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在 2014年12月30日星期二 UTC+8下午6:30:17，Li Yang写道： > > What Xu described is the ultimate goal in this direction -- realtime! > > For this feature, it is less in scope by focusing on the micro segment of > cube building. The goal is to reduce cube data delay to be within one hour. > > Realtime is on the long term roadmap of course! We will come to it when > inverted index is mature. > > Cheers > Yang > > > 在 2014年12月25日星期四UTC+8下午1时14分58秒，Luke Han写道： >> >> Github Issues for tracking this new feature: >> https://github.com/KylinOLAP/Kylin/issues/262 >> >> >> >> 在 2014年12月25日星期四UTC+8上午7时11分49秒，Branky Shao写道： >>> >>> Xu, thanks for your comment. For our internal use cases like Nous, the >>> query pattern is determinate. Defining "popular path" can be treated as an >>> additional step in cube modeling and only queries on "popular path" are >>> most optimized. >>> On Tuesday, December 23, 2014 6:37:23 PM UTC-8, Jiang Xu wrote: >>>> >>>> "popular path" is a kind of partial cube materialization that is highly >>>> depended on the query pattern. Since we can't predict the user's query >>>> pattern, I have some concerns about the query performance. >>>> >>>> I think that the more important thing is to bring real-time capability >>>> into Kylin. It includes 3 things: >>>> >>>> 1. real time build in-memory storage. >>>> I suggest to build bitmap index instead of cube in memory. Kafka & >>>> Storm is a good option. >>>> >>>> 2. real-time query in-memory storage. >>>> We need a distributed execution engine for real-time query. I have some >>>> concerns about the RPC mechanism of Storm. >>>> >>>> 3. dump in-memory storage into hadoop. >>>> Storm is a good opinion for it. >>>> >>>> >>>>
