Hi, I'm also considering something similar, Spark plain is too slow for my case, a possible solution is use Spark as Multiple Source connector and basic transformation layer, then persist the information (actually is a RDBM), after that with our engine we build a kind of Cube queries, and the result is processed again by Spark adding Machine Learning. Our Missing part is reemplace the RDBM with something more suitable and scalable than RDBM, dont care about pre processing information if after pre processing the queries are fast.
Regards On Mon, Nov 9, 2015 at 3:56 PM, tsh <t...@timshenkao.su> wrote: > Hi, > > I'm in the same position right now: we are going to implement something > like OLAP BI + Machine Learning explorations on the same cluster. > Well, the question is quite ambivalent: from one hand, we have terabytes > of versatile data and the necessity to make something like cubes (Hive and > Hive on HBase are unsatisfactory). From the other, our users get accustomed > to Tableau + Vertica. > So, right now I consider the following choices: > 1) Platfora (not free, I don't know price right now) + Spark > 2) AtScale + Tableau(not free, I don't know price right now) + Spark > 3) Apache Kylin (young project?) + Spark on YARN + Kafka + Flume + some > storage > 4) Apache Phoenix + Apache HBase + Mondrian + Spark on YARN + Kafka + > Flume (has somebody use it in production?) > 5) Spark + Tableau (cubes?) > > For myself, I decided not to dive into Mesos. Cassandra is hardly > configurable, you'll have to dedicate special employee to support it. > > I'll be glad to hear other ideas & propositions as we are at the beginning > of the process too. > > Sincerely yours, Tim Shenkao > > > On 11/09/2015 09:46 AM, fightf...@163.com wrote: > > Hi, > > Thanks for suggesting. Actually we are now evaluating and stressing the > spark sql on cassandra, while > > trying to define business models. FWIW, the solution mentioned here is > different from traditional OLAP > > cube engine, right ? So we are hesitating on the common sense or direction > choice of olap architecture. > > And we are happy to hear more use case from this community. > > Best, > Sun. > > ------------------------------ > fightf...@163.com > > > *From:* Jörn Franke <jornfra...@gmail.com> > *Date:* 2015-11-09 14:40 > *To:* fightf...@163.com > *CC:* user <user@spark.apache.org>; dev <d...@spark.apache.org> > *Subject:* Re: OLAP query using spark dataframe with cassandra > > Is there any distributor supporting these software components in > combination? If no and your core business is not software then you may want > to look for something else, because it might not make sense to build up > internal know-how in all of these areas. > > In any case - it depends all highly on your data and queries. You will > have to do your own experiments. > > On 09 Nov 2015, at 07:02, "fightf...@163.com" <fightf...@163.com> wrote: > > Hi, community > > We are specially interested about this featural integration according to > some slides from [1]. The SMACK(Spark+Mesos+Akka+Cassandra+Kafka) > > seems good implementation for lambda architecure in the open-source world, > especially non-hadoop based cluster environment. As we can see, > > the advantages obviously consist of : > > 1 the feasibility and scalability of spark datafram api, which can also > make a perfect complement for Apache Cassandra native cql feature. > > 2 both streaming and batch process availability using the ALL-STACK thing, > cool. > > 3 we can both achieve compacity and usability for spark with cassandra, > including seemlessly integrating with job scheduling and resource > management. > > Only one concern goes to the OLAP query performance issue, which mainly > caused by frequent aggregation work between daily increased large tables, > for > > both spark sql and cassandra. I can see that the [1] use case facilitates > FiloDB to achieve columnar storage and query performance, but we had > nothing more > > knowledge. > > Question is : Any guy had such use case for now, especially using in your > production environment ? Would be interested in your architeture for > designing this > > OLAP engine using spark + cassandra. What do you think the comparison > between the scenario with traditional OLAP cube design? Like Apache Kylin > or > > pentaho mondrian ? > > Best Regards, > > Sun. > > > [1] > <http://www.slideshare.net/planetcassandra/cassandra-summit-2014-interactive-olap-queries-using-apache-cassandra-and-spark> > http://www.slideshare.net/planetcassandra/cassandra-summit-2014-interactive-olap-queries-using-apache-cassandra-and-spark > > ------------------------------ > fightf...@163.com > > > -- Ing. Ivaldi Andres
