Multimodal query support in database servers

This paper introduces a novel approach to optimizing and monitoring database queries which involve operations on multiple data types in a parallel multimedia engine. Our approach uses dataflow graphs to represent the multimedia operations in a query. We have extended the Actors parallel programming model by designing an agent model for query execution that incorporates extensions for efficient data streaming, agent migration, and agent cloning. We incorporate algorithms for dynamic run-time workload control of both the number of queries in the system as well as the number of instances of agents executing multimedia operators. We describe an approach for capturing cost statistics for user-defined functions that is used by the system to estimate and schedule the execution of nested user-defined functions