H-DB: a hybrid quantitative-structural sql optimizer

Structural decomposition methods are query optimization methods specifically conceived in the database theory community to efficiently answer (near-)acyclic queries. We propose to demonstrate H-DB, an SQL query optimizer that combines classical quantitative optimization techniques with such structural decomposition methods, which so far have been just analyzed from the theoretical viewpoint. The system provides support to optimizing SQL queries with arbitrary output variables, aggregate operators, ORDER BY statements, and nested queries. H-DB can be put on top of any existing database management system supporting JDBC technology, by transparently interacting/replacing its standard query optimization module. However, to push at maximum its optimization capabilities, H-DB should be coupled with an ad-hoc physical semi-join operator, which (as a relevant example) we implemented and integrated within the PostgreSQL database management system.