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From Ted Yu <yuzhih...@gmail.com>
Subject Re: Spark job workflow engine recommendations
Date Fri, 07 Aug 2015 17:30:00 GMT
>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.pentreath@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 <jornfranke@gmail.com> wrote:
>
>> Check also falcon in combination with oozie
>>
>> Le ven. 7 août 2015 à 17:51, Hien Luu <hluu@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 <vikramkone@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
>>>>
>>>
>>>
>

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