Thanks Vincent. You mean 20 times improvement with data being local as opposed to Spark running on compute nodes?
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 14 April 2018 at 21:06, vincent gromakowski < vincent.gromakow...@gmail.com> wrote: > Not with hadoop but with Cassandra, i have seen 20x data locality > improvement on partitioned optimized spark jobs > > Le sam. 14 avr. 2018 à 21:17, Mich Talebzadeh <mich.talebza...@gmail.com> > a écrit : > >> Hi, >> >> This is a sort of your mileage varies type question. >> >> In a classic Hadoop cluster, one has data locality when each node >> includes the Spark libraries and HDFS data. this helps certain queries like >> interactive BI. >> >> However running Spark over remote storage say Isilon scaled out NAS >> instead of LOCAL HDFS becomes problematic. The full-scan Spark needs to >> do will take much longer when it is done over the network (access the >> remote Isilon storage) instead of local I/O request to HDFS. >> >> Has anyone done some comparative studies on this? >> >> >> Thanks >> >> >> 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. >> >> >> >
