We also should remember that STS is a pretty useful tool. With JDBC you can use beeline, Zeppelin, Squirrel and other tools against it.
One thing I like to change is the UI port that the thrift server listens and you can change it at startup using spark.ui.port. This is fixed at thrift startup and can only display one sql query at a time which is kind not useful. As one can run multiple clients against STS, it is a limitation that one cannot change the UI port at runtime. Cheers Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com/profile/view?id=AAEAAAAWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw>* 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 25 July 2016 at 22:04, Jacek Laskowski <ja...@japila.pl> wrote: > On Mon, Jul 25, 2016 at 10:57 PM, Mich Talebzadeh > <mich.talebza...@gmail.com> wrote: > > > Yarn promises the best resource management I believe. Having said that I > have not used Mesos myself. > > I'm glad you've mentioned it. > > I think Cloudera (and Hortonworks?) guys are doing a great job with > bringing all the features of YARN to Spark and I think Spark on YARN > shines features-wise. > > I'm not in a position to compare YARN vs Mesos for their resource > management, but Spark on Mesos is certainly lagging behind Spark on > YARN regarding the features Spark uses off the scheduler backends -- > security, data locality, queues, etc. (or I might be simply biased > after having spent months with Spark on YARN mostly?). > > Jacek >
