云多租数据库资源规划调度技术综述
Survey on Resource Planning and Scheduling Technologies for Multi-tenant Cloud Databases
刘海龙 1王硕 1侯舒峰 1徐海洋 1李战怀1
作者信息
- 1. 西北工业大学计算机学院,陕西 西安 710072;大数据存储与管理工业和信息化部重点实验室(西北工业大学),陕西 西安 710072
- 折叠
摘要
云多租数据库具有按需付费、按需扩展、免部署、高可用、自带运维能力、资源共享等诸多优势,可以大大降低用户使用数据库服务的成本.现在越来越多的企业和个人开始在数据库即服务(DaaS)平台托管他们的数据库服务.DaaS平台需要按照用户服务水平协议(SLA)为诸多租户提供服务,同时也需要保障平台收益.但是,由于租户及其负载具有动态性、异构性和竞争性等特点,如何在遵循SLA的同时根据负载自适应规划调度资源同时兼顾平台收益对于DaaS平台来说是一件极具挑战性的工作.针对云多租数据库中比较常见的类型,如关系型数据库,详细分析了当前云多租数据库资源规划调度技术所面临的挑战,提炼了关键科学问题,给出了技术框架,然后从资源规划调度技术、资源预估技术、资源弹性伸缩技术以及数据库资源规划调度工具等 4 个方面对现有研究工作进行了总结和分析,并且展望了未来的研究方向.
Abstract
Multi-tenant cloud databases offer services more cheaply and conveniently,with advantages like paying on demand,scaling on demand,automatic deployment,high availability,self-maintenance,and shared resources.Now more and more enterprises and individuals begin to host their database services on database as a service(DaaS)platforms.These DaaS platforms provide services to multiple tenants in accordance with their service-level agreements(SLAs),while improving revenue for themselves.However,due to the dynamic,heterogeneous,and competitive characteristics of multiple tenants and their loads,it is a very challenging task for DaaS platform providers to adaptively plan and schedule resources according to dynamic loads while complying with multi-tenants'SLAs.For common types of multi-tenant cloud databases,such as relational databases,this survey firstly analyzes the challenges faced by resource planning and scheduling of multi-tenant cloud databases in detail and then outlines related key scientific issues.Then,it provides a framework of related techniques and a summary of existing research in four areas:resource planning and scheduling technologies,resource forecasting technologies,resource elastic scaling technologies,and resource planning and scheduling tools for existing databases.Lastly,this survey provides suggestions for future research directions on resource planning and scheduling technologies for multi-tenant cloud databases.
关键词
多租户/云数据库/资源规划调度/资源预估/资源弹性伸缩/关系数据库/云原生/多模数据库Key words
multi-tenant/cloud database/resource planning and scheduling/resource estimation/resource elastic scaling/relational database/cloud-native/multi-model database引用本文复制引用
出版年
2025
NETL
NSTL
万方数据