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xMeta: SSD-HDD-Hybrid Optimization for Metadata Maintenance of Cloud-Scale Object Storage
ACM Transactions on Architecture and Code Optimization ( IF 1.6 ) Pub Date : 2024-03-13 , DOI: 10.1145/3652606
Yan Chen 1 , Qiwen Ke 2 , Huiba Li 3 , Yongwei Wu 4 , Yiming Zhang 2
Affiliation  

Object storage has been widely used in the cloud. Traditionally, the size of object metadata is much smaller than that of object data, and thus existing object storage systems (like Ceph and Oasis) can place object data and metadata respectively on hard disk drives (HDDs) and solid-state drives (SSDs) to achieve high I/O performance at a low monetary cost. Currently, however, a wide range of cloud applications organize their data as large numbers of small objects of which the data size is close to (or even smaller than) the metadata size, thus greatly increasing the cost if placing all metadata on expensive SSDs.

This paper presents xMeta, an SSD-HDD-hybrid optimization for metadata maintenance of cloud-scale object storage. We observed that a substantial portion of the metadata of small objects is rarely accessed and thus can be stored on HDDs with little performance penalty. Therefore, xMeta first classifies the hot and cold metadata based on the frequency of metadata accesses of upper-layer applications, and then adaptively stores the hot metadata on SSDs and the cold metadata on HDDs. We also propose a merging mechanism for hot metadata to further improve the efficiency of SSD storage, and optimize range key query and insertion for hot metadata by designing composite keys. We have integrated the xMeta metadata service with Ceph to realize a high-performance, low-cost object store (called xCeph). The extensive evaluation shows that xCeph outperforms the original Ceph by an order of magnitude in the space requirement of SSD storage, while improving the throughput by up to 2.7 ×.



中文翻译:

xMeta:用于云级对象存储元数据维护的 SSD-HDD 混合优化

对象存储在云中得到了广泛的应用。传统上,对象元数据的大小远小于对象数据的大小,因此现有的对象存储系统(如Ceph和Oasis)可以将对象数据和元数据分别放置在硬盘驱动器(HDD)和固态驱动器(SSD)上以较低的成本实现较高的 I/O 性能。然而,目前大量的云应用程序将其数据组织为大量小对象,这些小对象的数据大小接近(甚至小于)元数据大小,因此如果将所有元数据都放在昂贵的SSD上,则大大增加了成本。

本文介绍了 x Meta,这是一种用于云规模对象存储的元数据维护的 SSD-HDD 混合优化。我们观察到,小对象的大部分元数据很少被访问,因此可以存储在 HDD 上,而性能损失很小。因此,x Meta首先根据上层应用访问元数据的频率对元数据进行冷热分类,然后自适应地将热元数据存储在SSD上,冷元数据存储在HDD上。我们还提出了热元数据的合并机制,以进一步提高SSD存储效率,并通过设计复合键来优化热元数据的范围键查询和插入。我们将x Meta元数据服务与Ceph集成,实现了高性能、低成本的对象存储(称为xCeph)。广泛的评估表明,xCeph 在 SSD 存储的空间需求方面比原始 Ceph 提高了一个数量级,同时吞吐量提高了高达 2.7 倍。

更新日期:2024-03-13
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