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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Pebbles: Leveraging Sketches for Processing Voluminous, High Velocity Data Streams
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Pebbles: Leveraging Sketches for Processing Voluminous, High Velocity Data Streams

机译:鹅卵石:利用草图来处理庞大的高速数据流

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摘要

Voluminous, time-series data streams originating in continuous sensing environments pose data ingestion and processing challenges. We present a holistic methodology centered around data sketching to address both challenges. We introduce an order-preserving sketching algorithm that we have designed for space-efficient representation of multi-feature streams with native support for stream processing related operations. Observational streams are preprocessed at the edges of the network generating sketched streams to reduce data transfer costs and energy consumption. Ingested sketched streams are then processed using sketch-aware extensions to existing stream processing APIs delivering improved performance. Our benchmarks with real-world datasets show up to a similar to 8x reduction in data volumes transferred and a similar to 27x improvement in throughput.
机译:庞大,时间序列数据流源于连续感测环境,构成数据摄取和处理挑战。我们展示了一个全面的方法,以数据素描为中心,以解决这两个挑战。我们介绍了一个秩序保留的草图算法,我们设计用于具有用于流处理相关操作的本机支持的多特征流的节空节空间表示。观察流被预处理在网络的边缘生成草图流以降低数据传输成本和能量消耗。然后使用草图感知扩展来处理摄取的草图流,以提供改进的性能的现有流处理API。我们的基准与现实世界数据集显示出类似于8倍的数据卷减少,并且吞吐量的提高类似于27倍。

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