Hi, According to my experience, I would recommend option 3) using Apache Kylin for your requirements.
This is a suggestion based on the open-source world. For the per cassandra thing, I accept your advice for the special support thing. But the community is very open and convinient for prompt response. fightf...@163.com From: tsh Date: 2015-11-10 02:56 To: fightf...@163.com; user; dev Subject: Re: OLAP query using spark dataframe with cassandra 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 Date: 2015-11-09 14:40 To: fightf...@163.com CC: user; dev 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 fightf...@163.com
