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Smart scheme: an efficient query execution scheme for event-driven stream processing

机译:智能方案:用于事件驱动流处理的有效查询执行方案

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摘要

With the increase in stream data, a demand for stream processing has become diverse and complicated. To meet this demand, several stream processing engines (SPEs) have been developed which execute continuous queries (CQs) to process continuous data streams. Event-driven stream processing, which is one of the important requirements, continuously gets the incoming stream data and, however, generates query results only on the occurrence of specified events. In the basic query execution scheme, even when no event is raised, input stream tuples are continuously processed by query operators, though they do not generate any query result. This results in increased system load and wastage of system resources. For this problem, we propose a smart event-driven stream processing scheme, which makes use of smart windows to buffer the stream tuples during the absence of an event. When the event is raised, the buffered tuples are flushed and processed by the downstream operators. If the buffered tuples in the smart window expire due to the window size before the occurrence of an event, they are deleted directly from the smart window. Since CQs once registered are executed for several weeks, months or even years, SPEs usually execute several CQs in parallel and merge their query plans whenever possible to save processing cost. Due to the presence of smart window, existing multi-query optimization techniques cannot work for smart event-driven stream processing. Hence, this work proposes a multi-query optimization for the proposed smart scheme to cover the cases where multiple continuous queries are registered. Extensive experiments are performed on real and synthetic data streams to show the effectiveness of the proposed smart scheme and its multi-query optimization.
机译:随着流数据的增加,流处理的需求已经变得多样化和复杂。为了满足这种需求,已经开发了几个流处理引擎(SPE),其执行连续查询(CQS)来处理连续数据流。事件驱动的流处理,这是一个重要要求之一,连续获取传入的流数据,但是,仅在发生指定事件的发生时生成查询结果。在基本查询执行方案中,即使在没有提出事件时,也通过查询运算符连续处理输入流元组,但它们不会生成任何查询结果。这导致系统负荷增加和系统资源的浪费。对于此问题,我们提出了一种智能事件驱动的流处理方案,它利用智能窗口在不存在事件期间缓冲流元组。当事件提高时,缓冲元组被下游运营商刷新并处理。如果智能窗口中的缓冲元组因窗口大小发生在发生之前的窗口大小而过期,则它们将直接从智能窗口删除。由于CQS在注册后执行了数周,几个月甚至几年,因此SPE通常并行执行多个CQS,并在尽可能节省处理成本的情况下合并其查询计划。由于存在智能窗口,现有的多查询优化技术不能用于智能事件驱动的流处理。因此,这项工作提出了一种多查询优化,以便提出的智能方案,以涵盖注册多个连续查询的情况。对实际和合成数据流进行广泛的实验,以显示所提出的智能方案的有效性及其多查询优化。

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