Access plan optimization

Access plans can be optimized in an attempt to improve query performance. The degree of improvement depends on the type of optimization chosen. Optimizing access plans is one of the best ways to ensure that the query compiler behaves the way you expect and design it to.

You can utilize cardinality estimation models using the AI Query Optimizer. The AI Query Optimizer solution for cardinality estimation uses a learned model for estimating cardinality. If there are one or more supported local predicates on columns included in the model, the optimizer can compute the selectivity estimate from the model. The selectivity estimate is the ratio of rows qualifying the predicates as a fraction of the number of rows in the table. These selectivity estimates are combined independently with the selectivity of any remaining predicates not supported by the model.