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This commit is contained in:
Matei Zaharia 2012-09-25 15:46:18 -07:00
parent 30362a21e7
commit e47e11720f
4 changed files with 103 additions and 91 deletions
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38
docs/_plugins/copy_api_dirs.rb
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@ -1,28 +1,30 @@
require 'fileutils'
include FileUtils
projects = ["core", "examples", "repl", "bagel"]
if ENV['SKIP_SCALADOC'] != '1'
projects = ["core", "examples", "repl", "bagel"]
puts "Moving to project root and building scaladoc."
curr_dir = pwd
cd("..")
puts "Moving to project root and building scaladoc."
curr_dir = pwd
cd("..")
puts "Running sbt/sbt doc from " + pwd + "; this may take a few minutes..."
puts `sbt/sbt doc`
puts "Running sbt/sbt doc from " + pwd + "; this may take a few minutes..."
puts `sbt/sbt doc`
puts "moving back into docs dir."
cd("docs")
puts "moving back into docs dir."
cd("docs")
# Copy over the scaladoc from each project into the docs directory.
# This directory will be copied over to _site when `jekyll` command is run.
projects.each do |project_name|
source = "../" + project_name + "/target/scala-2.9.2/api"
dest = "api/" + project_name
# Copy over the scaladoc from each project into the docs directory.
# This directory will be copied over to _site when `jekyll` command is run.
projects.each do |project_name|
source = "../" + project_name + "/target/scala-2.9.2/api"
dest = "api/" + project_name
puts "echo making directory " + dest
mkdir_p dest
puts "echo making directory " + dest
mkdir_p dest
# From the rubydoc: cp_r('src', 'dest') makes src/dest, but this doesn't.
puts "cp -r " + source + "/. " + dest
cp_r(source + "/.", dest)
# From the rubydoc: cp_r('src', 'dest') makes src/dest, but this doesn't.
puts "cp -r " + source + "/. " + dest
cp_r(source + "/.", dest)
end
end

15
docs/css/main.css
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@ -10,8 +10,9 @@
}
.navbar-inner {
padding-top: 5px;
padding-bottom: 5px;
padding-top: 6px;
padding-bottom: 6px;
font-size: 15px;
}
body #content {
@ -35,7 +36,15 @@ h3 {
}
code {
color: #333;
font-family: "Menlo", "Lucida Console", monospace;
background: white;
border: none;
padding: 0;
color: #902000;
}
pre {
font-family: "Menlo", "Lucida Console", monospace;
}
.container {

100
docs/css/pygments-default.css
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@ -11,66 +11,66 @@ Also, I was thrown off for a while at first when I was using markdown
code block inside my {% highlight scala %} ... {% endhighlight %} tags
(I was using 4 spaces for this), when it turns out that pygments will
insert the code (or pre?) tags for you.
*/
.hll { background-color: #ffffcc }
.c { color: #408080; font-style: italic } /* Comment */
.err { border: 1px solid #FF0000 } /* Error */
.k { color: #008000; font-weight: bold } /* Keyword */
.c { color: #60a0b0; font-style: italic } /* Comment */
.err { } /* Error */
.k { color: #007020; font-weight: bold } /* Keyword */
.o { color: #666666 } /* Operator */
.cm { color: #408080; font-style: italic } /* Comment.Multiline */
.cp { color: #BC7A00 } /* Comment.Preproc */
.c1 { color: #408080; font-style: italic } /* Comment.Single */
.cs { color: #408080; font-style: italic } /* Comment.Special */
.cm { color: #60a0b0; font-style: italic } /* Comment.Multiline */
.cp { color: #007020 } /* Comment.Preproc */
.c1 { color: #60a0b0; font-style: italic } /* Comment.Single */
.cs { color: #60a0b0; background-color: #fff0f0 } /* Comment.Special */
.gd { color: #A00000 } /* Generic.Deleted */
.ge { font-style: italic } /* Generic.Emph */
.gr { color: #FF0000 } /* Generic.Error */
.gh { color: #000080; font-weight: bold } /* Generic.Heading */
.gi { color: #00A000 } /* Generic.Inserted */
.go { color: #808080 } /* Generic.Output */
.gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.gp { color: #c65d09; font-weight: bold } /* Generic.Prompt */
.gs { font-weight: bold } /* Generic.Strong */
.gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.gt { color: #0040D0 } /* Generic.Traceback */
.kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.kp { color: #008000 } /* Keyword.Pseudo */
.kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.kt { color: #B00040 } /* Keyword.Type */
.m { color: #666666 } /* Literal.Number */
.s { color: #BA2121 } /* Literal.String */
.na { color: #7D9029 } /* Name.Attribute */
.nb { color: #008000 } /* Name.Builtin */
.nc { color: #0000FF; font-weight: bold } /* Name.Class */
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.ni { color: #999999; font-weight: bold } /* Name.Entity */
.ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.nf { color: #0000FF } /* Name.Function */
.nl { color: #A0A000 } /* Name.Label */
.nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.nt { color: #008000; font-weight: bold } /* Name.Tag */
.nv { color: #19177C } /* Name.Variable */
.ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.kc { color: #007020; font-weight: bold } /* Keyword.Constant */
.kd { color: #007020; font-weight: bold } /* Keyword.Declaration */
.kn { color: #007020; font-weight: bold } /* Keyword.Namespace */
.kp { color: #007020 } /* Keyword.Pseudo */
.kr { color: #007020; font-weight: bold } /* Keyword.Reserved */
.kt { color: #902000 } /* Keyword.Type */
.m { color: #40a070 } /* Literal.Number */
.s { color: #4070a0 } /* Literal.String */
.na { color: #4070a0 } /* Name.Attribute */
.nb { color: #007020 } /* Name.Builtin */
.nc { color: #0e84b5; font-weight: bold } /* Name.Class */
.no { color: #60add5 } /* Name.Constant */
.nd { color: #555555; font-weight: bold } /* Name.Decorator */
.ni { color: #d55537; font-weight: bold } /* Name.Entity */
.ne { color: #007020 } /* Name.Exception */
.nf { color: #06287e } /* Name.Function */
.nl { color: #002070; font-weight: bold } /* Name.Label */
.nn { color: #0e84b5; font-weight: bold } /* Name.Namespace */
.nt { color: #062873; font-weight: bold } /* Name.Tag */
.nv { color: #bb60d5 } /* Name.Variable */
.ow { color: #007020; font-weight: bold } /* Operator.Word */
.w { color: #bbbbbb } /* Text.Whitespace */
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41
docs/index.md
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@ -7,7 +7,7 @@ title: Spark Overview
TODO(andyk): Rewrite to make the Java API a first class part of the story.
{% endcomment %}
Spark is a MapReduce-like cluster computing framework designed to support low-latency iterative jobs and interactive use from an interpreter. It is written in [Scala](http://www.scala-lang.org), a high-level language for the JVM, and exposes a clean language-integrated syntax that makes it easy to write parallel jobs. Spark runs on top of the [Apache Mesos](http://incubator.apache.org/mesos/) cluster manager, Hadoop YARN, or without an independent resource manager (i.e., in "standalone mode").
Spark is a MapReduce-like cluster computing framework designed to support low-latency iterative jobs and interactive use from an interpreter. It exposes clean language-integrated APIs in [Scala](http://www.scala-lang.org) and Java, providing a wide array of parallel operations. Spark can run on top of the [Apache Mesos](http://incubator.apache.org/mesos/) cluster manager, Hadoop YARN, or without an independent resource manager ("standalone mode").
# Downloading
@ -15,19 +15,14 @@ Get Spark by checking out the master branch of the Git repository, using `git cl
# Building
Spark requires [Scala 2.9](http://www.scala-lang.org/).
In addition, to run Spark on a cluster, you will need to install [Mesos](http://incubator.apache.org/mesos/), using the steps in
[Running Spark on Mesos]({{HOME_PATH}}running-on-mesos.html). However, if you just want to run Spark on a single machine (possibly using multiple cores),
you do not need Mesos.
To build and run Spark, you will need to have Scala's `bin` directory in your `PATH`,
Spark requires [Scala 2.9.2](http://www.scala-lang.org/). You will need to have Scala's `bin` directory in your `PATH`,
or you will need to set the `SCALA_HOME` environment variable to point
to where you've installed Scala. Scala must be accessible through one
of these methods on Mesos slave nodes as well as on the master.
of these methods on slave nodes on your cluster.
