ZonedStore:用于云数据存储的并发zns感知缓存系统

Yanqi Lv, Peiquan Jin, Xiaoliang Wang, Ruicheng Liu, Liming Fang, Yuanjin Lin, Kuankuan Guo
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引用次数: 2

摘要

云数据存储依赖于高效的缓存系统,为大数据的密集读写提供高性能。由于云数据存储的数据量大,而DRAM的容量有限,目前的云厂商更倾向于使用ssd (Solid State Drives)而不是DRAM来构建缓存系统。然而,传统ssd存在严重的供应过剩问题,并且垃圾收集成本高。因此,当ssd的使用增加时,基于ssd的缓存系统的性能将迅速下降。最近,分区命名空间(ZNS) ssd已经成为学术界和工业界的热门话题。与传统ssd相比,ZNS ssd具有较少的垃圾收集开销和较低的过度配置成本的优点。因此,ZNS ssd已经成为云存储缓存系统的更好候选。但是,ZNS ssd只接受顺序写入,并且需要仔细管理ZNS ssd内部的区域,以最大限度地发挥ZNS ssd的优势。因此,使缓存系统适应ZNS ssd成为一个具有挑战性的问题。在本文中,我们展示了ZonedStore,一种用于云数据存储的新型zns感知缓存系统。在简要介绍了ZonedStore的架构后,我们介绍了ZonedStore的关键设计,包括控制ZNS ssd上的空间分配和操作的Zone Manager,多层缓冲区管理器和内存并发索引以加速访问。最后,我们提出了一个案例研究来展示ZonedStore的工作过程和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ZonedStore: A Concurrent ZNS-Aware Cache System for Cloud Data Storage
Cloud data storage relies on efficient cache systems to offer high performance for intensive reads/writes on big data. Due to the large data volume of cloud data storage and the limited capacity of DRAM, current cloud vendors prefer to use SSDs (Solid State Drives) but not DRAM to build the cache system. However, traditional SSDs have a serious over-provisioning problem and a high cost in garbage collection. Thus, the performance of SSD-based cache systems will drop quickly when the usage of SSDs increases. Recently, Zoned Namespaces (ZNS) SSDs have emerged as a hot topic in both academics and industries. Compared to conventional SSDs, ZNS SSDs have the advantages of less overhead of garbage collection and lower over-provisioning costs. Therefore, ZNS SSDs have been a better candidate for the cache system for cloud storage. However, ZNS SSDs only accept sequential writes, and the zones inside ZNS SSDs need to be carefully managed to maximize the advantages of ZNS SSDs. Therefore, making the cache system adapt to ZNS SSDs is becoming a challenging issue. In this paper, we demonstrate ZonedStore, a novel ZNS-aware cache system for cloud data storage. After a brief introduction to the architecture of ZonedStore, we present the key designs of ZonedStore, including a Zone Manager to control the space allocation and operations on ZNS SSDs, a Multi-Layer Buffer Manager, and an In-Memory Concurrent Index to accelerate accesses. Finally, we present a case study to demonstrate the working process and performance of ZonedStore.
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