Incremental view materialization in deductive databases

This paper presents a unifying approach to processing of (recursive) querie s and updates in a deductive database. To improve query performance, a comb ined top-down and bottom-up evaluation method is used to compile rules into iterative programs that contain relational algebra operators. This method is based on the lemma resolution that retains previous results to guarantee termination. Due to locality in database processing (i.e. repetitive user query patterns ), it is desirable to materialize frequently used queries against views of the database. Unfortunately, if updates are allowed, maintaining materializ ed view tables becomes a major problem. We propose to materialize views inc rementally, as queries are being answered. Hence views in our approach are only partially materialized. For such views, we design algorithms to perfor m updates only when the underlying view tables are actually affected. We compare our approach to two well-known methods for dealing with views: t otal materialization and query-modification. The first method materializes the entire view when it is defined while the second recomputes the view on the fly without maintaining any physical view tables. We demonstrate that o ur approach is a compromise between these two methods by determining the co nditions under which it performs better.