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diff --git a/docs/index.md b/docs/index.md index 0c4add45dc..3cf9cc1c64 100644 --- a/docs/index.md +++ b/docs/index.md @@ -3,50 +3,52 @@ layout: global title: Spark Overview --- -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](scala-programming-guide.html), [Java](java-programming-guide.html), and [Python](python-programming-guide.html), with a rich array of parallel operators. +Apache Spark is a fast and general-purpose cluster computing system. +It provides high-level APIs in [Scala](scala-programming-guide.html), [Java](java-programming-guide.html), and [Python](python-programming-guide.html) that make parallel jobs easy to write, and an optimized engine that supports general computation graphs. Spark can run on the Apache Mesos cluster manager, Hadoop YARN, Amazon EC2, or without an independent resource manager ("standalone mode"). # Downloading -Get Spark by visiting the [downloads page](http://spark-project.org/downloads.html) of the Spark website. This documentation is for Spark version {{site.SPARK_VERSION}}. +Get Spark by visiting the [downloads page](http://spark.incubator.apache.org/downloads.html) of the Apache Spark site. This documentation is for Spark version {{site.SPARK_VERSION}}. # Building -Spark requires [Scala {{site.SCALA_VERSION}}](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 also be accessible through one -of these methods on slave nodes on your cluster. - Spark uses [Simple Build Tool](http://www.scala-sbt.org), which is bundled with it. To compile the code, go into the top-level Spark directory and run - sbt/sbt package + sbt/sbt assembly -Spark also supports building using Maven. If you would like to build using Maven, see the [instructions for building Spark with Maven](building-with-maven.html). +For its Scala API, Spark {{site.SPARK_VERSION}} depends on Scala {{site.SCALA_VERSION}}. If you write applications in Scala, you will need to use this same version of Scala in your own program -- newer major versions may not work. You can get the right version of Scala from [scala-lang.org](http://www.scala-lang.org/download/). # Testing the Build -Spark comes with a number of sample programs in the `examples` directory. -To run one of the samples, use `./run <class> <params>` in the top-level Spark directory -(the `run` script sets up the appropriate paths and launches that program). -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. +Spark comes with several sample programs in the `examples` directory. +To run one of the samples, use `./run-example <class> <params>` in the top-level Spark directory +(the `run-example` script sets up the appropriate paths and launches that program). +For example, try `./run-example org.apache.spark.examples.SparkPi local`. +Each example prints usage help when run with no parameters. 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](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. +Finally, Spark can be used interactively through modified versions of the Scala shell (`./spark-shell`) or +Python interpreter (`./pyspark`). These are a great way to learn Spark. # A Note About Hadoop Versions -Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported +Spark uses the Hadoop-client library to talk to HDFS and other Hadoop-supported storage systems. Because the HDFS protocol has changed in different versions of -Hadoop, you must build Spark against the same version that your cluster runs. -You can change the version by setting the `HADOOP_VERSION` variable at the top -of `project/SparkBuild.scala`, then rebuilding Spark (`sbt/sbt clean compile`). +Hadoop, you must build Spark against the same version that your cluster uses. +By default, Spark links to Hadoop 1.0.4. You can change this by setting the +`SPARK_HADOOP_VERSION` variable when compiling: + + SPARK_HADOOP_VERSION=1.2.1 sbt/sbt assembly + +In addition, if you wish to run Spark on [YARN](running-on-yarn.md), set +`SPARK_YARN` to `true`: + + SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true sbt/sbt assembly # Where to Go from Here @@ -54,15 +56,20 @@ of `project/SparkBuild.scala`, then rebuilding Spark (`sbt/sbt clean compile`). * [Quick Start](quick-start.html): a quick introduction to the Spark API; start here! * [Spark Programming Guide](scala-programming-guide.html): an overview of Spark concepts, and details on the Scala API -* [Java Programming Guide](java-programming-guide.html): using Spark from Java -* [Python Programming Guide](python-programming-guide.html): using Spark from Python -* [Spark Streaming Guide](streaming-programming-guide.html): using the alpha release of Spark Streaming + * [Java Programming Guide](java-programming-guide.html): using Spark from Java + * [Python Programming Guide](python-programming-guide.html): using Spark from Python +* [Spark Streaming](streaming-programming-guide.html): using the alpha release of Spark Streaming +* [MLlib (Machine Learning)](mllib-guide.html): Spark's built-in machine learning library +* [Bagel (Pregel on Spark)](bagel-programming-guide.html): simple graph processing model **API Docs:** -* [Spark Java/Scala (Scaladoc)](api/core/index.html) -* [Spark Python (Epydoc)](api/pyspark/index.html) -* [Spark Streaming Java/Scala (Scaladoc)](api/streaming/index.html) +* [Spark for Java/Scala (Scaladoc)](api/core/index.html) +* [Spark for Python (Epydoc)](api/pyspark/index.html) +* [Spark Streaming for Java/Scala (Scaladoc)](api/streaming/index.html) +* [MLlib (Machine Learning) for Java/Scala (Scaladoc)](api/mllib/index.html) +* [Bagel (Pregel on Spark) for Scala (Scaladoc)](api/bagel/index.html) + **Deployment guides:** @@ -74,27 +81,27 @@ of `project/SparkBuild.scala`, then rebuilding Spark (`sbt/sbt clean compile`). **Other documents:** -* [Building Spark With Maven](building-with-maven.html): Build Spark using the Maven build tool * [Configuration](configuration.html): customize Spark via its configuration system * [Tuning Guide](tuning.html): best practices to optimize performance and memory use -* [Bagel](bagel-programming-guide.html): an implementation of Google's Pregel on Spark +* [Hardware Provisioning](hardware-provisioning.html): recommendations for cluster hardware +* [Building Spark with Maven](building-with-maven.html): Build Spark using the Maven build tool * [Contributing to Spark](contributing-to-spark.html) **External resources:** -* [Spark Homepage](http://www.spark-project.org) -* [Mailing List](http://groups.google.com/group/spark-users): ask questions about Spark here -* [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), +* [Spark Homepage](http://spark.incubator.apache.org) +* [Mailing Lists](http://spark.incubator.apache.org/mailing-lists.html): ask questions about Spark here +* [AMP Camps](http://ampcamp.berkeley.edu/): a series of training camps 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 +* [Code Examples](http://spark.incubator.apache.org/examples.html): more are also available in the [examples subfolder](https://github.com/apache/incubator-spark/tree/master/examples/src/main/scala/) of Spark * [Paper Describing Spark](http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf) * [Paper Describing Spark Streaming](http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-259.pdf) # Community -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). +To get help using Spark or keep up with Spark development, sign up for the [user mailing list](http://spark.incubator.apache.org/mailing-lists.html). 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. |