Efficient event pattern matching with match windows

In event pattern matching a sequence of input events is matched against a complex query pattern that specifies constraints on extent, order, values, and quantification of matching events. In this paper we propose a general pattern matching strategy that consists of a pre-processing step and a pattern matching step. Instead of eagerly matching incoming events, the pre-processing step buffers events in a match window to apply different pruning techniques (filtering, partitioning, and testing for necessary match conditions). In the second step, an event pattern matching algorithm, A , is called only for match windows that satisfy the necessary match conditions. This two-phase strategy with a lazy call of the matching algorithm significantly reduces the number of events that need to be processed by A as well as the number of calls to A . This is important since pattern matching algorithms tend to be expensive in terms of runtime and memory complexity, whereas the pre-processing can be done very efficiently. We conduct extensive experiments using real-world data with pattern matching algorithms for, respectively, automata and join trees. The experimental results confirm the effectiveness of our strategy for both types of pattern matching algorithms.