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From Jeff Jones <>
Subject Standalone cluster not using multiple workers for single application
Date Mon, 02 Nov 2015 19:56:13 GMT
I’ve got an a series of applications using a single standalone Spark cluster (v1.4.1).  The
cluster has 1 master and 4 workers (4 CPUs per worker node). I am using the
script to launch the worker process on each node and I can see the nodes were successfully
registered using the SparkUI.  When I launch one of my applications regardless of what I set
spark.cores.max to when instantiating the SparkContext in the driver app I seem to get a single
worker assigned to the application and all jobs that get run.  For example, if I set spark.cores.max
to 16 the SparkUI will show a single worker take the load with 4 (16 Used) in the Cores column.
 How do I get my jobs run across multiple nodes in the cluster?

Here’s a snippet from the SparkUI (IP addresses removed for privacy)

Worker Id       Address State   Cores   Memory
worker-20150920064814-***-33659 ***:33659       ALIVE   4 (0 Used)      28.0 GB (0.0 B Used)
worker-20151012175609-***37399  ***:37399       ALIVE   4 (16 Used)     28.0 GB (28.0 GB Used)
worker-20151012181934-***-36573 ***:36573       ALIVE   4 (4 Used)      28.0 GB (28.0 GB Used)
worker-20151030170514-***-45368 ***:45368       ALIVE   4 (0 Used)      28.0 GB (0.0 B Used)
Running Applications
Application ID  Name    Cores   Memory per Node Submitted Time  User    State   Duration
app-20151102194733-0278 App1    16      28.0 GB 2015/11/02 19:47:33     ***     RUNNING 2
app-20151102164156-0274 App2    4       28.0 GB 2015/11/02 16:41:56     ***     RUNNING 3.1

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