Addressing resource usage in stream processing systems: sizing window effect

Abstract

Stream processing systems compute continuous queries over increasingly large volumes of data, as monitoring applications emerge in a broad array of fields. These systems need to satisfy application-dependent constraints, one of the most important ones being accuracy demands and query response times. As system resources are limited, various query optimization techniques are proposed. To the best of our knowledge, none of the existing methods takes into account the size of the window, which is input to a query. We believe resource usage can be tackled with a novel approach, that attempts to compute an optimal window size for a given continuous query, thereby placing a minimal upper bound on the resource consumption for that query.