FYI, the doc for streaming cubing is published in website: https://kylin.apache.org/docs15/tutorial/cube_streaming.html
2016-05-04 14:13 GMT+08:00 Li Yang <liy...@apache.org>: > Shaofeng is working on a document about Kafka and streaming cubing. Let's > wait. > > On Tue, May 3, 2016 at 11:26 PM, Nick Dimiduk <ndimi...@apache.org> wrote: > > > Very nice talk, thank you. That helped put many things into context for > me. > > I will resume my study of the code for understanding engine > implementation > > details. > > > > One final question -- is there a doc for getting started with the > > experimental Kafka integration? > > > > Thanks, > > Nick > > > > On Tue, May 3, 2016 at 2:45 AM, Li Yang <liy...@apache.org> wrote: > > > > > It's complicated. As of Kylin 1.5, there are two flavors of cubing > > > algorithm. Below talk covered a bit. There's no comprehensive document > at > > > the moment. > > > > > > https://www.youtube.com/watch?v=n74zvLmIgF0 > > > > > > > > > On Tue, May 3, 2016 at 7:52 AM, Nick Dimiduk <ndimi...@apache.org> > > wrote: > > > > > > > Hi there, > > > > > > > > I'm curious to understand how Kylin goes about building cubes. I've > > > > deployed it on a single-node cluster and played around with the > sample > > > cube > > > > [0]. Now i'm looking through the kylin server log and the code in the > > > > 'engine-mr'. I'm not finding much in the way of docs in the source > code > > > > though :( > > > > > > > > Is there any presentation, blog post, &c that gives and overview of > > these > > > > internals? I did find [1] but I'm looking go descend another level. > I'm > > > > curious about the various steps involved (looks like it ran 18 > "steps" > > > and > > > > 10 MR jobs), what they're doing. I'm also curious about the schema > > design > > > > for the data model in HBase. > > > > > > > > Thanks in advance! > > > > -n > > > > > > > > [0]: http://kylin.apache.org/docs15/tutorial/kylin_sample.html > > > > [1]: http://www.slideshare.net/YangLi43/design-cube-in-apache-kylin > > > > > > > > > > -- Best regards, Shaofeng Shi
