I have a simple cube with a Fact Table and a Lookup Table. The Fact Table includes some counter. The Lookup Table includes a region property which is the highest level of the hierarchy and therefore can accumulate quite a lot of data when summing the counter by region.
I am doing a query like this: select sum(MY_COUNTER) as tot_count, REGION from FACT_TABLE join LOOKUP_TABLE on FACT_TABLE.FK = LOOKUP_TABLE.PK where date = '2015-01-01' group by REGION I get the following result: -917,164,421 EMEA --> negative result! 777,795,808 AMER 514,879,134 APAC 117,814,485 LATAM I ran the exact same query in Hive and got the following result: 3,381,591,228 EMEA --> big number but smaller than the BIGINT limit 778,718,563 AMER --> 922,755 difference with the Kylin result 520,253,610 APAC --> 5,374,476 difference with the Kylin result 117,913,857 LATAM --> 99,372 difference with the Kylin result Based on that it seems that the limit is the int limit 2^31-1 (2,147,483,647) and that my negative result comes from an overflow. In my cube I defined this measure as a bigint: Expression Param Type Param Value Return Type SUM column AVAIL_COUNT bigint The other thing that worries me a bit is that the other numbers are not 100% accurate either (>100,000,000 difference!)
