Selectivity information in the graphical plan

In the example shown below, the selected node represents a scan of the Departments table, and the statistics pane shows the Predicate as the search condition, its selectivity estimation, and its real selectivity.

In the Details pane, statistics about an individual node are divided into three sections: Node Statistics, Subtree Statistics, and Optimizer Statistics.

Node statistics pertain to the execution of this specific node. If the node is not a leaf node in the plan, and therefore consumes an intermediate result(s) from other nodes, the Details pane shows a Subtree Statistics section that contains estimated and actual cumulative statistics for this node's entire subtree. Optimizer statistics information is present only for root nodes, which represent the entire SQL request.

Selectivity information may not be displayed for bypass queries. For more information about bypass queries, see How the optimizer works.

The access plan depends on the statistics available in the database, which, in turn, depends on what queries have previously been executed. You may see different statistics and plans from those shown here.

Graphical plan with statistics showing the predicate.

This predicate description is

Departments.DepartmentName = 'Sales' : 20% Column; true 1/5 20%

This can be read as follows:

  • Departments.DepartmentName = 'Sales' is the predicate.

  • 20% is the optimizer's estimate of the selectivity. That is, the optimizer is basing its query access selection on the estimate that 20% of the rows satisfy the predicate.

    This is the same output as is provided by the ESTIMATE function.

  • Column is the source of the estimate. This is the same output as is provided by the ESTIMATE_SOURCE function.

  • true 1/5 20% is the actual selectivity of the predicate during execution. The predicate was evaluated five times, and was true once, so its real selectivity is 20%.

    If the actual selectivity is very different from the estimate, and if the predicate was evaluated a large number of times, the incorrect estimates could cause a significant problem with query performance. Collecting statistics on the predicate may improve performance by giving the optimizer better information on which to base its choices.

Note

If you select the graphical plan, but not the graphical plan with statistics, the final two statistics are not displayed.

 See also