Departmental Papers (CIS)

Date of this Version

June 2000

Document Type

Journal Article


Copyright 2000 IEEE. Reprinted from Bulletin of the Technical Committee on Data Engineering, IEEE Computer Society, Volume 23, Issue 2, June 2000, pages 19-26.

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

NOTE: At the time of publication, author Zachary Ives was affiliated with the University of Washington. Currently (April 2005), he is a faculty member in the Department of Computer and Information Science at the University of Pennsylvania.


As the area of data management for the Internet has gained in popularity, recent work has focused on effectively dealing with unpredictable, dynamic data volumes and transfer rates using adaptive query processing techniques. Important requirements of the Internet domain include: (1) the ability to process XML data as it streams in from the network, in addition to working on locally stored data; (2) dynamic scheduling of operators to adjust to I/O delays and flow rates; (3) sharing and re-use of data across multiple queries, where possible; (4) the ability to output results and later update them. An equally important consideration is the high degree of variability in performance needs for different query processing domains: perhaps an ad-hoc query application should optimize for display of incomplete and partial incremental results, whereas a corporate data integration application may need the best time-to-completion and may have very strict data "freshness" guarantees. The goal of the Tukwila project at the University of Washington is to design a query processing system that supports a range of adaptive techniques that are configurable for different query processing contexts.



Date Posted: 09 May 2005

This document has been peer reviewed.