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| Content Provider | ACM Digital Library |
|---|---|
| Author | Levy, Alon Manolescu, Ioana Florescu, Daniela Suciu, Dan |
| Abstract | We consider the problem of query optimization in the presence of limitations on access patterns to the data (i.e., when one must provide values for one of the attributes of a relation in order to obtain tuples). We show that in the presence of limited access patterns we must search a space of annotated query plans, where the annotations describe the inputs that must be given to the plan. We describe a theoretical and experimental analysis of the resulting search space and a novel query optimization algorithm that is designed to perform well under the different conditions that may arise. The algorithm searches the set of annotated query plans, pruning invalid and non-viable plans as early as possible in the search space, and it also uses a best-first search strategy in order to produce a first complete plan early in the search. We describe experiments to illustrate the performance of our algorithm. |
| Starting Page | 311 |
| Ending Page | 322 |
| Page Count | 12 |
| File Format | |
| ISSN | 01635808 |
| DOI | 10.1145/304181.304210 |
| Journal | ACM SIGMOD Record (SGMD) |
| Volume Number | 28 |
| Issue Number | 2 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1999-06-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Information Systems Software |
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