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Hybrid DRAM-NVM R-Trees with Consistency Guarantee

  • Kaiqi Zhang
  • , Chengyou Shen*
  • , Siyuan Zhang
  • , Shengfei Shi*
  • , Hong Gao
  • , Yaofeng Tu
  • , Jianzhong Li
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Chongqing Research Institute of HIT
  • Zhejiang Normal University
  • ZTE Corporation
  • Nanjing University of Aeronautics and Astronautics
  • Shenzhen Institute of Advanced Technology

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

Abstract

The non-volatile memory (NVM) with DRAM-like performance and disk-like persistency has attracted considerable attention in a variety of index structures, including hash table, B-Tree and R-Tree. However, existing NVM-optimized consistent R-Tree is still suboptimal because its single level system neglects the potential boost that DRAM can bring. In this paper, we first propose a hybrid DRAM-NVM consistent R-Tree (HR-Tree), which separately stores internal nodes in DRAM and leaf nodes in NVM. To avoid inconsistency, HR-Tree uses several auxiliary flag bits and pointers to record the process of writes to NVM and employs persistence operations to strictly control the order of writes to NVM. To reduce DRAM consumption, which mainly depends on the metadata size of a leaf node, we present a shared byte strategy to abolish restrictions on metadata size while still keeping HR-Tree consistency. Next, for further shortening search time, we propose an alternative Hilbert-curve-based hybrid R-Tree (HHR-Tree). It has better search efficiency yet leads to insertion performance degradation. Contrary to in-place update in HR-Tree, HHR-Tree applies out-of-place mechanism to enforce data consistency. We conduct comprehensive evaluations on Intel Optane DC Persistent Memory. The proposed HR-Tree outperforms FBR-Tree in terms of insertion, deletion and search throughput while HHR-Tree exhibits a significant improvement for search performance by sacrificing insertion efficiency.

Original languageEnglish
Title of host publicationProceedings - 2025 IEEE 41st International Conference on Data Engineering, ICDE 2025
PublisherIEEE Computer Society
Pages3329-3341
Number of pages13
ISBN (Electronic)9798331536039
DOIs
StatePublished - 2025
Externally publishedYes
Event41st IEEE International Conference on Data Engineering, ICDE 2025 - Hong Kong, China
Duration: 19 May 202523 May 2025

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627
ISSN (Electronic)2375-0286

Conference

Conference41st IEEE International Conference on Data Engineering, ICDE 2025
Country/TerritoryChina
CityHong Kong
Period19/05/2523/05/25

Keywords

  • Data consistency
  • Non-volatile memory
  • R-Tree

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