Our latest paper by Jan Kossmann as well as Thorsten Papenbrock and Felix Naumann from the Information Systems Group surveys the use of data dependencies (functional, inclusion, order dependencies, and unique column combinations) for query optimization. Such optimization techniques can lead to more efficient query plans, e.g., due to query rewriting or improved cardinality estimation. Please feel free to contact Jan Kossmann for questions and discussions.
Effective query optimization is a core feature of any database management system. While most query optimization techniques make use of simple metadata, such as cardinalities and other basic statistics, other optimization techniques are based on more advanced metadata including data dependencies, such as functional, uniqueness, order, or inclusion dependencies. This survey provides an overview, intuitive descriptions, and classifications of query optimization and execution strategies that are enabled by data dependencies. We consider the most popular types of data dependencies and focus on optimization strategies that target the optimization of relational database queries. The survey supports database vendors to identify optimization opportunities as well as DBMS researchers to find related work and open research questions.