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wonkymeister
Creator III
Creator III

Link Table & Optimisation

Hi,

one of my apps is getting rather large now, and becoming rather slow. I started to think about optimisation, and looking at what i could do to improve the app.

The app uses a couple of link tables, where datasets need to be joined that are aggregated at different levels, and as this is the only solution that i know, i was wondering if there is a better, faster way?

As i say, as an example, dataset A is at its lowest level whereas dataset B is aggregated up - think of it in terms of sales and targets where targets aren't set at individual item (lowest level), but at product type level (aggregated up).

I tried concatenating the two tables, and although they share some similar fields, each dataset just ended up padded with nulls at the join.

cheers.

1 Solution

Accepted Solutions
marcus_sommer

Multiple linktables within the datamodel are the worst approach from a performance point of view - the more you are able to merge the tables the better will be the UI performance. To get NULL's within rows/columns by joining/mapping or concatenating is often no problem within the calculations or the performance. Also the match of mixed granularities is in general possible, for example: Fact Table with Mixed Granularity.

- Marcus

View solution in original post

2 Replies
marcus_sommer

Multiple linktables within the datamodel are the worst approach from a performance point of view - the more you are able to merge the tables the better will be the UI performance. To get NULL's within rows/columns by joining/mapping or concatenating is often no problem within the calculations or the performance. Also the match of mixed granularities is in general possible, for example: Fact Table with Mixed Granularity.

- Marcus

wonkymeister
Creator III
Creator III
Author

cheers - i will investigate!