J-D, I would say that querying is secondary because there is Impala. Plus, Drill is another one. The developers don’t need to be involved there. But, the wow factor for most would be the ability to upsert data into Kudu programmatically using DataFrames (SQLContext). When this is available, we would move more earnestly to using Kudu as a viable solution and migrate from HBase. If you didn’t know, HBase is a pain to work with.
Cheers,Ben > On Apr 11, 2016, at 8:22 AM, Jean-Daniel Cryans <jdcry...@apache.org> wrote: > > Ben, > > Thanks for the additional information. You know, I was expecting that > querying would be the most important part and writing into Kudu was secondary > since it can easily be done with the Java API, but you guys are proving me > wrong. > > I'm starting to think we should host a Spark + Kudu hackathon here in the Bay > Area. Bringing experts together from both sides might unlock some potential. > We did that with Drill and it was successful: > https://issues.apache.org/jira/browse/DRILL-4241 > <https://issues.apache.org/jira/browse/DRILL-4241> > > J-D > > On Sun, Apr 10, 2016 at 1:03 PM, Benjamin Kim <bbuil...@gmail.com > <mailto:bbuil...@gmail.com>> wrote: > J-D, > > Priority is data population of tables using DataFrames. That’s all I heard > the most. It is the same with HBase. But, I bet once this is taken care of, > the fast querying part would follow because the data is now in Kudu. If > SparkSQL integration is there, that would simplify things even more. That > wouldn’t be bad to have. > > Cheers, > Ben > > >> On Apr 10, 2016, at 12:23 PM, Jean-Daniel Cryans <jdcry...@apache.org >> <mailto:jdcry...@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 <bbuil...@gmail.com >> <mailto:bbuil...@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 <jdcry...@apache.org >>> <mailto:jdcry...@apache.org>> wrote: >>> >>> On Sun, Apr 10, 2016 at 12:30 AM, Benjamin Kim <bbuil...@gmail.com >>> <mailto:bbuil...@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 <jdcry...@apache.org >>>> <mailto:jdcry...@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 <bbuil...@gmail.com >>>> <mailto:bbuil...@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 <jdcry...@apache.org >>>>> <mailto:jdcry...@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 <b...@amobee.com >>>>> <mailto:b...@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 <jdcry...@apache.org >>>>>> <mailto:jdcry...@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 <bbuil...@gmail.com >>>>>> <mailto:bbuil...@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 <jdcry...@apache.org >>>>>>> <mailto:jdcry...@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 <bbuil...@gmail.com >>>>>>> <mailto:bbuil...@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 >>>>>>> >>>>>>> >>>>>> >>>>>> >>>>> >>>>> >>>> >>>> >>> >>> >> >> > >
