Continuous Queries over Data Streams

Abstract

In many recent applications, data may take the form of continuous data streams, rather than nite stored data sets. Several aspects of data management need to be re- considered in the presence of data streams, offering a new research direction for the database community. In this pa- per we focus primarily on the problem of query process- ing, specically on how to dene and evaluate continuous queries over data streams. We address semantic issues as well as efciency concerns. Our main contributions are threefold. First, we specify a general and exible architec- ture for query processing in the presence of data streams. Second, we use our basic architecture as a tool to clar- ify alternative semantics and processing techniques for continuous queries. The architecture also captures most previous work on continuous queries and data streams, as well as related concepts such as triggers and materialized views. Finally, we map out research topics in the area of query processing over data streams, showing where pre- vious work is relevant and describing problems yet to be addressed.

Introduction