Performance issue when multiple columns of same table are grouped

All we need is an easy explanation of the problem, so here it is.

I am dealing with large amount of data approx 1 million rows with 100s of columns.
I have this proc which performs some calculation over this data based on grouped by a colum1.

Now the same calculation is performed over this data grouped by column1, column2.

I can optimise the whole operation by creating indexes on column1 and column2.
But how i can achive the performance if column1 or column2 are dynamic and up to nth column.

Example:
For n columns the group by operation is going to be like as follows

operation 1 : group by column1
Operation 2 : group by column1, column2

Operation n : group by column1, column2….. upto columN

How to solve :

I know you bored from this bug, So we are here to help you! Take a deep breath and look at the explanation of your problem. We have many solutions to this problem, But we recommend you to use the first method because it is tested & true method that will 100% work for you.

Method 1

If you need all those aggregates at once use ROLLUP or GROUPING SETS to calculate multiple aggregate grains in a single scan.

If you want to optimize a large table for many different aggregates use a Columnstore index.

Note: Use and implement method 1 because this method fully tested our system.
Thank you 🙂

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0

Leave a Reply