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From Jean Georges Perrin <...@jgp.net>
Subject Re: spark.executor.cores
Date Fri, 15 Jul 2016 15:14:24 GMT
I don't use submit: I start my standalone cluster and connect to it remotely. Is that a bad
practice?

I'd like to be able to it dynamically as the system knows whether it needs more or less resources
based on its own  context

> On Jul 15, 2016, at 10:55 AM, Mich Talebzadeh <mich.talebzadeh@gmail.com> wrote:
> 
> Hi,
> 
> You can also do all this at env or submit time with spark-submit which I believe makes
it more flexible than coding in.
> 
> Example
> 
> ${SPARK_HOME}/bin/spark-submit \
>                 --packages com.databricks:spark-csv_2.11:1.3.0 \
>                 --driver-memory 2G \
>                 --num-executors 2 \
>                 --executor-cores 3 \
>                 --executor-memory 2G \
>                 --master spark://50.140.197.217:7077 <http://50.140.197.217:7077/>
\
>                 --conf "spark.scheduler.mode=FAIR" \
>                 --conf "spark.executor.extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps"
\
>                 --jars /home/hduser/jars/spark-streaming-kafka-assembly_2.10-1.6.1.jar
\
>                 --class "${FILE_NAME}" \
>                 --conf "spark.ui.port=${SP}" \
>  
> HTH
> 
> Dr Mich Talebzadeh
>  
> LinkedIn  https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
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>  
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> 
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>  
> 
> On 15 July 2016 at 13:48, Jean Georges Perrin <jgp@jgp.net <mailto:jgp@jgp.net>>
wrote:
> Merci Nihed, this is one of the tests I did :( still not working
> 
> 
> 
>> On Jul 15, 2016, at 8:41 AM, nihed mbarek <nihedmm@gmail.com <mailto:nihedmm@gmail.com>>
wrote:
>> 
>> can you try with : 
>> SparkConf conf = new SparkConf().setAppName("NC Eatery app").set("spark.executor.memory",
"4g")
>> 				.setMaster("spark://10.0.100.120:7077 <>");
>> 		if (restId == 0) {
>> 			conf = conf.set("spark.executor.cores", "22");
>> 		} else {
>> 			conf = conf.set("spark.executor.cores", "2");
>> 		}
>> 		JavaSparkContext javaSparkContext = new JavaSparkContext(conf);
>> 
>> On Fri, Jul 15, 2016 at 2:31 PM, Jean Georges Perrin <jgp@jgp.net <mailto:jgp@jgp.net>>
wrote:
>> Hi,
>> 
>> Configuration: standalone cluster, Java, Spark 1.6.2, 24 cores
>> 
>> My process uses all the cores of my server (good), but I am trying to limit it so
I can actually submit a second job.
>> 
>> I tried
>> 
>> 		SparkConf conf = new SparkConf().setAppName("NC Eatery app").set("spark.executor.memory",
"4g")
>> 				.setMaster("spark://10.0.100.120:7077 <>");
>> 		if (restId == 0) {
>> 			conf = conf.set("spark.executor.cores", "22");
>> 		} else {
>> 			conf = conf.set("spark.executor.cores", "2");
>> 		}
>> 		JavaSparkContext javaSparkContext = new JavaSparkContext(conf);
>> 
>> and
>> 
>> 		SparkConf conf = new SparkConf().setAppName("NC Eatery app").set("spark.executor.memory",
"4g")
>> 				.setMaster("spark://10.0.100.120:7077 <>");
>> 		if (restId == 0) {
>> 			conf.set("spark.executor.cores", "22");
>> 		} else {
>> 			conf.set("spark.executor.cores", "2");
>> 		}
>> 		JavaSparkContext javaSparkContext = new JavaSparkContext(conf);
>> 
>> but it does not seem to take it. Any hint?
>> 
>> jg
>> 
>> 
>> 
>> 
>> 
>> -- 
>> 
>> M'BAREK Med Nihed,
>> Fedora Ambassador, TUNISIA, Northern Africa
>> http://www.nihed.com <http://www.nihed.com/>
>> 
>>  <http://tn.linkedin.com/in/nihed>
>> 
> 
> 


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