SQPR:具有重用性的流查询规划

Evangelia Kalyvianaki, W. Wiesemann, Q. Vu, D. Kuhn, P. Pietzuch
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引用次数: 54

摘要

当用户向分布式流处理系统(DSPS)提交新的查询时,查询规划器必须从一组主机上为查询分配物理资源,如CPU内核、内存和网络带宽。分配决策必须提供查询所需资源的正确组合,同时实现有效的总体分配,以扩展所允许查询的数量。通过利用查询之间的重叠和重用部分结果,查询规划器可以节省资源,但必须执行更复杂的规划决策。在本文中,我们描述了SQPR,一种针对具有异构资源的数据中心环境中的dsb的查询规划器。SQPR模型将查询准入、分配和重用作为一个单一的约束优化问题,并解决一个近似的版本来实现可扩展性。它通过重新规划过去的分配决策来防止单个资源成为瓶颈,并支持不同的分配目标。与最先进的规划器相比,我们的实验评估表明,即使资源利用率很高,SQPR也能在可接受的开销下做出有效的资源分配决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SQPR: Stream query planning with reuse
When users submit new queries to a distributed stream processing system (DSPS), a query planner must allocate physical resources, such as CPU cores, memory and network bandwidth, from a set of hosts to queries. Allocation decisions must provide the correct mix of resources required by queries, while achieving an efficient overall allocation to scale in the number of admitted queries. By exploiting overlap between queries and reusing partial results, a query planner can conserve resources but has to carry out more complex planning decisions. In this paper, we describe SQPR, a query planner that targets DSPSs in data centre environments with heterogeneous resources. SQPR models query admission, allocation and reuse as a single constrained optimisation problem and solves an approximate version to achieve scalability. It prevents individual resources from becoming bottlenecks by re-planning past allocation decisions and supports different allocation objectives. As our experimental evaluation in comparison with a state-of-the-art planner shows SQPR makes efficient resource allocation decisions, even with a high utilisation of resources, with acceptable overheads.
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