{"title":"SILT: a memory-efficient, high-performance key-value store","authors":"Hyeontaek Lim, Bin Fan, D. Andersen, M. Kaminsky","doi":"10.1145/2043556.2043558","DOIUrl":null,"url":null,"abstract":"SILT (Small Index Large Table) is a memory-efficient, high-performance key-value store system based on flash storage that scales to serve billions of key-value items on a single node. It requires only 0.7 bytes of DRAM per entry and retrieves key/value pairs using on average 1.01 flash reads each. SILT combines new algorithmic and systems techniques to balance the use of memory, storage, and computation. Our contributions include: (1) the design of three basic key-value stores each with a different emphasis on memory-efficiency and write-friendliness; (2) synthesis of the basic key-value stores to build a SILT key-value store system; and (3) an analytical model for tuning system parameters carefully to meet the needs of different workloads. SILT requires one to two orders of magnitude less memory to provide comparable throughput to current high-performance key-value systems on a commodity desktop system with flash storage.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":"45 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"330","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2043556.2043558","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 330
Abstract
SILT (Small Index Large Table) is a memory-efficient, high-performance key-value store system based on flash storage that scales to serve billions of key-value items on a single node. It requires only 0.7 bytes of DRAM per entry and retrieves key/value pairs using on average 1.01 flash reads each. SILT combines new algorithmic and systems techniques to balance the use of memory, storage, and computation. Our contributions include: (1) the design of three basic key-value stores each with a different emphasis on memory-efficiency and write-friendliness; (2) synthesis of the basic key-value stores to build a SILT key-value store system; and (3) an analytical model for tuning system parameters carefully to meet the needs of different workloads. SILT requires one to two orders of magnitude less memory to provide comparable throughput to current high-performance key-value systems on a commodity desktop system with flash storage.
淤泥(Small Index Large Table)是一种内存高效、高性能的键值存储系统,基于flash存储,可扩展到在单个节点上服务数十亿个键值项。它每个条目只需要0.7字节的DRAM,并且每次平均使用1.01次闪存读取来检索键/值对。淤泥结合了新的算法和系统技术来平衡内存、存储和计算的使用。我们的贡献包括:(1)设计了三个基本的键值存储,每个存储对内存效率和写友好性的强调不同;(2)综合基本键值存储,构建一个淤泥键值存储系统;(3)建立分析模型,对系统参数进行精心调整,以满足不同工作负载的需要。淤泥需要少一到两个数量级的内存,以提供与当前具有闪存的商用桌面系统上的高性能键值系统相当的吞吐量。