Continuous queries over data streams

In many recent applications, data may take the form of continuous data stre ams, rather than finite stored data sets. Several aspects of data managemen t need to be reconsidered in the presence of data streams, offering a new r esearch direction for the database community. In this paper we focus primar ily on the problem of query processing, specifically on how to define and e valuate continuous queries over data streams. We address semantic issues as well as efficiency concerns, Our main contributions are threefold. First, we specify a general and flexible architecture for query processing in the presence of data streams. Second, we use our basic architecture as a tool t o clarify alternative semantics and processing techniques for continuous qu eries. The architecture also captures most previous work on continuous quer ies and data streams, as well as related concepts such as triggers and mate rialized views. Finally, we map out research topics in the area of query pr ocessing over data streams, showing where previous work is relevant and des cribing problems yet to be addressed.