data are generated naturally during the measurement and monitoring
of complex, dynamic phenomena (such as traffic evolution in internet
and telephone communication infrastructures, usage of the web,
email and newsgroups, movement of financial markets, atmospheric
conditions, etc.), and also by (message-based) web services, in
which loosely coupled systems interact by exchanging high volumes
of business data (e.g., purchase orders, retail transactions)
tagged in XML (the lingua franca of web services). The applications
that operate on modern data streams require sophisticated queries
to continuously match, correlate, extract and transform parts
of the data stream.
stream data presents many technical challenges and is an active
research area in the database community, involving new stream
operators, SQL extensions, query optimization methods, operator
scheduling techniques, etc., with the goal of developing general-purpose
(e.g., NiagaraCQ, Stanford Stream, Telegraph, Aurora) and specialized
(e.g., Gigascope) data stream management systems.
objective of this tutorial is to provide a comprehensive and cohesive
overview of the key research results in the area of data stream
query processing, both for SQL-like and XML query languages.
tutorial is example driven, and organized as follows.
Applications, Query Processing Architectures: Data stream applications,
data and query characteristics, query processing architectures
of commercial and prototype systems.
SQL Query Processing: Filters, simple and complex joins, aggregation,
SQL extensions, approximate answers, query optimization methods,
operator scheduling techniques.
XML Query Processing: Automata- and navigation-based techniques
for single and multiple XPath queries, connections with stream
SQL query processing.
target audience of this tutorial includes researchers in database
systems, database and Web application developers, and the XML
Koudas is a Principal Technical Staff Member at AT&T Labs-Research.
He holds a Ph.D. from the University of Toronto, a M.Sc. from
the University of Maryland at College Park, and a B.Tech. from
the University of Patras in Greece. He serves as an associate
editor for the Information Systems journal and the IEEE TKDE journal.
He is the recipient of the 1998 ICDE Best Paper award. His research
interests include core database management, metadata management
and its applications to networking.
Srivastava is the head of the Database Research Department
at AT&T Labs-Research. He received his Ph.D. from the University
of Wisconsin, Madison, and his B.Tech. from the Indian Institute
of Technology, Bombay, India, He was a vice-chair of ICDE 2002,
and is on the editorial board of the ACM SIGMOD Digital Review.
His current research interests include XML databases, IP network
data management, and data quality.