Semantic query optimization for tree and chain queries

Semantic query optimization, or knowledge-based query optimization, has received increasing interest in recent years. The authors provide an effective and systematic approach to optimizing queries by appropriately choosing semantically equivalent transformations. Basically, there are two different types of transformations: transformations by eliminating unnecessary joins, and transformations by adding/eliminating redundant beneficial/nonbeneficial selection operations (restrictions). A necessary and sufficient condition to eliminate a single unnecessary join is provided. We prove that it is 𝒩𝒫-𝒞omplete to eliminate as many unnecessary joins as possible for various types of acyclic queries with the exception of the closure chain queries whose query graphs are chains and all equi-join attributes are distinct. An algorithm is provided to minimize the number of joins in tree queries. This algorithm has an important property that, when applied to a closure chain query, it will yield an optimal solution with the time complexity O(n*m), where n is the number of relations referenced in the chain query, and m is the time complexity of a restriction closure computation