Hi Manoj, Usually, we know the query pattern first, and then design the cube according to it.
For your question, if the query is among the 10 normal dimensions, the query should be fast; If you have derived column in query, Kylin need do a mapping from the FK to derived columns; If the derived column's cardinality is much less than FK's, that means a lot of aggregation would happen at query time, the performance would be impacted. 2017-12-18 12:19 GMT+08:00 Kumar, Manoj H <[email protected]>: > Can you pls. advise on this case – I have Cube built on for below case – > It has 234 dimension(224 dimensions are for Derived & 10 dimensions from > Fact table which are normal one). > > > > Fact table – 1 > > Dimension/look up table – 9 [ All these are linked to Fact table column > Mapping] > > > ------------------------------ > > *Model Name* > > Data_model > > *Cube Name* > > CUBE_1 > > *Fact Table* > > V_EP_FACT_ACTUALS > > *Lookup Table* > > 9 > > *Dimensions* > > 234 > > *Measures* > > 13 (Sum of Columns) > > > > > > User will be using Tableau Desktop to get the data viewed – which way I > should write the query to get faster response from Hbase Cube which > includes Dimensions & Fact table. Pls. advise. Pls. let me know if you need > any other information. > > > > Regards, > > Manoj > > > > This message is confidential and subject to terms at: http:// > www.jpmorgan.com/emaildisclaimer including on confidentiality, legal > privilege, viruses and monitoring of electronic messages. If you are not > the intended recipient, please delete this message and notify the sender > immediately. Any unauthorized use is strictly prohibited. > -- Best regards, Shaofeng Shi 史少锋
