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From Benjamin Kim <bbuil...@gmail.com>
Subject Re: Spark on Kudu
Date Sun, 10 Apr 2016 18:29:20 GMT
Yes, we took Kudu for a test run using 0.6 and 0.7 versions. But, since it’s not “production-ready”,
upper management doesn’t want to fully deploy it yet. They just want to keep an eye on it
though. Kudu was so much simpler and easier to use in every aspect compared to HBase. Impala
was great for the report writers and analysts to experiment with for the short time it was
up. But, once again, the only blocker was the lack of Spark support for our Data Developers/Scientists.
So, production-level data population won’t happen until then.

I hope this helps you get an idea where I am coming from…

Cheers,
Ben

> On Apr 10, 2016, at 11:08 AM, Jean-Daniel Cryans <jdcryans@apache.org> wrote:
> 
> On Sun, Apr 10, 2016 at 12:30 AM, Benjamin Kim <bbuild11@gmail.com <mailto:bbuild11@gmail.com>>
wrote:
> J-D,
> 
> The main thing I hear that Cassandra is being used as an updatable hot data store to
ensure that duplicates are taken care of and idempotency is maintained. Whether data was directly
retrieved from Cassandra for analytics, reports, or searches, it was not clear as to what
was its main use. Some also just used it for a staging area to populate downstream tables
in parquet format. The last thing I heard was that CQL was terrible, so that rules out much
use of direct queries against it.
> 
> I'm no C* expert, but I don't think CQL is meant for real analytics, just ease of use
instead of plainly using the APIs. Even then, Kudu should beat it easily on big scans. Same
for HBase. We've done benchmarks against the latter, not the former.
>  
> 
> As for our company, we have been looking for an updatable data store for a long time
that can be quickly queried directly either using Spark SQL or Impala or some other SQL engine
and still handle TB or PB of data without performance degradation and many configuration headaches.
For now, we are using HBase to take on this role with Phoenix as a fast way to directly query
the data. I can see Kudu as the best way to fill this gap easily, especially being the closest
thing to other relational databases out there in familiarity for the many SQL analytics people
in our company. The other alternative would be to go with AWS Redshift for the same reasons,
but it would come at a cost, of course. If we went with either solutions, Kudu or Redshift,
it would get rid of the need to extract from HBase to parquet tables or export to PostgreSQL
to support more of the SQL language using by analysts or the reporting software we use..
> 
> Ok, the usual then *smile*. Looks like we're not too far off with Kudu. Have you folks
tried Kudu with Impala yet with those use cases?
>  
> 
> I hope this helps.
> 
> It does, thanks for nice reply.
>  
> 
> Cheers,
> Ben 
> 
>> On Apr 9, 2016, at 2:00 PM, Jean-Daniel Cryans <jdcryans@apache.org <mailto:jdcryans@apache.org>>
wrote:
>> 
>> Ha first time I'm hearing about SMACK. Inside Cloudera we like to refer to "Impala
+ Kudu" as Kimpala, but yeah it's not as sexy. My colleagues who were also there did say that
the hype around Spark isn't dying down.
>> 
>> There's definitely an overlap in the use cases that Cassandra, HBase, and Kudu cater
to. I wouldn't go as far as saying that C* is just an interim solution for the use case you
describe.
>> 
>> Nothing significant happened in Kudu over the past month, it's a storage engine so
things move slowly *smile*. I'd love to see more contributions on the Spark front. I know
there's code out there that could be integrated in kudu-spark, it just needs to land in gerrit.
I'm sure folks will happily review it.
>> 
>> Do you have relevant experiences you can share? I'd love to learn more about the
use cases for which you envision using Kudu as a C* replacement.
