Updating lots of docs to use the new special version number variables,

also adding the version to the navbar so it is easy to tell which
version of Spark these docs were compiled for.

docs/_config.yml

@@ -5,4 +5,4 @@ markdown: kramdown
 # of Spark, Scala, and Mesos.
 SPARK_VERSION: 0.6.0
 SCALA_VERSION: 2.9.2
-MESOS_VERSION: 0.9.0
+MESOS_VERSION: 0.9.0-incubating

docs/_layouts/global.html

@@ -43,8 +43,8 @@
                             <a href="#" class="dropdown-toggle" data-toggle="dropdown">Programming Guides<b class="caret"></b></a>
                             <ul class="dropdown-menu">
                                 <li><a href="quick-start.html">Quick Start</a></li>
-                                <li><a href="scala-programming-guide.html">Scala</a></li>
-                                <li><a href="java-programming-guide.html">Java</a></li>
+                                <li><a href="scala-programming-guide.html">Scala Programming Guide</a></li>
+                                <li><a href="java-programming-guide.html">Java Programming Guide</a></li>
                             </ul>
                         </li>
                         
@@ -55,8 +55,8 @@
                             <ul class="dropdown-menu">
                                 <li><a href="ec2-scripts.html">Amazon EC2</a></li>
                                 <li><a href="spark-standalone.html">Standalone Mode</a></li>
-                                <li><a href="running-on-mesos.html">Mesos</a></li>
-                                <li><a href="running-on-yarn.html">YARN</a></li>
+                                <li><a href="running-on-mesos.html">On Mesos</a></li>
+                                <li><a href="running-on-yarn.html">On YARN</a></li>
                             </ul>
                         </li>
 
@@ -69,6 +69,7 @@
                                 <li><a href="contributing-to-spark.html">Contributing to Spark</a></li>
                             </ul>
                         </li>
+                        <p class="navbar-text pull-right"><span class="version-text">v{{site.SPARK_VERSION}}</span></p>
                     </ul>
                 </div>
             </div>

docs/css/main.css

@@ -20,6 +20,17 @@
   font-size: 15px;
 }
 
+.navbar .divider-vertical {
+  border-right-color: lightgray;
+}
+
+.navbar-text .version-text {
+  border: solid thin lightgray;
+  border-radius: 6px;
+  padding: 5px;
+  margin-left: 10px;
+}
+
 body #content {
   line-height: 1.6; /* Inspired by Github's wiki style */
 }

docs/index.md

@@ -19,7 +19,7 @@ Get Spark by checking out the master branch of the Git repository, using `git cl
 
 # Building
 
-Spark requires [Scala 2.9.2](http://www.scala-lang.org/). You will need to have Scala's `bin` directory in your `PATH`,
+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.

docs/java-programming-guide.md

 ---
 layout: global
-title: Java Programming Guide
+title: Spark Java Programming Guide
 ---
 
 The Spark Java API exposes all the Spark features available in the Scala version to Java.

docs/quick-start.md

@@ -119,7 +119,7 @@ import SparkContext._
 object SimpleJob extends Application {
   val logFile = "/var/log/syslog" // Should be some log file on your system
   val sc = new SparkContext("local", "Simple Job", "$YOUR_SPARK_HOME", 
-    "target/scala-2.9.2/simple-project_2.9.2-1.0.jar")
+    "target/scala-{{site.SCALA_VERSION}}/simple-project_{{site.SCALA_VERSION}}-1.0.jar")
   val logData = sc.textFile(logFile, 2).cache()
   val numAs = logData.filter(line => line.contains("a")).count()
   val numBs = logData.filter(line => line.contains("b")).count()
@@ -136,9 +136,9 @@ name := "Simple Project"
 
 version := "1.0"
 
-scalaVersion := "2.9.2"
+scalaVersion := "{{site.SCALA_VERSION}}"
 
-libraryDependencies += "org.spark-project" %% "spark-core" % "0.6.0-SNAPSHOT"
+libraryDependencies += "org.spark-project" %% "spark-core" % "{{site.SPARK_VERSION}}"
 {% endhighlight %}
 
 Of course, for sbt to work correctly, we'll need to layout `SimpleJob.scala` and `simple.sbt` according to the typical directory structure. Once that is in place, we can create a jar package containing the job's code, then use `sbt run` to execute our example job. 
@@ -209,8 +209,8 @@ Our Maven `pom.xml` file will list Spark as a dependency. Note that Spark artifa
   <dependencies>
     <dependency> <!-- Spark dependency -->
       <groupId>org.spark-project</groupId>
-      <artifactId>spark-core_2.9.2</artifactId>
-      <version>0.6.0-SNAPSHOT</version>
+      <artifactId>spark-core_{{site.SCALA_VERSION}}</artifactId>
+      <version>{{site.SPARK_VERSION}}</version>
     </dependency>
   </dependencies>
 </project>

docs/running-on-mesos.md

@@ -6,7 +6,7 @@ title: Running Spark on Mesos
 Spark can run on private clusters managed by the [Apache Mesos](http://incubator.apache.org/mesos/) resource manager. Follow the steps below to install Mesos and Spark:
 
