Abstract
A Data Warehouse (DW) can be seen as a set of materialized views defined over remote source relations. During the initial design and evolution of a DW, the DW designer is faced, on many occasions, with the problem of selecting views to materialize in the DW. This problem has been addressed for different classes of queries/views, and with different design goals. In this work we unify these approaches in a general framework for materialized view selection for Data Warehousing. We first identify and analyze different design goals. A design goal can be the minimization of a cost function or a constrain t of different types. We then define the general view selection problem that aims at satisfying all these goals together. This definition of the problem allows us to deal not only with the static design of a DW, but also with its evolution. We use expression AND/OR dags to represen t alternative ways of evaluating multiple queries and views, and subexpression sharing. Our formalism is general enough to allow the representation of complex queries including grouping/aggregation queries, necessary in DW applications. We show how the design goals can be mapped into conditions on expression AND/OR dag structures. Using this mapping, we determine the search space for the general view selection problem, and we discuss algorithms for exploring it. Our approach can be used as is but it can be also applied to particular D W design cases where not all the design goals are required.
Original language | English (US) |
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Title of host publication | Proceedings of the 3rd ACM International Workshop on Data Warehousing and OLAP, DOLAP 2000 |
Publisher | Association for Computing Machinery |
Pages | 1-8 |
Number of pages | 8 |
Volume | Part F129125 |
ISBN (Electronic) | 1581133235 |
DOIs | |
State | Published - Nov 1 2000 |
Externally published | Yes |
Event | 3rd ACM International Workshop on Data Warehousing and OLAP, DOLAP 2000 - McLean, United States Duration: Nov 6 2000 → Nov 11 2000 |
Other
Other | 3rd ACM International Workshop on Data Warehousing and OLAP, DOLAP 2000 |
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Country/Territory | United States |
City | McLean |
Period | 11/6/00 → 11/11/00 |
All Science Journal Classification (ASJC) codes
- Computer Science(all)