In bigdata analytics platform, we often query data of the nature week or nature month.
For example, in Bank or Accounting reports, the query periods are often a natural week or natural month report.
In kylin system, we can build cube to increase query speed. However, it will query slowly if the amount of data is large and the query cycle is long especlially using count distinct measure.
For example, We can add month dimension to the cube, then merge cube in normal month peroid; but if the query sql has date partition, it will also match the cube has both week dimension and date dimension, kylin need search data from HBase and aggregate data in memory. It also slowly if the amountof data is large.
Does anyone face the same problem? Who has a better way to solve the problems of nature week or nature month query?