In general, tuning analytic functions (and more generally, all sort operations) is rather difficult. While for most poorly performing queries it’s relatively straightforward to gain some improvements by applying “eliminate early” principle one way or another, for slow sort operations it’s rarely applicable. Usually options are limiting to rewriting a query without analytics (e.g. using self-joins or correlated subqueries to achieve the same goal) or manually resizing the workarea to reduce/eliminate the use of disk. Recently, however, I had a case where I managed to obtain an excellent performance gain using a different technique that I would like to share in this post.
The original query was selecting about 100 columns using the LAG function on one of the columns in the WHERE clause, but in my test case I’ll both simplify and generalize the situation. Let’s create a table with a sequential id, three filtering columns x, y and z, and 20 sufficiently lengthy columns.
