流处理系统的网络感知算子配置

P. Pietzuch, J. Ledlie, Jeffrey Shneidman, M. Roussopoulos, M. Welsh, M. Seltzer
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引用次数: 474

摘要

为了有效地使用资源池,分布式流处理系统将查询操作符推送到网络中的节点。目前,这些操作符(从简单的过滤器到自定义业务逻辑)被手动放置在传输路径上的中间节点上,以满足特定于应用程序的性能目标。由于网络和节点的条件会随着时间的推移而变化,而且数据流可能会相互作用,从而为运营商的再利用和重新定位开辟场地,因此确定放置位置是一项挑战。本文描述了一种基于流的覆盖网络(SBON),它是流处理系统和物理网络之间的一层,用于管理流处理系统的操作员位置。我们的设计基于成本空间,网络和持续流的抽象表示,它允许分散的,大规模的多查询优化决策。我们通过模拟、PlanetLab上的实验以及与现有流处理引擎Borealis的集成,对SBON方法进行了评估。我们的研究结果表明,SBON可以持续提高网络利用率,提供低流延迟,并以低工程成本实现动态优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Network-Aware Operator Placement for Stream-Processing Systems
To use their pool of resources efficiently, distributed stream-processing systems push query operators to nodes within the network. Currently, these operators, ranging from simple filters to custom business logic, are placed manually at intermediate nodes along the transmission path to meet application-specific performance goals. Determining placement locations is challenging because network and node conditions change over time and because streams may interact with each other, opening venues for reuse and repositioning of operators. This paper describes a stream-based overlay network (SBON), a layer between a stream-processing system and the physical network that manages operator placement for stream-processing systems. Our design is based on a cost space, an abstract representation of the network and on-going streams, which permits decentralized, large-scale multi-query optimization decisions. We present an evaluation of the SBON approach through simulation, experiments on PlanetLab, and an integration with Borealis, an existing stream-processing engine. Our results show that an SBON consistently improves network utilization, provides low stream latency, and enables dynamic optimization at low engineering cost.
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