MTopS: scalable processing of continuous top-k multi-query workloads

A continuous top-k query retrieves the k most preferred objects in a data stream according to a given preference function. These queries are important for a broad spectrum of applications ranging from web-based advertising to financial analysis. In various streaming applications, a large number of such continuous top-k queries need to be executed simultaneously against a common popular input stream. To efficiently handle such top-k query workload, we present a comprehensive framework, called MTopS. Within this MTopS framework, several computational components work collaboratively to first analyze the commonalities across the workload; organize the workload for maximized sharing opportunities; execute the workload queries simultaneously in a shared manner; and output query results whenever any input query requires. In particular, MTopS supports two proposed algorithms, MTopBand and MTopList, which both incrementally maintain the top-k objects over time for multiple queries. As the f...

• Type: Journal
• Year: 2011
• Where: CIKM
• Authors: Avani Shastri, Di Yang, Elke A. Rundensteiner, Matthew O. Ward
• Keywords: CIKM 2011, Cpu Time Usage, Information Systems Applications, Information Technology, Preference Function