Autonomic physical database design – from indexing to multidimensional clustering

Abstract

Database design is a well-studied and well-understood problem in developing database applications. However, modern application requirements in terms of query response time, query throughput, database sizes, database maintenance and database interactivity capabilities on the one hand, and the manifold features of modern DBMS for physical schema design such as numerous different index structures, materialized views, partitioning, and clustering schemes on the other hand make high demands on the database design process. With this growing number of impact factors on physical database design automatic solutions have been developed and are provided in most systems, while research in this area still continues. In this paper, we give a survey on the state of the art in autonomic physical design. Starting with the classic index tuning problem and possible solutions, we describe further design problems such as choosing materializations of aggregations for OLAP and multidimensional clustering schemes. Finally, we point out to most recent challenges resulting from a shift in requirements and give a direction on how to tackle these.