spark-instrumented-optimizer/docs
Evan Chan 1440154c27 SPARK-1154: Clean up app folders in worker nodes
This is a fix for [SPARK-1154](https://issues.apache.org/jira/browse/SPARK-1154).   The issue is that worker nodes fill up with a huge number of app-* folders after some time.  This change adds a periodic cleanup task which asynchronously deletes app directories older than a configurable TTL.

Two new configuration parameters have been introduced:
  spark.worker.cleanup_interval
  spark.worker.app_data_ttl

This change does not include moving the downloads of application jars to a location outside of the work directory.  We will address that if we have time, but that potentially involves caching so it will come either as part of this PR or a separate PR.

Author: Evan Chan <ev@ooyala.com>
Author: Kelvin Chu <kelvinkwchu@yahoo.com>

Closes #288 from velvia/SPARK-1154-cleanup-app-folders and squashes the following commits:

0689995 [Evan Chan] CR from @aarondav - move config, clarify for standalone mode
9f10d96 [Evan Chan] CR from @pwendell - rename configs and add cleanup.enabled
f2f6027 [Evan Chan] CR from @andrewor14
553d8c2 [Kelvin Chu] change the variable name to currentTimeMillis since it actually tracks in seconds
8dc9cb5 [Kelvin Chu] Fixed a bug in Utils.findOldFiles() after merge.
cb52f2b [Kelvin Chu] Change the name of findOldestFiles() to findOldFiles()
72f7d2d [Kelvin Chu] Fix a bug of Utils.findOldestFiles(). file.lastModified is returned in milliseconds.
ad99955 [Kelvin Chu] Add unit test for Utils.findOldestFiles()
dc1a311 [Evan Chan] Don't recompute current time with every new file
e3c408e [Evan Chan] Document the two new settings
b92752b [Evan Chan] SPARK-1154: Add a periodic task to clean up app directories
2014-04-06 19:21:40 -07:00
..
_layouts SPARK-1251 Support for optimizing and executing structured queries 2014-03-20 18:03:20 -07:00
_plugins SPARK-1251 Support for optimizing and executing structured queries 2014-03-20 18:03:20 -07:00
css Merge pull request #552 from martinjaggi/master. Closes #552. 2014-02-08 11:39:13 -08:00
img Merge pull request #497 from tdas/docs-update 2014-01-28 21:51:05 -08:00
js SPARK-1135: fix broken anchors in docs 2014-02-26 11:20:16 -08:00
_config.yml [SPARK-1342] Scala 2.10.4 2014-04-01 18:35:50 -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-1154: Clean up app folders in worker nodes 2014-04-06 19:21:40 -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 SPARK-1251 Support for optimizing and executing structured queries 2014-03-20 18:03:20 -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 SPARK-1183. Don't use "worker" to mean executor 2014-03-13 12:11:33 -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 SPARK-1421. Make MLlib work on Python 2.6 2014-04-05 20:52:05 -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-1167: Remove metrics-ganglia from default build due to LGPL issues... 2014-03-11 11:16:59 -07:00
python-programming-guide.md SPARK-1421. Make MLlib work on Python 2.6 2014-04-05 20:52:05 -07:00
quick-start.md small fix ( proogram -> program ) 2014-04-04 21:32:00 -07:00
README.md Add Jekyll tag to isolate "production-only" doc components. 2014-03-02 18:19:01 -08:00
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-1305: Support persisting RDD's directly to Tachyon 2014-04-04 20:38:20 -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-1314: Use SPARK_HIVE to determine if we include Hive in packaging 2014-04-06 17:48:41 -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 SPARK-929: Fully deprecate usage of SPARK_MEM 2014-03-09 11:08:39 -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.

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.