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From Jean Georges Perrin <...@jgp.net>
Subject Re: spark.executor.cores
Date Fri, 15 Jul 2016 15:42:10 GMT
lol - young padawan I am and path to knowledge seeking I am...

And on this path I also tried (without luck)...

		if (restId == 0) {
			conf = conf.setExecutorEnv("spark.executor.cores", "22");
		} else {
			conf = conf.setExecutorEnv("spark.executor.cores", "2");
		}

and

		if (restId == 0) {
			conf.setExecutorEnv("spark.executor.cores", "22");
		} else {
			conf.setExecutorEnv("spark.executor.cores", "2");
		}

the only annoying thing I see is we designed some of the work to be handled by the driver/client
app and we will have to rethink a bit the design of the app for that...


> On Jul 15, 2016, at 11:34 AM, Daniel Darabos <daniel.darabos@lynxanalytics.com>
wrote:
> 
> Mich's invocation is for starting a Spark application against an already running Spark
standalone cluster. It will not start the cluster for you.
> 
> We used to not use "spark-submit", but we started using it when it solved some problem
for us. Perhaps that day has also come for you? :)
> 
> On Fri, Jul 15, 2016 at 5:14 PM, Jean Georges Perrin <jgp@jgp.net <mailto:jgp@jgp.net>>
wrote:
> 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 <mailto: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
<https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>
>>  
>> http://talebzadehmich.wordpress.com <http://talebzadehmich.wordpress.com/>
>> 
>> Disclaimer: Use it at your own risk. Any and all responsibility for any loss, damage
or destruction of data or any other property which may arise from relying on this email's
technical content is explicitly disclaimed. The author will in no case be liable for any monetary
damages arising from such loss, damage or destruction.
>>  
>> 
>> 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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