ok they are submitted but the latter one 14302 is it doing anything? can you check it with jmonitor or the logs created
HTH Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* http://talebzadehmich.wordpress.com On 28 May 2016 at 18:03, sujeet jog <sujeet....@gmail.com> wrote: > Thanks Ted, > > Thanks Mich, yes i see that i can run two applications by submitting > these, probably Driver + Executor running in a single JVM . In-Process > Spark. > > wondering if this can be used in production systems, the reason for me > considering local instead of standalone cluster mode is purely because of > CPU/MEM resources, i.e, i currently do not have the liberty to use 1 > Driver & 1 Executor per application, ( running in a embedded network > switch ) > > > jps output > [root@fos-elastic02 ~]# jps > 14258 SparkSubmit > 14503 Jps > 14302 SparkSubmit > , > > On Sat, May 28, 2016 at 10:21 PM, Mich Talebzadeh < > mich.talebza...@gmail.com> wrote: > >> Ok so you want to run all this in local mode. In other words something >> like below >> >> ${SPARK_HOME}/bin/spark-submit \ >> >> --master local[2] \ >> >> --driver-memory 2G \ >> >> --num-executors=1 \ >> >> --executor-memory=2G \ >> >> --executor-cores=2 \ >> >> >> I am not sure it will work for multiple drivers (app/JVM). The only way >> you can find out is to do try it running two apps simultaneously. You have >> a number of tools. >> >> >> >> 1. use jps to see the apps and PID >> 2. use jmonitor to see memory/cpu/heap usage for each spark-submit job >> >> HTH >> >> Dr Mich Talebzadeh >> >> >> >> LinkedIn * >> https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* >> >> >> >> http://talebzadehmich.wordpress.com >> >> >> >> On 28 May 2016 at 17:41, Ted Yu <yuzhih...@gmail.com> wrote: >> >>> Sujeet: >>> >>> Please also see: >>> >>> https://spark.apache.org/docs/latest/spark-standalone.html >>> >>> On Sat, May 28, 2016 at 9:19 AM, Mich Talebzadeh < >>> mich.talebza...@gmail.com> wrote: >>> >>>> Hi Sujeet, >>>> >>>> if you have a single machine then it is Spark standalone mode. >>>> >>>> In Standalone cluster mode Spark allocates resources based on cores. >>>> By default, an application will grab all the cores in the cluster. >>>> >>>> You only have one worker that lives within the driver JVM process that >>>> you start when you start the application with spark-shell or spark-submit >>>> in the host where the cluster manager is running. >>>> >>>> The Driver node runs on the same host that the cluster manager is >>>> running. The Driver requests the Cluster Manager for resources to run >>>> tasks. The worker is tasked to create the executor (in this case there is >>>> only one executor) for the Driver. The Executor runs tasks for the Driver. >>>> Only one executor can be allocated on each worker per application. In your >>>> case you only have >>>> >>>> >>>> The minimum you will need will be 2-4G of RAM and two cores. Well that >>>> is my experience. Yes you can submit more than one spark-submit (the >>>> driver) but they may queue up behind the running one if there is not enough >>>> resources. >>>> >>>> >>>> You pointed out that you will be running few applications in parallel >>>> on the same host. The likelihood is that you are using a VM machine for >>>> this purpose and the best option is to try running the first one, Check Web >>>> GUI on 4040 to see the progress of this Job. If you start the next JVM >>>> then assuming it is working, it will be using port 4041 and so forth. >>>> >>>> >>>> In actual fact try the command "free" to see how much free memory you >>>> have. >>>> >>>> >>>> HTH >>>> >>>> >>>> >>>> >>>> >>>> Dr Mich Talebzadeh >>>> >>>> >>>> >>>> LinkedIn * >>>> https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw >>>> <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* >>>> >>>> >>>> >>>> http://talebzadehmich.wordpress.com >>>> >>>> >>>> >>>> On 28 May 2016 at 16:42, sujeet jog <sujeet....@gmail.com> wrote: >>>> >>>>> Hi, >>>>> >>>>> I have a question w.r.t production deployment mode of spark, >>>>> >>>>> I have 3 applications which i would like to run independently on a >>>>> single machine, i need to run the drivers in the same machine. >>>>> >>>>> The amount of resources i have is also limited, like 4- 5GB RAM , 3 - >>>>> 4 cores. >>>>> >>>>> For deployment in standalone mode : i believe i need >>>>> >>>>> 1 Driver JVM, 1 worker node ( 1 executor ) >>>>> 1 Driver JVM, 1 worker node ( 1 executor ) >>>>> 1 Driver JVM, 1 worker node ( 1 executor ) >>>>> >>>>> The issue here is i will require 6 JVM running in parallel, for which >>>>> i do not have sufficient CPU/MEM resources, >>>>> >>>>> >>>>> Hence i was looking more towards a local mode deployment mode, would >>>>> like to know if anybody is using local mode where Driver + Executor run in >>>>> a single JVM in production mode. >>>>> >>>>> Are there any inherent issues upfront using local mode for production >>>>> base systems.?.. >>>>> >>>>> >>>> >>> >> >
