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From Mich Talebzadeh <mich.talebza...@gmail.com>
Subject Executors assigned to STS and number of workers in Stand Alone Mode
Date Mon, 25 Jul 2016 16:17:07 GMT
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 \
                --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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