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Diffstat (limited to 'docs/scala-programming-guide.md')
| -rw-r--r-- | docs/scala-programming-guide.md | 5 |
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. |