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Discussion board for questions about the Qlik Community, its features, sharing information, general discussions and even some fun. This is for both new and longtime community members. Everyone is welcome!
I have a straight table with a calculated dimension using the aggr() function. The dimension for the aggr function is a field of several million values. I then make selections in some other filters, and should reduce the possible values of the aggr dimension to several thousands. However, charting of the straight table still takes several minutes.
So, my questions are as following:
1. Is it appropriate to use aggr() over a dimension of millions of values to create a dimension in a straight table?
2. Can reducing possible values of the dimension of the aggr() reduce time of charting the table?
3. If it is no to 1. and 2 above, what alternatives can I have for a better performance?
The report is historical data analysis. I also wonder what data model technique is appropriate for trending analysis with QlikView. I would appreciate for any suggestions and/or examples on this.