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Event processing with dynamically changing focus: Doctoral consortium paper

机译:焦点动态变化的事件处理:博士联合论文

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Event Processing technologies are likely to play an increasingly important role in future IT systems due to the increasing demand for on-line analytical systems as well as big data processing applications. Event Processing is particularly suitable for those applications due to its active processing approach combined with scalability. Today's approaches for achieving scalability are however focused on rather static event stream partitioning mechanisms to allow parallelization. Such approaches are well suited as long as a feasible partitioning for all processing tasks can be found. However when such a scaling mechanism is faced with processing tasks with dynamically changing focus areas, no effective pre-determined partitioning can be found which massively hampers with the required scalability. This paper presents the first steps towards a focused processing framework to overcome these limitations.
机译:由于对在线分析系统以及大数据处理应用程序的需求不断增加,事件处理技术可能在未来的IT系统中扮演越来越重要的角色。事件处理由于其主动处理方法和可伸缩性而特别适合那些应用程序。但是,当今实现可伸缩性的方法集中在相当静态的事件流分区机制上,以允许并行化。只要可以找到所有处理任务的可行分区,这些方法就非常适用。但是,当这种缩放机制面临着具有动态变化的焦点区域的处理任务时,就找不到有效的预定分区,这大大妨碍了所需的可伸缩性。本文介绍了克服这些限制的重点处理框架的第一步。

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