title: How to allocate more executors per worker in Standalone cluster mode?
body: <p>I use Spark 1.3.0 in a cluster of 5 worker nodes with 36 cores and 58GB of memory each. I'd like to configure Spark's Standalone cluster with many executors per worker.</p>
  
  <p>I have seen the merged <a href="https://issues.apache.org/jira/browse/SPARK-1706">SPARK-1706</a>, however it is not immediately clear how to actually configure multiple executors.</p>
  
  <p>Here is the latest configuration of the cluster:</p>
  
  <pre><code>spark.executor.cores = "15"
  spark.executor.instances = "10"
  spark.executor.memory = "10g"
  </code></pre>
  
  <p>These settings are set on a <code>SparkContext</code> when the Spark application is submitted to the cluster.</p>