No Pane, No Gain: Efficient Evaluation of Sliding-Window Aggregates over Data Streams

摘要

Window queries are proving essential to data-stream processing. In this paper, we present an approach for evaluating sliding-window aggregate queries that reduces both space and computation time for query execution. Our approach divides overlapping windows into disjoint panes, computes sub-aggregates over each pane, and "rolls up" the pane-aggregates to compute window-aggregates. Our experimental study shows that using panes has significant performance benefits.