Materialized views can provide massive improvements in query processing time, especially for aggregation queries over large tables. To achieve the potential of materialized views, we must determine what views to materialize. An important issue in view selection is view merging. View merging can take a set of candidate views generated by analyzing queries in a workload, and produce a set of merged views by exploiting commonality among those queries. View merging can efficiently reduce candidate views for view selection. In this paper we present a merging tree, as well as a fast and scalable algorithm for view merging based on such a tree. The merging tree can significantly reduce the search space of potential views to be merged. Our approach is more scalable than the alternative of sequentially merging all pairs of views every time.
展开▼
