That's also available in standalone. On Thu, Apr 14, 2016 at 12:47 PM, Alexander Pivovarov <apivova...@gmail.com> wrote:
> Spark on Yarn supports dynamic resource allocation > > So, you can run several spark-shells / spark-submits / spark-jobserver / > zeppelin on one cluster without defining upfront how many executors / > memory you want to allocate to each app > > Great feature for regular users who just want to run Spark / Spark SQL > > > On Thu, Apr 14, 2016 at 12:05 PM, Sean Owen <so...@cloudera.com> wrote: > >> I don't think usage is the differentiating factor. YARN and standalone >> are pretty well supported. If you are only running a Spark cluster by >> itself with nothing else, standalone is probably simpler than setting >> up YARN just for Spark. However if you're running on a cluster that >> will host other applications, you'll need to integrate with a shared >> resource manager and its security model, and for anything >> Hadoop-related that's YARN. Standalone wouldn't make as much sense. >> >> On Thu, Apr 14, 2016 at 6:46 PM, Alexander Pivovarov >> <apivova...@gmail.com> wrote: >> > AWS EMR includes Spark on Yarn >> > Hortonworks and Cloudera platforms include Spark on Yarn as well >> > >> > >> > On Thu, Apr 14, 2016 at 7:29 AM, Arkadiusz Bicz < >> arkadiusz.b...@gmail.com> >> > wrote: >> >> >> >> Hello, >> >> >> >> Is there any statistics regarding YARN vs Standalone Spark Usage in >> >> production ? >> >> >> >> I would like to choose most supported and used technology in >> >> production for our project. >> >> >> >> >> >> BR, >> >> >> >> Arkadiusz Bicz >> >> >> >> --------------------------------------------------------------------- >> >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> >> For additional commands, e-mail: user-h...@spark.apache.org >> >> >> > >> > >
