Optimization techniques for queries with expensive methods
ACM Transactions on Database Systems (TODS)
Optimization of queries with user-defined predicates
ACM Transactions on Database Systems (TODS)
Approximate Selection Queries over Imprecise Data
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Adaptive ordering of pipelined stream filters
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Content-based routing: different plans for different data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Window-aware load shedding for aggregation queries over data streams
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A semantic approach for building pervasive spaces
Proceedings of the 6th Middleware Doctoral Symposium
Dynamic query optimisation: towards decentralised methods
International Journal of Intelligent Information and Database Systems
Mobile Information Systems
Multimedia selection operation placement
Multimedia Tools and Applications
| Hi-index | 0.00 |
Modern query optimizers need to take into account the performance of expensive user-defined predicates. Existing research has shown how to incorporate such predicates in a traditional cost-based query optimizer. In this paper we deal with the optimization of the expensive predicates themselves, showing how their cost can be reduced by utilizing cheaper, but less accurate, versions of the predicates to pre-filter tuples. We discuss the generalized tuple handling mechanism, which processes tuples along a fixed sequence of versions, as well as adaptive approaches that either split tuple streams into groups, or make routing decisions at the individual tuple level. We identify the lower bound to the problem of evaluating a multi-version selection predicate by an ideal individualized plan (IIP), and develop an optimal generalized plan (OGP). We then show how realistic individualized or grouped schemes can produce an intermediate cost between OGP and IIP, if tuples substantially deviate from the average stream behavior. Our algorithms are tested experimentally, identifying many of the issues that arise whenever multi-version predicates are used.