More updates to documentation

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).