Evaluating the effect of cardinality estimates on two state-of-the-art query optimizer's selection of access method

Abstract: This master thesis concern relational databases and their query optimizer’s sensitivity to cardinality estimates and the e!ect the quality of the estimate has on the number of different access methods used for the same relation. Two databases are evaluated — PostgreSQL and MariaDB — on a real-world dataset to provide realistic results. The evaluation was done via a tool implemented in Clojure and tests were conducted on a query and subsets of it with varying sample sizes used when estimating cardinality. The results indicate that MariaDB’s query optimizer is less sensitive to cardinality estimates and for all tests select the same access methods, regardless of the quality of the cardinality estimate. This stands in contrast to PostgreSQL’s query optimizer which will vary between using an index or doing a full table scan depending on the estimated cardinality. Finally, it is also found that the predicate value used in the query a!ects the access method used. Both PostgreSQL and MariaDB are found sensitive to this property, with MariaDB having the largest number of di!erent access methods used depending on predicate value.