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

${SPARK_HOME}/bin/spark-submit \
                --packages com.databricks:spark-csv_2.11:1.3.0 \
                --driver-memory 2G \
                --num-executors 2 \
                --executor-cores 3 \
                --executor-memory 2G \
                --master spark://50.140.197.217:7077 \
                --conf "spark.scheduler.mode=FAIR" \
                --conf "spark.executor.extraJavaOptions=-XX:+PrintGCDetails
-XX:+PrintGCTimeStamps" \
                --jars
/home/hduser/jars/spark-streaming-kafka-assembly_2.10-1.6.1.jar \
                --class "${FILE_NAME}" \
                --conf "spark.ui.port=${SP}" \

HTH

Dr Mich Talebzadeh



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On 15 July 2016 at 13:48, Jean Georges Perrin <j...@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 <nihe...@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 <j...@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://tn.linkedin.com/in/nihed>
>
>
>

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