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From Mridul Muralidharan <mri...@gmail.com>
Subject Re: Spark config option 'expression language' feedback request
Date Sat, 14 Mar 2015 00:30:51 GMT
Let me try to rephrase my query.
How can a user specify, for example, what the executor memory should
be or number of cores should be.

I dont want a situation where some variables can be specified using
one set of idioms (from this PR for example) and another set cannot
be.


Regards,
Mridul




On Fri, Mar 13, 2015 at 4:06 PM, Dale Richardson <dale__r@hotmail.com> wrote:
>
>
>
> Thanks for your questions Mridul.
> I assume you are referring to how the functionality to query system state works in Yarn
and Mesos?
> The API's used are the standard JVM API's so the functionality will work without change.
There is no real use case for using 'physicalMemoryBytes' in these cases though, as the JVM
size has already been limited by the resource manager.
> Regards,Dale.
>> Date: Fri, 13 Mar 2015 08:20:33 -0700
>> Subject: Re: Spark config option 'expression language' feedback request
>> From: mridul@gmail.com
>> To: dale__r@hotmail.com
>> CC: dev@spark.apache.org
>>
>> I am curious how you are going to support these over mesos and yarn.
>> Any configure change like this should be applicable to all of them, not
>> just local and standalone modes.
>>
>> Regards
>> Mridul
>>
>> On Friday, March 13, 2015, Dale Richardson <dale__r@hotmail.com> wrote:
>>
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > PR#4937 ( https://github.com/apache/spark/pull/4937) is a feature to
>> > allow for Spark configuration options (whether on command line, environment
>> > variable or a configuration file) to be specified via a simple expression
>> > language.
>> >
>> >
>> > Such a feature has the following end-user benefits:
>> > - Allows for the flexibility in specifying time intervals or byte
>> > quantities in appropriate and easy to follow units e.g. 1 week rather
>> > rather then 604800 seconds
>> >
>> > - Allows for the scaling of a configuration option in relation to a system
>> > attributes. e.g.
>> >
>> > SPARK_WORKER_CORES = numCores - 1
>> >
>> > SPARK_WORKER_MEMORY = physicalMemoryBytes - 1.5 GB
>> >
>> > - Gives the ability to scale multiple configuration options together eg:
>> >
>> > spark.driver.memory = 0.75 * physicalMemoryBytes
>> >
>> > spark.driver.maxResultSize = spark.driver.memory * 0.8
>> >
>> >
>> > The following functions are currently supported by this PR:
>> > NumCores:             Number of cores assigned to the JVM (usually ==
>> > Physical machine cores)
>> > PhysicalMemoryBytes:  Memory size of hosting machine
>> >
>> > JVMTotalMemoryBytes:  Current bytes of memory allocated to the JVM
>> >
>> > JVMMaxMemoryBytes:    Maximum number of bytes of memory available to the
>> > JVM
>> >
>> > JVMFreeMemoryBytes:   maxMemoryBytes - totalMemoryBytes
>> >
>> >
>> > I was wondering if anybody on the mailing list has any further ideas on
>> > other functions that could be useful to have when specifying spark
>> > configuration options?
>> > Regards,Dale.
>> >
>
>

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