Yes, that is correct. You can use this boiler plate to avoid spark-submit.
//The configurations
val sconf = new SparkConf()
.setMaster("spark://spark-ak-master:7077")
.setAppName("SigmoidApp")
.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.set("spark.cores.max", "12")
.set("spark.executor.memory", "36g")
//The context!
val sc = new SparkContext(sconf)
//The jar dependencies!
sc.addJar("target/scala-2.10/sigmoidapp_10-1.0.jar")
Thanks
Best Regards
On Fri, Jul 10, 2015 at 4:07 PM, algermissen1971 <algermissen1...@icloud.com
> wrote:
> Hi,
>
> I am a bit confused about the steps I need to take to start a Spark
> application on a cluster.
>
> So far I had this impression from the documentation that I need to
> explicitly submit the application using for example spark-submit.
>
> However, from the SparkContext constructur signature I get the impression
> that maybe I do not have to do that after all:
>
> In
> http://spark.apache.org/docs/latest/api/scala/#org.apache.spark.SparkContext
> the first constructor has (among other things) a parameter 'jars' which
> indicates the "Collection of JARs to send to the cluster".
>
> To me this suggests that I can simply start the application anywhere and
> that it will deploy itself to the cluster in the same way a call to
> spark-submit would.
>
> Is that correct?
>
> If not, can someone explain why I can / need to provide master and jars
> etc. in the call to SparkContext because they essentially only duplicate
> what I would specify in the call to spark-submit.
>
> Jan
>
>
>
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