The optimization process allows you to create sampled optimizer statistics on database tables. For large tables, sampled statistics are usually much faster to generate than full statistics, and if the percentage of rows to be sampled is chosen appropriately, they can be nearly as accurate.

Sampled statistics are generated by only looking at a certain percentage of the rows in a table. The percentage must be chosen so that all significant variations in the data distribution are likely to be sampled.

The sampled rows are selected by randomly generating values for the tuple identifier (tid), so tid values are required to support this functionality.