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From Mark Hamstra <m...@clearstorydata.com>
Subject Re: Spark on Kudu
Date Mon, 11 Apr 2016 16:34:00 GMT
It's pretty simple, actually.  I need to support versioned datasets in a
Spark SQL environment.  Instead of a hack on top of a Parquet data store,
I'm hoping (among other reasons) to be able to use Kudu's write and
timestamp-based read operations to support not only appending data, but
also updating existing data, and even some schema migration.  The most
typical use case is a dataset that is updated periodically (e.g., weekly or
monthly) in which the the preliminary data in the previous window (week or
month) is updated with values that are expected to remain unchanged from
then on, and a new set of preliminary values for the current window need to
be added/appended.

Using Kudu's Java API and developing additional functionality on top of
what Kudu has to offer isn't too much to ask, but the ease of integration
with Spark SQL will gate how quickly we would move to using Kudu and how
seriously we'd look at alternatives before making that decision.

On Mon, Apr 11, 2016 at 8:14 AM, Jean-Daniel Cryans <jdcryans@apache.org>
wrote:

> Mark,
>
> Thanks for taking some time to reply in this thread, glad it caught the
> attention of other folks!
>
> On Sun, Apr 10, 2016 at 12:33 PM, Mark Hamstra <mark@clearstorydata.com>
> wrote:
>
>> Do they care being able to insert into Kudu with SparkSQL
>>
>>
>> I care about insert into Kudu with Spark SQL.  I'm currently delaying a
>> refactoring of some Spark SQL-oriented insert functionality while trying to
>> evaluate what to expect from Kudu.  Whether Kudu does a good job supporting
>> inserts with Spark SQL will be a key consideration as to whether we adopt
>> Kudu.
>>
>
> I'd like to know more about why SparkSQL inserts in necessary for you. Is
> it just that you currently do it that way into some database or parquet so
> with minimal refactoring you'd be able to use Kudu? Would re-writing those
> SQL lines into Scala and directly use the Java API's KuduSession be too
> much work?
>
> Additionally, what do you expect to gain from using Kudu VS your current
> solution? If it's not completely clear, I'd love to help you think through
> it.
>
>
>>
>> On Sun, Apr 10, 2016 at 12:23 PM, Jean-Daniel Cryans <jdcryans@apache.org
>> > wrote:
>>
>>> Yup, starting to get a good idea.
>>>
>>> What are your DS folks looking for in terms of functionality related to
>>> Spark? A SparkSQL integration that's as fully featured as Impala's? Do they
>>> care being able to insert into Kudu with SparkSQL or just being able to
>>> query real fast? Anything more specific to Spark that I'm missing?
>>>
>>> FWIW the plan is to get to 1.0 in late Summer/early Fall. At Cloudera
>>> all our resources are committed to making things happen in time, and a more
>>> fully featured Spark integration isn't in our plans during that period. I'm
>>> really hoping someone in the community will help with Spark, the same way
>>> we got a big contribution for the Flume sink.
>>>
>>> J-D
>>>
>>> On Sun, Apr 10, 2016 at 11:29 AM, Benjamin Kim <bbuild11@gmail.com>
>>> wrote:
>>>
>>>> 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>
>>>> 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>
>>>>> 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>
>>>>> 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>
>>>>>> 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>
>>>>>> 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 <%2B1%20818%20635%202900>*
>>>>>>> 3250 Ocean Park Blvd, Suite 200  |  Santa Monica, CA 90405  |
>>>>>>> www.amobee.com
>>>>>>>
>>>>>>> On Feb 24, 2016, at 3:51 PM, Jean-Daniel Cryans <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>
>>>>>>> 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> 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
>>>>>>>>
>>>>>>>> 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>
>>>>>>>> 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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