Information systems produce different types of event logs; in many situations, it may be desirable to look for trends inside these logs. We show how trends of various kinds can be computed over such logs in real time, using a generic framework called the trend distance workflow. Many common computations on event streams turn out to be special cases of this workflow, depending on how a handful of workflow parameters are defined. This process has been implemented and tested in a real-world event stream processing tool, called BeepBeep. Experimental results show that deviations from a reference trend can be detected in realtime for streams producing up to thousands of events per second.

信息系统产生不同类型的事件日志；在许多情况下，可能希望在这些日志中查找趋势。我们展示了如何使用称为趋势距离工作流程的通用框架实时计算此类日志中的各种趋势。事件流的许多常见计算结果都是此工作流的特殊情况，具体取决于如何定义几个工作流参数。此过程已在称为BeepBeep的实际事件流处理工具中实施和测试。实验结果表明，对于每秒产生多达数千个事件的流，可以实时检测到与参考趋势的偏差。