>> 
>> Thanks,
>> 
>> J-D
>> 
>> On Fri, Apr 8, 2016 at 12:45 PM, Benjamin Kim <bbuild11@gmail.com <mailto:bbuild11@gmail.com>>
wrote:
>> Hi J-D,
>> 
>> My colleagues recently came back from Strata in San Jose. They told me that everything
was about Spark and there is a big buzz about the SMACK stack (Spark, Mesos, Akka, Cassandra,
Kafka). I still think that Cassandra is just an interim solution as a low-latency, easily
queried data store. I was wondering if anything significant happened in regards to Kudu, especially
on the Spark front. Plus, can you come up with your own proposed stack acronym to promote?
>> 
>> Cheers,
>> Ben
>> 
>> 
>>> On Mar 1, 2016, at 12:20 PM, Jean-Daniel Cryans <jdcryans@apache.org <mailto:jdcryans@apache.org>>
wrote:
>>> 
>>> Hi Ben,
>>> 
>>> AFAIK no one in the dev community committed to any timeline. I know of one person
on the Kudu Slack who's working on a better RDD, but that's about it.
>>> 
>>> Regards,
>>> 
>>> J-D
>>> 
>>> On Tue, Mar 1, 2016 at 11:00 AM, Benjamin Kim <bkim@amobee.com <mailto:bkim@amobee.com>>
wrote:
>>> Hi J-D,
>>> 
>>> Quick question… Is there an ETA for KUDU-1214? I want to target a version of
Kudu to begin real testing of Spark against it for our devs. At least, I can tell them what
timeframe to anticipate.
>>> 
>>> Just curious,
>>> Benjamin Kim
>>> Data Solutions Architect
>>> 
>>> [a•mo•bee] (n.) the company defining digital marketing.
>>> 
>>> Mobile: +1 818 635 2900 <tel:%2B1%20818%20635%202900>
>>> 3250 Ocean Park Blvd, Suite 200  |  Santa Monica, CA 90405  |  www.amobee.com
<http://www.amobee.com/>
>>> 
>>>> On Feb 24, 2016, at 3:51 PM, Jean-Daniel Cryans <jdcryans@apache.org <mailto:jdcryans@apache.org>>
wrote:
>>>> 
>>>> The DStream stuff isn't there at all. I'm not sure if it's needed either.
>>>> 
>>>> The kuduRDD is just leveraging the MR input format, ideally we'd use scans
directly.
>>>> 
>>>> The SparkSQL stuff is there but it doesn't do any sort of pushdown. It's
really basic.
>>>> 
>>>> The goal was to provide something for others to contribute to. We have some
basic unit tests that others can easily extend. None of us on the team are Spark experts,
but we'd be really happy to assist one improve the kudu-spark code.
>>>> 
>>>> J-D
>>>> 
>>>> On Wed, Feb 24, 2016 at 3:41 PM, Benjamin Kim <bbuild11@gmail.com <mailto:bbuild11@gmail.com>>
wrote:
>>>> J-D,
>>>> 
>>>> It looks like it fulfills most of the basic requirements (kudu RDD, kudu
DStream) in KUDU-1214. Am I right? Besides shoring up more Spark SQL functionality (Dataframes)
and doing the documentation, what more needs to be done? Optimizations?
>>>> 
>>>> I believe that it’s a good place to start using Spark with Kudu and compare
it to HBase with Spark (not clean).
>>>> 
>>>> Thanks,
>>>> Ben
>>>> 
>>>> 
>>>>> On Feb 24, 2016, at 3:10 PM, Jean-Daniel Cryans <jdcryans@apache.org
<mailto:jdcryans@apache.org>> wrote:
>>>>> 
>>>>> AFAIK no one is working on it, but we did manage to get this in for 0.7.0:
https://issues.cloudera.org/browse/KUDU-1321 <https://issues.cloudera.org/browse/KUDU-1321>
>>>>> 
>>>>> It's a really simple wrapper, and yes you can use SparkSQL on Kudu, but
it will require a lot more work to make it fast/useful.
>>>>> 
>>>>> Hope this helps,
>>>>> 
>>>>> J-D
>>>>> 
>>>>> On Wed, Feb 24, 2016 at 3:08 PM, Benjamin Kim <bbuild11@gmail.com
<mailto:bbuild11@gmail.com>> wrote:
>>>>> I see this KUDU-1214 <https://issues.cloudera.org/browse/KUDU-1214>
targeted for 0.8.0, but I see no progress on it. When this is complete, will this mean that
Spark will be able to work with Kudu both programmatically and as a client via Spark SQL?
Or is there more work that needs to be done on the Spark side for it to work?
>>>>> 
>>>>> Just curious.
>>>>> 
>>>>> Cheers,
>>>>> Ben
>>>>> 
>>>>> 
>>>> 
>>>> 
>>> 
>>> 
>> 
>> 
> 
> 


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