Github user sryza commented on a diff in the pull request:
https://github.com/apache/spark/pull/130#discussion_r10530856
--- Diff: docs/running-on-yarn.md ---
@@ -99,16 +99,16 @@ With this mode, your application is actually run on the
remote machine where the
## Launch spark application with yarn-client mode.
-With yarn-client mode, the application will be launched locally. Just like
running application or spark-shell on Local / Mesos / Standalone mode. The
launch method is also the similar with them, just make sure that when you need
to specify a master url, use "yarn-client" instead. And you also need to export
the env value for SPARK_JAR.
+With yarn-client mode, the application will be launched locally, as when
running the application or spark-shell on Local / Mesos / Standalone mode. The
method to launch is similar as with those modes, except you should specify
"yarn-client" as the master URL. You also need to export the env value for
SPARK_JAR.
Configuration in yarn-client mode:
-In order to tune worker core/number/memory etc. You need to export
environment variables or add them to the spark configuration file
(./conf/spark_env.sh). The following are the list of options.
+In order to tune worker core/number/memory etc. you need to export
environment variables or add them to the spark configuration file
(./conf/spark_env.sh). The following are the list of options.
* `SPARK_WORKER_INSTANCES`, Number of workers to start (Default: 2)
-* `SPARK_WORKER_CORES`, Number of cores for the workers (Default: 1).
+* `SPARK_WORKER_CORES`, Number of cores for the workers (Default: 1)
* `SPARK_WORKER_MEMORY`, Memory per Worker (e.g. 1000M, 2G) (Default: 1G)
-* `SPARK_MASTER_MEMORY`, Memory for Master (e.g. 1000M, 2G) (Default: 512
Mb)
+* `SPARK_MASTER_MEMORY`, Memory for Master (e.g. 1000M, 2G) (Default: 512
M)
--- End diff --
Should take out the space between 512 and "M" as well.
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