Query optimization techniques for partitioned tables

Abstract

Table partitioning splits a table into smaller parts that can be accessed, stored, and maintained independent of one another. From their traditional use in improving query performance, partitioning strategies have evolved into a powerful mechanism to improve the overall manageability of database systems. Table partitioning simplifies administrative tasks like data loading, removal, backup, statistics maintenance, and storage provisioning. Query language extensions now enable applications and user queries to specify how their results should be partitioned for further use. However, query optimization techniques have not kept pace with the rapid advances in usage and user control of table partitioning. We address this gap by developing new techniques to generate efficient plans for SQL queries involving multiway joins over partitioned tables. Our techniques are designed for easy incorporation into bottom-up query optimizers that are in wide use today. We have prototyped these techniques in the PostgreSQL optimizer. An extensive evaluation shows that our partition-aware optimization techniques, with low optimization overhead, generate plans that can be an order of magnitude better than plans produced by current optimizers. © 2011 ACM.