Continuous Queries over Data Streams

May 26, 2005
Arvind Arasu | Stanford University

Continuous queries are a common interface for monitoring dynamically changing data, including data streams. Applications include tracking financial trends, network health monitoring, and sensor deployments.

In the STREAM project at Stanford, we have built a comprehensive prototype system that supports rich, declarative continuous queries over data streams.

In this talk I will focus on continuous aggregation queries and address the following three problem settings.

A large number of queries: Here a primary challenge is to share resources (e.g., space, computation) across different queries.
Limited memory: Here the challenge is to design algorithms for maintaining approximate statistics making the best use of available memory.
Distributed systems: Here a primary challenge is to minimize communication while correlating events on distributed streams.

I will conclude with a brief summary of my other work, including continuous query language design and semantics, and characterizing memory requirements for continuous queries.

Speaker Details

Arvind Arasu is a PhD candidate at Stanford University working with Prof. Jennifer Widom. He received his M.S. in Computer Science from Stanford University in 2001 and a B.Tech in Computer Science from Indian Institute of Technology, Madras in 1999, where he won the President of India Gold Medal for the best academic performance in his class. His research interests are broadly in the area of information management. They include query processing and optimization, web information management, and information extraction.