Hi Kaisen, Good summary! Here I have several questions:
1) How did you test the end-to-end flow and also the accuracy of query result? Can it be included in Kylin's integration test? 2) How do we recommend the different storage engines to end user, HBase, Druid, and also the on-going Parquet storage? In my mind, HBase is mature, and provide an out-of-box experience on Hadoop; Parquet is simple, ease of deployment and scaling; Druid is good at performance on complex filtering, but the user needs to have a good knowledge of Druid's deployment and DevOps. Does this make sense? BTW, could you please open a JIRA for this new feature? Best regards, Shaofeng Shi 史少锋 Apache Kylin PMC Work email: [email protected] Kyligence Inc: https://kyligence.io/ Apache Kylin FAQ: https://kylin.apache.org/docs/gettingstarted/faq.html Join Kylin user mail group: [email protected] Join Kylin dev mail group: [email protected] kangkaisen <[email protected]> 于2018年11月18日周日 下午4:09写道： > Hi all, > > Meituan Kylin team has implemented a new storage engine for Kylin: Druid > Storage Engine. > The attach file is the Kylin On Druid Storage Engine architecture design > doc. > We would like to contribute the feature to community, please let us know if > you have any concern. > > Kylin_On_Druid_Storage.pdf > < > http://apache-kylin.74782.x6.nabble.com/file/t705/Kylin_On_Druid_Storage.pdf> > > > Thanks, > Kaisen Kang > > -- > Sent from: http://apache-kylin.74782.x6.nabble.com/ >
