计算机科学 ›› 2022, Vol. 49 ›› Issue (8): 26-32.doi: 10.11896/jsjkx.210700176

• 数据库&大数据&数据科学* 上一篇    下一篇

基于热点数据的持久性内存索引查询加速

刘高聪, 罗永平, 金培权   

  1. 中国科学技术大学计算机科学与技术学院 合肥 230027
  • 收稿日期:2021-07-19 修回日期:2022-02-27 出版日期:2022-08-15 发布日期:2022-08-02
  • 通讯作者: 金培权(jpq@ustc.edu.cn)
  • 作者简介:(cs1033@mail.ustc.edu.cn)
  • 基金资助:
    国家自然科学基金(62072419)

Accelerating Persistent Memory-based Indices Based on Hotspot Data

LIU Gao-cong, LUO Yong-ping, JIN Pei-quan   

  1. School of Computer Science and Technology,University of Science and Technology of China,Hefei 230027,China
  • Received:2021-07-19 Revised:2022-02-27 Online:2022-08-15 Published:2022-08-02
  • About author:LIU Gao-cong,born in 1999,postgra-duate.His main research interests include database technologies for NVM and so on.
    JIN Pei-quan,born in 1975,Ph.D,associate professor,is a senior member of China Computer Federation.His main research interests include databases and big data.
  • Supported by:
    National Natural Science Foundation of China(62072419).

摘要: 非易失性内存(Non-Volatile Memory,NVM),也被称为持久性内存(Persistent Memory,PM),具有按位寻址、持久性、存储密度高、低延迟等特点。虽然NVM的延迟远小于闪存,但高于DRAM(Dynamic Random Access Memory)。此外,NVM还有读写不均衡、写次数有限等不足。因此,目前NVM还无法完全代替DRAM。一种更为合理的方法是利用NVM构建基于DRAM+NVM的混合内存架构。文中针对NVM和DRAM构成的混合内存架构,着重研究了基于热点数据的持久性内存索引加速方法。具体而言,以数据访问中的倾斜性特征为基础,利用DRAM的低延迟和NVM的持久性与高存储密度,提出了在持久性内存索引的基础上增加基于DRAM的热点数据缓存,进而提出了可以根据热点数据的变化自动调整缓存的查询自适应索引方法。将所提方法应用到多种持久性内存索引上,包括wBtree,FPTree以及Fast&Fair,并进行了对比实验。结果表明,当热点数据访问达到总访问次数的80%时,所提索引加速方法在3种索引上的查询性能分别取得了52%,33%,37%的提升。

关键词: 非易失性内存, 混合内存架构, 热点数据, 自适应索引

Abstract: Non-volatile memory(NVM),also known as persistent memory(PM),has the characteristics of bit-based addressing,durability,high storage density and low latency.Although the latency of NVM is much smaller than that of solid-state drives,it is greater than that of DRAM.In addition,NVM has shortcomings such as unbalanced reading and writing as well as short writing life.Therefore,currently NVM cannot completely replace DRAM.A more reasonable method is using NVM to build a hybrid memory architecture based on DRAM+NVM.Based on the observation that many data accesses in database applications are skewed,this paper focuses on the hybrid memory architecture composed of NVM and DRAM and proposes a hotspot data-based speedup method for persistent memory indices.Particularly,we utilize the low latency of DRAM and the durability and high sto-rage density of NVM,and propose to add a DRAM-based hotspot-data cache for persistent memory indices.Then,we present a query-adaptive indexing method that can automatically adjust the cache according to the change of hotspot data.We apply the proposed method to several persistent memory indices,including wBtree,FPTree and Fast&Fair,and conduct comparative experiments.The results show that when the number of hotspot data visits accounts for 80% of the total visits,the proposed method can accelerate the query performance of the three indices by 52%,33% and 37%,respectively.

Key words: Non-volatile memory, Hybrid memory architecture, Hotspot data, Adaptive index

中图分类号: 

  • TP311
[1]WU Z L,JIN P Q,YUE L H,et al.A survey on PCM-Based big data storage and management[J].Journal of Compute Research and Development,2015,52(2):343-361.
[2]LUO Y,CHU Z,JIN P,et al.Efficient sorting and join on nvm-based hybrid memory[C]//ICA3PP.2020:15-30.
[3]LIU Y,JIN P,WAN S.BF-Join:An efficient hash join algorithm for dram-nvm-based hybrid memory system[C]//ISPA.2019:875-882.
[4]VENKATARAMAN S,TOLIA N,RANGANATHAN P,et al.Consistent and durable data structures for non-volatile byte-addressable memory[C]//FAST.2011:61-75.
[5]CHEN S,JIN Q.Persistent B+-trees in non-volatile main me-mory[J].Proceedings of the VLDB Endowment,2015,8(7):786-797.
[6]OUKID I,LASPERAS J,NICA A,et al.FPtree:A hybrid scm-dram persistent and concurrent b-tree for storage class memory[C]//SIGMOD.2016:371-386.
[7]ATIKOGLU B,XU Y,FRACHTENBERG E,et al.Workloadanalysis of a large-scale key-value store[C]//SIGMETRICS.2012:53-64.
[8]CHEN J,CHEN L,WANG S,et al.Hotring:A hotspot-aware in-memory key-value store[C]//FAST.2020:239-252.
[9]HWANG D,KIM W H,WON Y,et al.Endurable transient inconsistency in byte-addressable persistent b+tree[C]//FAST.2018:187-200.
[10]ZUO P,HUA Y,WU J.Level hashing:A high-performance and flexible-resizing persistent hashing index structure[J].ACM Transactions on Storage,2019,15(2):13:1-13:30.
[11]LU B,HAO X,WANG T,et al.Dash:Scalable hashing on persistent memory[J].Proceedings of the VLDB Endowment,2020,13(8):1147-1161.
[12]JUNG J,KRISHNAMURTHY B,RABINOVICH M.Flashcrowds and denial of service attacks:Characterization and implications for cdns and website[C]//WWW.2002:293-304.
[13]DAN A,TOWSLEY D.An approximate analysis of the LRU and FIFO buffer replacement schemes[C]//SIGMETRICS.1990:143-152.
[14]INTEL.Intel Optane Technology[EB/OL].https://www.intel.com/content/www/us/en/archit-ecture-and-technology/optane-dc-persistent-memory.html.
[15]GITHUB.Zipfian-distribution[EB/OL].https://github.com/ekg/dirtyzipf/blob/master/dirty_zipfian_int_distribution.html.
[16]GRAY J,SUNDARESAN P,ENGLERT S,et al.Quickly genera-ting billion-record synthetic databases[C]//SIGMOD.1994:243-252.
[1] 范鹏浩, 黄国锐, 金培权.
NVRC:一种面向NVM的写限制日志方案
NVRC:Write-limited Logging for Non-volatile Memory
计算机科学, 2021, 48(3): 130-135. https://doi.org/10.11896/jsjkx.200900071
[2] 孙强, 诸葛晴凤, 陈咸彰, 沙行勉, 吴林.
带磨损均衡的小粒度非易失性内存管理机制
In-page Wear-leveling Memory Management Based on Non-volatile Memory
计算机科学, 2018, 45(11A): 505-510.
[3] 薛忠斌,周烜,张延松,周新,王珊.
内存列存储数据库中优化的混合自适应索引
Optimized Adaptive Hybrid Indexing for In-memory Column Stores
计算机科学, 2015, 42(11): 28-31. https://doi.org/10.11896/j.issn.1002-137X.2015.11.004
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!