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EEPH: An Efficient Extendible Perfect Hashing for Hybrid PMem-DRAM

  • Qi Chen
  • , Hao Hu
  • , Cai Deng
  • , Dingbang Liu
  • , Shiyi Li
  • , Bo Tang
  • , Ting Yao
  • , Wen Xia*
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen
  • Southern University of Science and Technology
  • Huawei Technologies Co., Ltd.
  • Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, the performance of hash indexes has been significantly improved by exploiting emerging persistent memory (PMem). However, the performance improvement of hash indexes mainly comes from exploiting the hardware features of PMem. Only a few studies optimize the hash index itself to fully exploit the potential of PMem. Interestingly, many of these studies improve the performance of write, but disregard the performance of read, of hash indexes on PMem. With extensive experimental evaluation, we find the major reason for inefficient read in the hash index on PMem is that the overhead of hash collision processing is expensive.To address that, we propose a novel Efficient Extendible Perfect Hashing (EEPH) on PMem-DRAM hybrid data layout to improve read performance of hash indexes. Specifically, we reduce the overhead of dynamic perfect hashing extension on PMem by combing extendible hashing. We then design a hybrid data layout to unlock the inherent read strengths of perfect hashing (i.e., zero collision). Last, we devise a complement move algorithm to efficiently guarantee the zero collision of perfect hashing when data move is conducted on PMem. We compare EEPH with the state-of-the-art hash indexes on PMem by conducting comprehensive experiments on several real-world read-intensive and read-skew workloads. The experimental results confirm the superiority of our EEPH as it achieves up to 2.21× higher throughput and about 1/3 of the 99th percentile latency than state-of-the-art hash indexes.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 39th International Conference on Data Engineering, ICDE 2023
PublisherIEEE Computer Society
Pages1366-1378
Number of pages13
ISBN (Electronic)9798350322279
DOIs
StatePublished - 2023
Externally publishedYes
Event39th IEEE International Conference on Data Engineering, ICDE 2023 - Anaheim, United States
Duration: 3 Apr 20237 Apr 2023

Publication series

NameProceedings - International Conference on Data Engineering
Volume2023-April
ISSN (Print)1084-4627

Conference

Conference39th IEEE International Conference on Data Engineering, ICDE 2023
Country/TerritoryUnited States
CityAnaheim
Period3/04/237/04/23

Keywords

  • hybrid PMem DRAM
  • perfect hashing

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