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Systems and methods for reservoir sampling of streaming data and stream joins

机译:用于流数据和流连接的储层采样的系统和方法

摘要

Algorithms and concepts for maintaining uniform random samples of streaming data and stream joins. These algorithms and concepts are used in systems and methods, such as wireless sensor networks and methods for implementing such networks, that generate and handle such streaming data and/or stream joins. The algorithms and concepts directed to streaming data allow one or more sample reservoirs to change size during sampling. When multiple reservoirs are maintained, some of the algorithms and concepts periodically reallocate memory among the multiple reservoirs to effectively utilize limited memory. The algorithms and concepts directed to stream joins allow reservoir sampling to proceed as a function of the probability of a join sampling operation. In memory limited situations wherein memory contains the sample reservoir and a join buffer, some of the stream join algorithms and concepts progressively increase the size of the sampling reservoir and reallocate memory from the join buffer to the reservoir.
机译:用于维护流数据和流连接的统一随机样本的算法和概念。这些算法和概念用在系统和方法中,例如无线传感器网络和用于实现这种网络的方法,该系统和方法生成并处理这种流数据和/或流联接。针对流数据的算法和概念允许一个或多个样本容器在采样期间改变大小。当维护多个存储库时,某些算法和概念会定期在多个存储库之间重新分配内存,以有效利用有限的内存。针对流连接的算法和概念允许根据连接采样操作的概率来进行储层采样。在存储器包含样本容器和连接缓冲区的内存受限情况下,某些流连接算法和概念会逐渐增加采样容器的大小,并将内存从连接缓冲区重新分配给容器。

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