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Diffstat (limited to 'docs/spark-standalone.md')
| -rw-r--r-- | docs/spark-standalone.md | 15 |
1 files changed, 11 insertions, 4 deletions
diff --git a/docs/spark-standalone.md b/docs/spark-standalone.md index b822265b5a..f7f0b78908 100644 --- a/docs/spark-standalone.md +++ b/docs/spark-standalone.md @@ -154,11 +154,18 @@ You can also pass an option `-c <numCores>` to control the number of cores that The standalone cluster mode currently only supports a simple FIFO scheduler across applications. However, to allow multiple concurrent users, you can control the maximum number of resources each -application will acquire. +application will use. By default, it will acquire *all* cores in the cluster, which only makes sense if you just run one -application at a time. You can cap the number of cores using -`System.setProperty("spark.cores.max", "10")` (for example). -This value must be set *before* initializing your SparkContext. +application at a time. You can cap the number of cores by setting `spark.cores.max` in your +[SparkConf](configuration.html#spark-properties). For example: + +{% highlight scala %} +val conf = new SparkConf() + .setMaster(...) + .setAppName(...) + .set("spark.cores.max", "10") +val sc = new SparkContext(conf) +{% endhighlight %} # Monitoring and Logging |