CDSBen: Benchmarking the Performance of Storage Services in Cloud-Native Database System at ByteDance

IF 2.6 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the Vldb Endowment Pub Date : 2023-08-01 DOI:10.14778/3611540.3611549
Jiashu Zhang, Wen Jiang, Bo Tang, Haoxiang Ma, Lixun Cao, Zhongbin Jiang, Yuanyuan Nie, Fan Wang, Lei Zhang, Yuming Liang
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Abstract

In this work, we focus on the performance benchmarking problem of storage services in cloud-native database systems, which are widely used in various cloud applications. The core idea of these systems is to separate computation and storage in traditional monolithic OLTP databases. Specifically, we first present the characteristics of two representative real I/O workloads at the storage tier of ByteDance's cloud-native database veDB. We then elaborate the limitations of using standard benchmarks such as TPC-C and YCSB to resemble these workloads. To overcome these limitations, we devise a learning-based I/O workload benchmark called CDS-Ben. We demonstrate the superiority of CDSBen by deploying it at ByteDance and showing that its generated I/O traces accurately resemble the real I/O traces in production. Additionally, we verify the accuracy and flexibility of CDSBen by generating a wide range of I/O workloads with different I/O characteristics.
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CDSBen:在ByteDance上对云原生数据库系统中的存储服务性能进行基准测试
在这项工作中,我们重点研究了云原生数据库系统中存储服务的性能基准测试问题,云原生数据库系统广泛应用于各种云应用。这些系统的核心思想是将传统的单片OLTP数据库中的计算和存储分离开来。具体来说,我们首先展示了字节跳动的云原生数据库veDB的存储层上两个具有代表性的真实I/O工作负载的特征。然后,我们详细说明了使用标准基准(如TPC-C和YCSB)来模拟这些工作负载的局限性。为了克服这些限制,我们设计了一个基于学习的I/O工作负载基准,称为CDS-Ben。我们通过在ByteDance上部署CDSBen来展示它的优越性,并展示其生成的I/O轨迹与生产中的实际I/O轨迹非常相似。此外,我们还通过生成具有不同I/O特征的各种I/O工作负载来验证cdshen的准确性和灵活性。
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来源期刊
Proceedings of the Vldb Endowment
Proceedings of the Vldb Endowment Computer Science-General Computer Science
CiteScore
7.70
自引率
0.00%
发文量
95
期刊介绍: The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.
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