In my opinion, choosing some particular project among its peers should leave enough room for future growth (which may come faster than you initially think).
Cheers On Fri, Aug 7, 2015 at 11:23 AM, Hien Luu <h...@linkedin.com> wrote: > Scalability is a known issue due the the current architecture. However > this will be applicable if you run more 20K jobs per day. > > On Fri, Aug 7, 2015 at 10:30 AM, Ted Yu <yuzhih...@gmail.com> wrote: > >> From what I heard (an ex-coworker who is Oozie committer), Azkaban is >> being phased out at LinkedIn because of scalability issues (though UI-wise, >> Azkaban seems better). >> >> Vikram: >> I suggest you do more research in related projects (maybe using their >> mailing lists). >> >> Disclaimer: I don't work for LinkedIn. >> >> On Fri, Aug 7, 2015 at 10:12 AM, Nick Pentreath <nick.pentre...@gmail.com >> > wrote: >> >>> Hi Vikram, >>> >>> We use Azkaban (2.5.0) in our production workflow scheduling. We just >>> use local mode deployment and it is fairly easy to set up. It is pretty >>> easy to use and has a nice scheduling and logging interface, as well as >>> SLAs (like kill job and notify if it doesn't complete in 3 hours or >>> whatever). >>> >>> However Spark support is not present directly - we run everything with >>> shell scripts and spark-submit. There is a plugin interface where one could >>> create a Spark plugin, but I found it very cumbersome when I did >>> investigate and didn't have the time to work through it to develop that. >>> >>> It has some quirks and while there is actually a REST API for adding jos >>> and dynamically scheduling jobs, it is not documented anywhere so you kinda >>> have to figure it out for yourself. But in terms of ease of use I found it >>> way better than Oozie. I haven't tried Chronos, and it seemed quite >>> involved to set up. Haven't tried Luigi either. >>> >>> Spark job server is good but as you say lacks some stuff like scheduling >>> and DAG type workflows (independent of spark-defined job flows). >>> >>> >>> On Fri, Aug 7, 2015 at 7:00 PM, Jörn Franke <jornfra...@gmail.com> >>> wrote: >>> >>>> Check also falcon in combination with oozie >>>> >>>> Le ven. 7 août 2015 à 17:51, Hien Luu <h...@linkedin.com.invalid> a >>>> écrit : >>>> >>>>> Looks like Oozie can satisfy most of your requirements. >>>>> >>>>> >>>>> >>>>> On Fri, Aug 7, 2015 at 8:43 AM, Vikram Kone <vikramk...@gmail.com> >>>>> wrote: >>>>> >>>>>> Hi, >>>>>> I'm looking for open source workflow tools/engines that allow us to >>>>>> schedule spark jobs on a datastax cassandra cluster. Since there are >>>>>> tonnes >>>>>> of alternatives out there like Ozzie, Azkaban, Luigi , Chronos etc, I >>>>>> wanted to check with people here to see what they are using today. >>>>>> >>>>>> Some of the requirements of the workflow engine that I'm looking for >>>>>> are >>>>>> >>>>>> 1. First class support for submitting Spark jobs on Cassandra. Not >>>>>> some wrapper Java code to submit tasks. >>>>>> 2. Active open source community support and well tested at production >>>>>> scale. >>>>>> 3. Should be dead easy to write job dependencices using XML or web >>>>>> interface . Ex; job A depends on Job B and Job C, so run Job A after B >>>>>> and >>>>>> C are finished. Don't need to write full blown java applications to >>>>>> specify >>>>>> job parameters and dependencies. Should be very simple to use. >>>>>> 4. Time based recurrent scheduling. Run the spark jobs at a given >>>>>> time every hour or day or week or month. >>>>>> 5. Job monitoring, alerting on failures and email notifications on >>>>>> daily basis. >>>>>> >>>>>> I have looked at Ooyala's spark job server which seems to be hated >>>>>> towards making spark jobs run faster by sharing contexts between the jobs >>>>>> but isn't a full blown workflow engine per se. A combination of spark job >>>>>> server and workflow engine would be ideal >>>>>> >>>>>> Thanks for the inputs >>>>>> >>>>> >>>>> >>> >> >
