> taking advantage of underlaying datasource capabilities (predicate pushdown, projection etc) is important to improve query performance.
That is very true. There was discussion about replacing HBase with Cassandra <http://apache-kylin.74782.x6.nabble.com/Cassandra-instead-of-HBase-in-Kylin-td2688.html> previously. And the worry is lack of coprocessor will prevent predicate & aggregation pushdown. Similar concern exists for Kudu. Cheers Yang On Fri, Mar 24, 2017 at 12:50 AM, Nirav Patel <[email protected]> wrote: > Thanks for logging those improvements. I think decision about replacing > Hbase or using any other nosql datastore for storing cubes would be based > on many factors but one important I can think of is the query > engine/optimizer of all of those datasources. I think taking advantage of > underlaying datasource capabilities (predicate pushdown, projection etc) is > important to improve query performance. > > Cheers, > Nirav > > On Mon, Mar 20, 2017 at 12:23 PM, Li Yang <[email protected]> wrote: > >> Hi Nirav, >> >> Glad to see you on the mailing list!! >> >> Yes, this is a great idea and it is on the roadmap. (This reminds me, I >> should update the roadmap on kylin website soon.) >> >> However there are many moving parts that affect how we approach it. E.g. >> >> - If coprocessor is retired, do we still need HBase? >> - If HBase is retired, what is the alternative storage? How about >> metadata? >> - There are other ways to integrate SparkSQL (KYLIN-2515), how do they >> fit in... >> >> There are many work in this direction, I would say. >> >> Cheers >> Yang >> >> On Tue, Mar 21, 2017 at 2:05 AM, Nirav Patel <[email protected]> >> wrote: >> >>> Hi, >>> >>> In recent strata conference I raised a question if kylin can support >>> sparkSQL as a query engine or have a kylin query resultset converted into >>> spark DataSet(DataFrame) on which user can perform further distributed >>> computation. >>> Reason are >>> 1) some flavor of Hbase doesnt support co-processor >>> 2) SparkSql UDF much easier to develop then hbase coprocessor >>> 3) User can write their own spark UDF and run any custom aggregation >>> >>> Is this on roadmap ? >>> >>> Thanks, >>> Nirav >>> >>> >>> >>> [image: What's New with Xactly] <http://www.xactlycorp.com/email-click/> >>> >>> <https://www.nyse.com/quote/XNYS:XTLY> [image: LinkedIn] >>> <https://www.linkedin.com/company/xactly-corporation> [image: Twitter] >>> <https://twitter.com/Xactly> [image: Facebook] >>> <https://www.facebook.com/XactlyCorp> [image: YouTube] >>> <http://www.youtube.com/xactlycorporation> >> >> >> > > > > [image: What's New with Xactly] <http://www.xactlycorp.com/email-click/> > > <https://www.nyse.com/quote/XNYS:XTLY> [image: LinkedIn] > <https://www.linkedin.com/company/xactly-corporation> [image: Twitter] > <https://twitter.com/Xactly> [image: Facebook] > <https://www.facebook.com/XactlyCorp> [image: YouTube] > <http://www.youtube.com/xactlycorporation> >
