--num-executors does not work for Standalone mode. Try --total-executor-cores
> On Jul 26, 2016, at 00:17, Mich Talebzadeh <mich.talebza...@gmail.com> wrote:
> 
> Hi,
> 
> 
> I am doing some tests
> 
> I have started Spark in Standalone mode.
> 
> For simplicity I am using one node only with 8 works and I have 12 cores
> 
> In spark-env.sh I set this
> 
> # Options for the daemons used in the standalone deploy mode
> export SPARK_WORKER_CORES=1 ##, total number of cores to be used by executors 
> by each worker
> export SPARK_WORKER_MEMORY=1g ##, to set how much total memory workers have 
> to give executors (e.g. 1000m, 2g)
> the worker
> export SPARK_WORKER_INSTANCES=8 ##, to set the number of worker processes per 
> node
> 
> So it is pretty straight forward with 8 works and each worker assigned one 
> core
> 
> jps|grep Worker
> 15297 Worker
> 14794 Worker
> 15374 Worker
> 14998 Worker
> 15198 Worker
> 15465 Worker
> 14897 Worker
> 15099 Worker
> 
> I start Spark Thrift Server with the following parameters (using standalone 
> mode)
> 
> ${SPARK_HOME}/sbin/start-thriftserver.sh \
>                 --master spark://50.140.197.217:7077 
> <http://50.140.197.217:7077/> \
>                 --hiveconf hive.server2.thrift.port=10055 \
>                 --driver-memory 1G \
>                 --num-executors 1 \
>                 --executor-cores 1 \
>                 --executor-memory 1G \
>                 --conf "spark.scheduler.mode=FIFO" \
> 
> With one executor allocated 1 core
> 
> However, I can see both in the OS and UI that it starts with 8 executors, the 
> same number of workers on this node!
> 
> jps|egrep 'SparkSubmit|CoarseGrainedExecutorBackend'|sort
> 32711 SparkSubmit
> 369 CoarseGrainedExecutorBackend
> 370 CoarseGrainedExecutorBackend
> 371 CoarseGrainedExecutorBackend
> 376 CoarseGrainedExecutorBackend
> 387 CoarseGrainedExecutorBackend
> 395 CoarseGrainedExecutorBackend
> 419 CoarseGrainedExecutorBackend
> 420 CoarseGrainedExecutorBackend
> 
> 
> I fail to see why this is happening. Nothing else is running Spark wise. The 
> cause?
> 
>  How can I stop STS going and using all available workers?
> 
> Thanks
> 
> Dr Mich Talebzadeh
>  
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