 1. Download and build Spark using the instructions [here](index.html).
-2. Download Mesos 0.9.0 from a [mirror](http://www.apache.org/dyn/closer.cgi/incubator/mesos/mesos-0.9.0-incubating/).
+2. Download Mesos {{site.MESOS_VERSION}} from a [mirror](http://www.apache.org/dyn/closer.cgi/incubator/mesos/mesos-{{site.MESOS_VERSION}}/).
 3. Configure Mesos using the `configure` script, passing the location of your `JAVA_HOME` using `--with-java-home`. Mesos comes with "template" configure scripts for different platforms, such as `configure.macosx`, that you can run. See the README file in Mesos for other options. **Note:** If you want to run Mesos without installing it into the default paths on your system (e.g. if you don't have administrative privileges to install it), you should also pass the `--prefix` option to `configure` to tell it where to install. For example, pass `--prefix=/home/user/mesos`. By default the prefix is `/usr/local`.
 4. Build Mesos using `make`, and then install it using `make install`.
 5. Create a file called `spark-env.sh` in Spark's `conf` directory, by copying `conf/spark-env.sh.template`, and add the following lines in it:

docs/running-on-yarn.md

@@ -3,10 +3,11 @@ layout: global
 title: Launching Spark on YARN
 ---
 
-Spark 0.6 adds experimental support for running over a [YARN (Hadoop 
-NextGen)](http://hadoop.apache.org/docs/r2.0.1-alpha/hadoop-yarn/hadoop-yarn-site/YARN.html) cluster. 
-Because YARN depends on version 2.0 of the Hadoop libraries, this currently requires checking out a
-separate branch of Spark, called `yarn`, which you can do as follows:
+Experimental support for running over a [YARN (Hadoop
+NextGen)](http://hadoop.apache.org/docs/r2.0.1-alpha/hadoop-yarn/hadoop-yarn-site/YARN.html)
+cluster was added to Spark in version 0.6.0.  Because YARN depends on version
+2.0 of the Hadoop libraries, this currently requires checking out a separate
+branch of Spark, called `yarn`, which you can do as follows:
 
     git clone git://github.com/mesos/spark
     cd spark
@@ -18,7 +19,7 @@ separate branch of Spark, called `yarn`, which you can do as follows:
 - In order to distribute Spark within the cluster, it must be packaged into a single JAR file. This can be done by running `sbt/sbt assembly`
 - Your application code must be packaged into a separate JAR file.
 
-If you want to test out the YARN deployment mode, you can use the current Spark examples. A `spark-examples_2.9.2-0.6.0-SNAPSHOT.jar` file can be generated by running `sbt/sbt package`.
+If you want to test out the YARN deployment mode, you can use the current Spark examples. A `spark-examples_{{site.SCALA_VERSION}}-{{site.SPARK_VERSION}}-SNAPSHOT.jar` file can be generated by running `sbt/sbt package`. NOTE: since the documentation you're reading is for Spark version {{site.SPARK_VERSION}}, we are assuming here that you have downloaded Spark {{site.SPARK_VERSION}} or checked it out of source control. If you are using a different version of Spark, the version numbers in the jar generated by the sbt package command will obviously be different.
 
 # Launching Spark on YARN
 
@@ -34,8 +35,8 @@ The command to launch the YARN Client is as follows:
 
 For example:
 
-    SPARK_JAR=./core/target/spark-core-assembly-0.6.0-SNAPSHOT.jar ./run spark.deploy.yarn.Client \
-      --jar examples/target/scala-2.9.2/spark-examples_2.9.2-0.6.0-SNAPSHOT.jar \
+    SPARK_JAR=./core/target/spark-core-assembly-{{site.SPARK_VERSION}}-SNAPSHOT.jar ./run spark.deploy.yarn.Client \
+      --jar examples/target/scala-{{site.SCALA_VERSION}}/spark-examples_{{site.SCALA_VERSION}}-{{site.SPARK_VERSION}}-SNAPSHOT.jar \
       --class spark.examples.SparkPi \
       --args standalone \
       --num-workers 3 \

docs/scala-programming-guide.md

 ---
 layout: global
-title: Spark Programming Guide
+title: Spark Scala Programming Guide
 ---
 
 * This will become a table of contents (this text will be scraped).