You can set the spark.cores.max property in your application to limit the maximum number of cores it will take. Checko ut http://spark.incubator.apache.org/docs/latest/spark-standalone.html#resource-scheduling. It’s also possible to control scheduling in more detail within a Spark application, or if you run on other cluster managers, like Mesos. That’s described in more detail here: http://spark.incubator.apache.org/docs/latest/job-scheduling.html.
Matei On Jan 31, 2014, at 2:42 PM, Timothee Besset <[email protected]> wrote: > Hello, > > What are my options to balance resources between multiple applications > running against a Spark cluster? > > I am using the standalone cluster [1] setup on my local machine, and starting > a single application uses all the available cores. As long as that first > application is running, no other application does any processing. > > I tried to run more workers using less cores with SPARK_WORKER_CORES, but the > single application still takes everything (see > https://dl.dropboxusercontent.com/u/1529870/spark%20-%20multiple%20applications.png > ). > > Is there any strategy to reallocate resources based on number of applications > running against the cluster, or is the design mostly geared towards having a > single application running at a time? > > Thank you, > TTimo > > [1] http://spark.incubator.apache.org/docs/latest/spark-standalone.html >
