so I assume Ignite will not work with Spark version >=2? Dr Mich Talebzadeh
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On 27 October 2016 at 12:27, vincent gromakowski < vincent.gromakow...@gmail.com> wrote: > some options: > - ignite for spark 1.5, can deep store on cassandra > - alluxio for all spark versions, can deep store on hdfs, gluster... > > ==> these are best for sharing between jobs > > - shared sparkcontext and fair scheduling, seems to be not thread safe > - spark jobserver and namedRDD, CRUD thread safe RDD sharing between spark > jobs > ==> these are best for sharing between users > > 2016-10-27 12:59 GMT+02:00 vincent gromakowski < > vincent.gromakow...@gmail.com>: > >> I would prefer sharing the spark context and using FAIR scheduler for >> user concurrency >> >> Le 27 oct. 2016 12:48 PM, "Mich Talebzadeh" <mich.talebza...@gmail.com> >> a écrit : >> >>> thanks Vince. >>> >>> So Ignite uses some hash/in-memory indexing. >>> >>> The question is in practice is there much use case to use these two >>> fabrics for sharing RDDs. >>> >>> Remember all RDBMSs do this through shared memory. >>> >>> In layman's term if I have two independent spark-submit running, can >>> they share result set. For example the same tempTable etc? >>> >>> 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 27 October 2016 at 11:44, vincent gromakowski < >>> vincent.gromakow...@gmail.com> wrote: >>> >>>> Ignite works only with spark 1.5 >>>> Ignite leverage indexes >>>> Alluxio provides tiering >>>> Alluxio easily integrates with underlying FS >>>> >>>> Le 27 oct. 2016 12:39 PM, "Mich Talebzadeh" <mich.talebza...@gmail.com> >>>> a écrit : >>>> >>>>> Thanks Chanh, >>>>> >>>>> Can it share RDDs. >>>>> >>>>> Personally I have not used either Alluxio or Ignite. >>>>> >>>>> >>>>> 1. Are there major differences between these two >>>>> 2. Have you tried Alluxio for sharing Spark RDDs and if so do you >>>>> have any experience you can kindly share >>>>> >>>>> Regards >>>>> >>>>> >>>>> 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 27 October 2016 at 11:29, Chanh Le <giaosu...@gmail.com> wrote: >>>>> >>>>>> Hi Mich, >>>>>> Alluxio is the good option to go. >>>>>> >>>>>> Regards, >>>>>> Chanh >>>>>> >>>>>> On Oct 27, 2016, at 5:28 PM, Mich Talebzadeh < >>>>>> mich.talebza...@gmail.com> wrote: >>>>>> >>>>>> >>>>>> There was a mention of using Zeppelin to share RDDs with many users. >>>>>> From the notes on Zeppelin it appears that this is sharing UI and I am >>>>>> not >>>>>> sure how easy it is going to be changing the result set with different >>>>>> users modifying say sql queries. >>>>>> >>>>>> There is also the idea of caching RDDs with something like Apache >>>>>> Ignite. Has anyone really tried this. Will that work with multiple >>>>>> applications? >>>>>> >>>>>> It looks feasible as RDDs are immutable and so are registered >>>>>> tempTables etc. >>>>>> >>>>>> 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. >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>> >>> >
