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https://issues.apache.org/jira/browse/SPARK-15917?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15401600#comment-15401600
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Jonathan Taws commented on SPARK-15917:
---------------------------------------

I'd really like to move forward on this issue, could anyone look into the 
changes ? [~andrewor14] hasn't been on the JIRA for quite some time ([~srowen] 
?)

> Define the number of executors in standalone mode with an easy-to-use property
> ------------------------------------------------------------------------------
>
>                 Key: SPARK-15917
>                 URL: https://issues.apache.org/jira/browse/SPARK-15917
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core, Spark Shell, Spark Submit
>    Affects Versions: 1.6.1
>            Reporter: Jonathan Taws
>            Priority: Minor
>
> After stumbling across a few StackOverflow posts around the issue of using a 
> fixed number of executors in standalone mode (non-YARN), I was wondering if 
> we could not add an easier way to set this parameter than having to resort to 
> some calculations based on the number of cores and the memory you have 
> available on your worker. 
> For example, let's say I have 8 cores and 30GB of memory available :
>  - If no option is passed, one executor will be spawned with 8 cores and 1GB 
> of memory allocated.
>  - However, if I want to have only *2* executors, and to use 2 cores and 10GB 
> of memory per executor, I will end up with *3* executors (as the available 
> memory will limit the number of executors) instead of the 2 I was hoping for.
> Sure, I can set {{spark.cores.max}} as a workaround to get exactly what I 
> want, but would it not be easier to add a {{--num-executors}}-like option to 
> standalone mode to be able to really fine-tune the configuration ? This 
> option is already available in YARN mode.
> From my understanding, I don't see any other option lying around that can 
> help achieve this.  
> This seems to be slightly disturbing for newcomers, and standalone mode is 
> probably the first thing anyone will use to just try out Spark or test some 
> configuration.  



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