Apache Spark is a fast and general-purpose cluster computing system.
It provides high-level APIs in Java, Scala and Python,
and an optimized engine that supports general execution graphs.
It also supports a rich set of higher-level tools including [Shark](http://shark.cs.berkeley.edu)(Hive on Spark), [Spark SQL](sql-programming-guide.html) for structured data, [MLlib](mllib-guide.html) for machine learning, [GraphX](graphx-programming-guide.html) for graph processing, and [Spark Streaming](streaming-programming-guide.html).
It also supports a rich set of higher-level tools including [Spark SQL](sql-programming-guide.html) for SQL and structured data processing, [MLlib](mllib-guide.html) for machine learning, [GraphX](graphx-programming-guide.html) for graph processing, and [Spark Streaming](streaming-programming-guide.html).
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**External Resources:**
*[Spark Homepage](http://spark.apache.org)
*[Shark](http://shark.cs.berkeley.edu): Apache Hive over Spark
*[Mailing Lists](http://spark.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, Spark Streaming, Mesos, and more. [Videos](http://ampcamp.berkeley.edu/3/),
exercises about Spark, Spark Streaming, Mesos, and more. [Videos](http://ampcamp.berkeley.edu/3/),
[slides](http://ampcamp.berkeley.edu/3/) and [exercises](http://ampcamp.berkeley.edu/3/exercises/) are
available online for free.
*[Code Examples](http://spark.apache.org/examples.html): more are also available in the `examples` subfolder of Spark ([Scala]({{site.SPARK_GITHUB_URL}}/tree/master/examples/src/main/scala/org/apache/spark/examples),
