关系数据库即服务的灵活资源分配

Pankaj Arora, Surajit Chaudhuri, Sudipto Das, Junfeng Dong, Cyril George, Ajay Kalhan, A. König, Willis Lang, Changsong Li, Feng Li, Jiaqi Liu, Lukas M. Maas, Akshay Mata, Ishai Menache, Justin Moeller, Vivek R. Narasayya, Matthaios Olma, Morgan Oslake, Elnaz Rezai, Yi Shan, Manoj Syamala, Shize Xu, Vasileios Zois
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引用次数: 0

摘要

对于云数据库提供商来说,超额订购是一项重要的成本管理策略,而无服务器数据库这一新兴模式则放大了超额订购的重要性。与管理程序、操作系统和集群管理器中用于超额订购的通用技术不同,我们开发的技术利用了我们对数据库管理系统如何使用资源以及资源分配如何影响数据库性能的理解。我们的技术旨在以较低的开销在节点和集群级别灵活地重新分配数据库租户的资源。我们已经在商业云数据库服务中实现了我们的技术:Azure SQL 数据库。使用微基准、行业标准基准和实际资源使用跟踪进行的实验表明,使用我们的方法,即使超量订阅程度相对较高,也能严格控制对数据库性能的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible Resource Allocation for Relational Database-as-a-Service
Oversubscription is an essential cost management strategy for cloud database providers, and its importance is magnified by the emerging paradigm of serverless databases. In contrast to general purpose techniques used for oversubscription in hypervisors, operating systems and cluster managers, we develop techniques that leverage our understanding of how DBMSs use resources and how resource allocations impact database performance. Our techniques are designed to flexibly redistribute resources across database tenants at the node and cluster levels with low overhead. We have implemented our techniques in a commercial cloud database service: Azure SQL Database. Experiments using microbenchmarks, industry-standard benchmarks and real-world resource usage traces show that using our approach, it is possible to tightly control the impact on database performance even with a relatively high degree of oversubscription.
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