SPARK-1099: Introduce local[*] mode to infer number of cores

This is the default mode for running spark-shell and pyspark, intended to allow users running spark for the first time to see the performance benefits of using multiple cores, while not breaking backwards compatibility for users who use "local" mode and expect exactly 1 core.

Author: Aaron Davidson <aaron@databricks.com>

Closes #182 from aarondav/110 and squashes the following commits:

a88294c [Aaron Davidson] Rebased changes for new spark-shell
a9f393e [Aaron Davidson] SPARK-1099: Introduce local[*] mode to infer number of cores

1 files changed, 3 insertions, 2 deletions

diff --git a/docs/scala-programming-guide.md b/docs/scala-programming-guide.md
index 77373890ee..a07cd2e0a3 100644
--- a/docs/scala-programming-guide.md
+++ b/docs/scala-programming-guide.md
@@ -54,7 +54,7 @@ object for more advanced configuration.
 
 The `master` parameter is a string specifying a [Spark or Mesos cluster URL](#master-urls) to connect to, or a special "local" string to run in local mode, as described below. `appName` is a name for your application, which will be shown in the cluster web UI. Finally, the last two parameters are needed to deploy your code to a cluster if running in distributed mode, as described later.
 
-In the Spark shell, a special interpreter-aware SparkContext is already created for you, in the variable called `sc`. Making your own SparkContext will not work. You can set which master the context connects to using the `MASTER` environment variable, and you can add JARs to the classpath with the `ADD_JARS` variable. For example, to run `bin/spark-shell` on four cores, use
+In the Spark shell, a special interpreter-aware SparkContext is already created for you, in the variable called `sc`. Making your own SparkContext will not work. You can set which master the context connects to using the `MASTER` environment variable, and you can add JARs to the classpath with the `ADD_JARS` variable. For example, to run `bin/spark-shell` on exactly four cores, use
 
 {% highlight bash %}
 $ MASTER=local[4] ./bin/spark-shell
@@ -74,6 +74,7 @@ The master URL passed to Spark can be in one of the following formats:
 <tr><th>Master URL</th><th>Meaning</th></tr>
 <tr><td> local </td><td> Run Spark locally with one worker thread (i.e. no parallelism at all). </td></tr>
 <tr><td> local[K] </td><td> Run Spark locally with K worker threads (ideally, set this to the number of cores on your machine).
+<tr><td> local[*] </td><td> Run Spark locally with as many worker threads as logical cores on your machine.</td></tr>
 </td></tr>
 <tr><td> spark://HOST:PORT </td><td> Connect to the given <a href="spark-standalone.html">Spark standalone
         cluster</a> master. The port must be whichever one your master is configured to use, which is 7077 by default.
@@ -84,7 +85,7 @@ The master URL passed to Spark can be in one of the following formats:
 </td></tr>
 </table>
 
-If no master URL is specified, the spark shell defaults to "local".
+If no master URL is specified, the spark shell defaults to "local[*]".
 
 For running on YARN, Spark launches an instance of the standalone deploy cluster within YARN; see [running on YARN](running-on-yarn.html) for details.