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author | Matei Zaharia <matei@eecs.berkeley.edu> | 2012-09-25 19:31:07 -0700 |
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committer | Matei Zaharia <matei@eecs.berkeley.edu> | 2012-09-25 19:31:07 -0700 |
commit | 56c90485fd947d75bbe7aac81593ba42cfe56821 (patch) | |
tree | 99c5bc617a350a408abfa62f612fc14c807ad1e7 /docs/index.md | |
parent | 1821bf1f1f50e5eb1c7adf9d010ecc392b1adad5 (diff) | |
download | spark-56c90485fd947d75bbe7aac81593ba42cfe56821.tar.gz spark-56c90485fd947d75bbe7aac81593ba42cfe56821.tar.bz2 spark-56c90485fd947d75bbe7aac81593ba42cfe56821.zip |
More updates to documentation
Diffstat (limited to 'docs/index.md')
-rw-r--r-- | docs/index.md | 36 |
1 files changed, 20 insertions, 16 deletions
diff --git a/docs/index.md b/docs/index.md index b9d9a8a36f..154ad42d49 100644 --- a/docs/index.md +++ b/docs/index.md @@ -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 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"). +Spark is a MapReduce-like cluster computing framework designed for low-latency iterative jobs and interactive use from an interpreter. It provides clean, language-integrated APIs in Scala and Java, with a rich array of parallel operators. Spark can run on top of the [Apache Mesos](http://incubator.apache.org/mesos/) cluster manager, Hadoop YARN, Amazon EC2, or without an independent resource manager ("standalone mode"). # Downloading @@ -17,7 +17,7 @@ Get Spark by checking out the master branch of the Git repository, using `git cl 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 +to where you've installed Scala. Scala must also be accessible through one 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 @@ -32,9 +32,10 @@ To run one of the samples, use `./run <class> <params>` in the top-level Spark d For example, `./run spark.examples.SparkPi` will run a sample program that estimates Pi. Each of the examples prints usage help if no params are given. -Note that all of the sample programs take a `<host>` parameter that is the Mesos master -to connect to. This can be a [Mesos master URL](http://www.github.com/mesos/mesos/wiki), or `local` to run locally with one -thread, or `local[N]` to run locally with N threads. You should start by using `local` for testing. +Note that all of the sample programs take a `<master>` parameter specifying the cluster URL +to connect to. This can be a [URL for a distributed cluster]({{HOME_PATH}}scala-programming-guide.html#master_urls), +or `local` to run locally with one thread, or `local[N]` to run locally with N threads. You should start by using +`local` for testing. 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. @@ -49,34 +50,37 @@ of `project/SparkBuild.scala`, then rebuilding Spark (`sbt/sbt clean compile`). # Where to Go from Here -Programming guides: +**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: +**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 * [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. +**Other documents:** +* [Configuration]({{HOME_PATH}}configuration.html): customize Spark via its configuration system +* [API docs (Scaladoc)]({{HOME_PATH}}api/core/index.html) * [Bagel]({{HOME_PATH}}bagel-programming-guide.html): an implementation of Google's Pregel on Spark * [Contributing to Spark](contributing-to-spark.html) -# Other Resources - +**External 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, and provide a great introduction to Spark. -* [Paper describing the programming model](http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf) +* [AMP Camp](http://ampcamp.berkeley.edu/): a two-day training camp at UC Berkeley that featured talks and exercises + about Spark, Shark, Mesos, and more. [Videos](http://ampcamp.berkeley.edu/agenda-2012), + [slides](http://ampcamp.berkeley.edu/agenda-2012) and [exercises](http://ampcamp.berkeley.edu/exercises-2012) are + available online for free. * [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 +* [Paper describing the Spark system](http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf) +* [Mailing List](http://groups.google.com/group/spark-users) # Community -To keep up with Spark development or get help, sign up for the [spark-users mailing list](http://groups.google.com/group/spark-users). +To get help using Spark or keep up with Spark development, sign up for the [spark-users mailing list](http://groups.google.com/group/spark-users). If you're in the San Francisco Bay Area, there's a regular [Spark meetup](http://www.meetup.com/spark-users/) every few weeks. Come by to meet the developers and other users. -If you'd like to contribute code to Spark, read [how to contribute]({{HOME_PATH}}contributing-to-spark.html). +Finally, if you'd like to contribute code to Spark, read [how to contribute]({{HOME_PATH}}contributing-to-spark.html). |