I have some scenarios where I would like to drill down to the lowest granularity of my table, does Kylin handle this?
If I am not mistaken a least one "group by" should always be used. So I tried to query by grouping by all my dimensions at the same time : "select dim1, dim2, ..., dimN, sum(measure1), ..., sum(measureN) from ... where ... group by dim1, dim2, ..., dimN". This gives me the expected results. Is this the correct way to do it? Although this seems to work, with several dimension it would mean building a lot of cubes and using a lot of space whereas in this case it would not necessarily be used. I know that aggregation groups can be used to solve reduce this. With the same example I created 1 aggregation group for each dimension and the expansion rate is 200%, but I tested only on 5 dimensions. Again, is this the correct way to do it? Relative to this topic, I saw: v0.7.x: InvertedIndex (HybridOLAP) Goal: Introduce InvertedIndex to optimise queries on raw data and low level aggregation on https://issues.apache.org/jira/browse/KYLIN-577 Is this something that is currently available in 0.7.2? This ticket dates back from beginning 2015, so I am not sure if it reflects Kylin current plan or not.
