Abstract: Complex Event Processing (CEP) is a technical method that comes with streaming data. It is used to find interesting event patterns in event streams that are mixed in different data sources. However, with the increasing amount of data, the traditional CEP techniques often fail to address the processing needs for efficient access to event patterns on big data sets. In response to this problem, this paper combines the idea of cluster analysis and association rules in data mining, proposes a “complex event processing” algorithm, and deploys it to the distributed platform Hadoop, thereby discovering the relationship between complex events in 〖JP2〗big data sets and effectively changing the limitations of traditional technologies facing massive data. Finally, the algorithm is applied to GPS big data set and the complex event patterns are found out. Experiments show that the method is feasible and effective.

Key words: complex event, event pattern, big data, cluster analysis, association rule