Multi-query optimization of sliding window aggregates

Dr. Lukasz Golab
AT&T Labs--Research, Florham Park, NJ


Abstract

Database management systems (DBMSs) have been used successfully in business applications that require persistent storage of relatively static data. However, emerging applications, such as sensor networks, real-time Internet traffic analysis and on-line financial trading, require support for continuous processing of unbounded streams of data. The fundamental assumption of a data stream management system (DSMS) is that new data are generated continually, making it infeasible to store a stream in its entirety. At best, we may be able to maintain a sliding window of recently arrived data. Furthermore, since the contents of a sliding window evolve over time, it makes sense for users to ask a query once and receive updated answers over time. In this talk, I will describe my recent research on shared processing of continuous aggregation queries over sliding windows.