Depending on how many rows and how many count distinct values are returned, the query may take much memory and become slow.
By saying querying uv of a month data, how many rows do you expect? Also what's the precision of the HLL measure? Lower the precision can ease the problem too. On Fri, Jul 29, 2016 at 4:54 PM, 张天生 <[email protected]> wrote: > I'm using kylin 1.5.2.1. I built a cube for a month's event data of > advertisment impression/click/conversion. It consists of 6 dimensions and 8 > measures. It consists of 2 uv measures, and uv measure was computed by > DISTINCT COUNT. The cube size is 2G. When i queried uv measures of a month > data, the memory quickly increased to 30G+, and the quey was also slowly. I > don't known why it occupied so much memory, but cube size is only 2G, > memory data expanded so big. Hower, when i executed simple silimar sum or > count query ,it was fast and occupied memory not too much. >
