59:58 -07:00

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.

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.

The markdown code can be compiled to HTML using the Jekyll tool. To use the jekyll command, you will need to have Jekyll installed. The easiest way to do this is via a Ruby Gem, see the jekyll installation instructions. Compiling the site with Jekyll will create a directory called _site containing index.html as well as the rest of the compiled files.

You can modify the default Jekyll build as follows:

# Skip generating API docs (which takes a while)
$ SKIP_SCALADOC=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

Pygments

We also use pygments (http://pygments.org) for syntax highlighting in documentation markdown pages, so you will also need to install that (it requires Python) by running sudo easy_install Pygments.

To mark a block of code in your markdown to be syntax highlighted by jekyll during the compile phase, use the following sytax:

{% highlight scala %}
// Your scala code goes here, you can replace scala with many other
// supported languages too.
{% endhighlight %}

API Docs (Scaladoc and Epydoc)

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

Similarly, you can build just the PySpark epydoc by running epydoc --config epydoc.conf from the SPARK_PROJECT_ROOT/pyspark directory. Documentation is only generated for classes that are listed as public in __init__.py.

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 sbt/sbt doc 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 using epydoc.

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