1. Data cube is multi-dimensional array that is basically key-value data model. HBase is ordered key-value storage that is suitable for cube data model and query processing. 2. Kylin is focus on Hadoop. HBase is seamlessly integrate with MR, HDFS, HIVE. 3. HBase is scale out that is suitable to store large volume data set. 4. HBase coprocessor provide server-side parallel processing that is suitable for push-down computation and parallel the query processing.
Thanks JiangXu ------------------ ???????? ------------------ ??????: hongbin ma <[email protected]> ????????: 2015??05??27?? 12:47 ??????: dev <[email protected]> ????: Re: Choice of HBASE On Wed, May 27, 2015 at 12:35 PM, Sarnath <[email protected]> wrote: > Is it because Cube data can grow exponentially (2^N) with increasing > dimensions? > ?6?7this is one of the most important reasons. We applied many optimization to avoid curse of dimensions, but the cube size can still grow very large, especially when distinct count appears in metrics?6?7 -- Regards, *Bin Mahone | ??????* Apache Kylin: http://kylin.io Github: https://github.com/binmahone