Spark uses [Simple Build Tool](https://github.com/harrah/xsbt/wiki), which is bundled with it. To compile the code, go into the top-level Spark directory and run
sbt/sbt compile
sbt/sbt package
# Testing the Build
@ -44,7 +39,7 @@ thread, or `local[N]` to run locally with N threads. You should start by using `
Finally, Spark can be used interactively from a modified version of the Scala interpreter that you can start through
`./spark-shell`. This is a great way to learn Spark.
# A Note About Hadoop
# A Note About Hadoop Versions
Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported
storage systems. Because the HDFS protocol has changed in different versions of
@ -54,23 +49,29 @@ of `project/SparkBuild.scala`, then rebuilding Spark (`sbt/sbt clean compile`).
# Where to Go from Here
* [Spark Programming Guide]({{HOME_PATH}}scala-programming-guide.html): how to get started using Spark, and details on the API
Programming guides:
* [Spark Programming Guide]({{HOME_PATH}}scala-programming-guide.html): how to get started using Spark, and details on the Scala API
* [Java Programming Guide]({{HOME_PATH}}java-programming-guide.html): using Spark from Java
Deployment guides:
* [Running Spark on Amazon EC2]({{HOME_PATH}}ec2-scripts.html): scripts that let you launch a cluster on EC2 in about 5 minutes
* [Running Spark on Mesos]({{HOME_PATH}}running-on-mesos.html): instructions on how to deploy to a private cluster
* [Running Spark on YARN]({{HOME_PATH}}running-on-yarn.html): instructions on how to run Spark on top of a YARN cluster
* [Spark Standalone Mode]({{HOME_PATH}}spark-standalone.html): instructions on running Spark without Mesos
* [Configuration]({{HOME_PATH}}configuration.html): How to set up and customize Spark via its configuration system.
* [Bagel Programming Guide]({{HOME_PATH}}bagel-programming-guide.html): implementation of Google's Pregel on Spark
* [Spark Debugger]({{HOME_PATH}}spark-debugger.html): experimental work on a debugger for Spark jobs
* [Standalone Deploy Mode]({{HOME_PATH}}spark-standalone.html): launch a standalone cluster quickly without Mesos
* [Running Spark on Mesos]({{HOME_PATH}}running-on-mesos.html): deploy a private cluster using
[Apache Mesos](http://incubator.apache.org/mesos)
* [Running Spark on YARN]({{HOME_PATH}}running-on-yarn.html): deploy Spark on top of Hadoop NextGen (YARN)
Miscellaneous:
* [Configuration]({{HOME_PATH}}configuration.html): customize Spark via its configuration system.
* [Bagel]({{HOME_PATH}}bagel-programming-guide.html): an implementation of Google's Pregel on Spark
* [Contributing to Spark](contributing-to-spark.html)
# Other Resources
* [Spark Homepage](http://www.spark-project.org)
* [AMP Camp](http://ampcamp.berkeley.edu/) - In 2012, the AMP Lab hosted the first AMP Camp which featured talks and hands-on exercises about Spark, Shark, Mesos, and more. [Videos, slides](http://ampcamp.berkeley.edu/agenda) and the [exercises](http://ampcamp.berkeley.edu/exercises) are all available online now. Going through the videos and exercises is a great way to sharpen your Spark skills.
* [AMP Camp](http://ampcamp.berkeley.edu/) - In 2012, the AMP Lab hosted the first AMP Camp which featured talks and hands-on exercises about Spark, Shark, Mesos, and more. [Videos, slides](http://ampcamp.berkeley.edu/agenda) and the [exercises](http://ampcamp.berkeley.edu/exercises) are all available online, and provide a great introduction to Spark.
* [Paper describing the programming model](http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf)
* [Code Examples](http://spark-project.org/examples.html) (more also available in the [examples subfolder](https://github.com/mesos/spark/tree/master/examples/src/main/scala/spark/examples) of the Spark codebase)
* [Mailing List](http://groups.google.com/group/spark-users)
* [Code Examples](http://spark-project.org/examples.html): more are also available in the [examples subfolder](https://github.com/mesos/spark/tree/master/examples/src/main/scala/spark/examples) of Spark
* [Mailing List](http://groups.google.com/group/spark-users): ask here for help
# Community