About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
DEBS 2017
Tutorial
Sliding-Window Aggregation Algorithms: Tutorial
Abstract
Stream processing is important for analyzing continuous streams of data in real time. Sliding-window aggregation is both needed for many streaming applications and surprisingly hard to do efficiently. Picking the wrong aggregation algorithm causes poor performance, and knowledge of the right algorithms and when to use them is scarce. This paper was written to accompany a tutorial, but can be read as a stand-alone survey that aims to better educate the community about fast sliding-window aggregation algorithms for a variety of common aggregation operations and window types.