657a88835d
Major changes: * Added programming guide sections for tree ensembles * Added examples for tree ensembles * Updated DecisionTree programming guide with more info on parameters * **API change**: Standardized the tree parameter for the number of classes (for classification) Minor changes: * Updated decision tree documentation * Updated existing tree and tree ensemble examples * Use train/test split, and compute test error instead of training error. * Fixed decision_tree_runner.py to actually use the number of classes it computes from data. (small bug fix) Note: I know this is a lot of lines, but most is covered by: * Programming guide sections for gradient boosting and random forests. (The changes are probably best viewed by generating the docs locally.) * New examples (which were copied from the programming guide) * The "numClasses" renaming I have run all examples and relevant unit tests. CC: mengxr manishamde codedeft Author: Joseph K. Bradley <joseph@databricks.com> Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com> Closes #3461 from jkbradley/ensemble-docs and squashes the following commits: 70a75f3 [Joseph K. Bradley] updated forest vs boosting comparison d1de753 [Joseph K. Bradley] Added note about toString and toDebugString for DecisionTree to migration guide 8e87f8f [Joseph K. Bradley] Combined GBT and RandomForest guides into one ensembles guide 6fab846 [Joseph K. Bradley] small fixes based on review b9f8576 [Joseph K. Bradley] updated decision tree doc 375204c [Joseph K. Bradley] fixed python style 2b60b6e [Joseph K. Bradley] merged Java RandomForest examples into 1 file. added header. Fixed small bug in same example in the programming guide. 706d332 [Joseph K. Bradley] updated python DT runner to print full model if it is small c76c823 [Joseph K. Bradley] added migration guide for mllib abe5ed7 [Joseph K. Bradley] added examples for random forest in Java and Python to examples folder 07fc11d [Joseph K. Bradley] Renamed numClassesForClassification to numClasses everywhere in trees and ensembles. This is a breaking API change, but it was necessary to correct an API inconsistency in Spark 1.1 (where Python DecisionTree used numClasses but Scala used numClassesForClassification). cdfdfbc [Joseph K. Bradley] added examples for GBT 6372a2b [Joseph K. Bradley] updated decision tree examples to use random split. tested all of them. ad3e695 [Joseph K. Bradley] added gbt and random forest to programming guide. still need to update their examples |
||
---|---|---|
.. | ||
_layouts | ||
_plugins | ||
css | ||
img | ||
js | ||
_config.yml | ||
api.md | ||
bagel-programming-guide.md | ||
building-spark.md | ||
cluster-overview.md | ||
configuration.md | ||
contributing-to-spark.md | ||
ec2-scripts.md | ||
graphx-programming-guide.md | ||
hadoop-third-party-distributions.md | ||
hardware-provisioning.md | ||
index.md | ||
java-programming-guide.md | ||
job-scheduling.md | ||
mllib-classification-regression.md | ||
mllib-clustering.md | ||
mllib-collaborative-filtering.md | ||
mllib-data-types.md | ||
mllib-decision-tree.md | ||
mllib-dimensionality-reduction.md | ||
mllib-ensembles.md | ||
mllib-feature-extraction.md | ||
mllib-guide.md | ||
mllib-linear-methods.md | ||
mllib-naive-bayes.md | ||
mllib-optimization.md | ||
mllib-statistics.md | ||
monitoring.md | ||
programming-guide.md | ||
python-programming-guide.md | ||
quick-start.md | ||
README.md | ||
running-on-mesos.md | ||
running-on-yarn.md | ||
scala-programming-guide.md | ||
security.md | ||
spark-standalone.md | ||
sql-programming-guide.md | ||
storage-openstack-swift.md | ||
streaming-custom-receivers.md | ||
streaming-flume-integration.md | ||
streaming-kafka-integration.md | ||
streaming-kinesis-integration.md | ||
streaming-programming-guide.md | ||
submitting-applications.md | ||
tuning.md |
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.
Jekyll
and a few dependencies must be installed for this to work. We recommend
installing via the Ruby Gem dependency manager. Since the exact HTML output
varies between versions of Jekyll and its dependencies, we list specific versions here
in some cases:
$ sudo gem install jekyll
$ sudo gem install jekyll-redirect-from
Execute jekyll
from the docs/
directory. 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_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
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 pip 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 %}
Sphinx
We use Sphinx to generate Python API docs, so you will need to install it by running
sudo pip install sphinx
.
API Docs (Scaladoc and Sphinx)
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 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
.
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 Sphinx.
NOTE: To skip the step of building and copying over the Scala and Python API docs, run SKIP_API=1 jekyll
.