Introduction to algorithms
Predicate migration: optimizing queries with expensive predicates
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Optimizing disjunctive queries with expensive predicates
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Query execution techniques for caching expensive methods
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Continuously adaptive continuous queries over streams
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Filtering with Approximate Predicates
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Probabilistic Optimization of Top N Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Offering a Precision-Performance Tradeoff for Aggregation Queries over Replicated Data
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Optimization of Queries with User-defined Predicates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Adaptive filters for continuous queries over distributed data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Aurora: a data stream management system
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
TelegraphCQ: continuous dataflow processing
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Predicate result range caching for continuous queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Principles of Computational Fluid Dynamics
Principles of Computational Fluid Dynamics
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Supporting user-defined functions on uncertain data
Proceedings of the VLDB Endowment
| Hi-index | 0.00 |
Many analysis applications require the ability to repeatedly execute sophisticated modeling functions, which can each take minutes or even hours to produce a single answer. Because of this expense, such applications have largely been unable to directly use such models in queries, with either on-demand or continuous query processing technology. Query processors are hindered in their ability to optimize expensive modeling functions due to the "black box" nature of existing user-defined function (UDF) interfaces. In this paper, we address the problem of querying over sophisticated models with the development of VAOs (Variable-Accuracy Operators). VAOs use a new function interface that exposes the trade-off between compute time and accuracy that exists in many modeling functions. Using this interface, VAOs adaptively run each function call in a query only to an accuracy needed to answer the query, thus eliminating unneeded work. In this paper, we present the design of VAOs for a set of common query operations. We show the effectiveness of VAOs using a prototype implementation running financial queries over real bond market data.