BPTree: An Optimized Index with Batch Persistence on Optane DC PM

Chenchen Huang, Huiqi Hu, Aoying Zhou

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

4 Scopus citations

Abstract

Intel Optane DC Persistent Memory (PM) is the first commercially available PM product. Although it meets many hypothesises about PM in previous studies, some other design considerations are observed in subsequent tests. For instance, 1) the internal data access granularity in Optane DC PM is 256B, accesses smaller than 256B will cause read/write amplification; 2) the locking overhead will be amplified when the PM operations are included in the critical area or the lock is added on PM. In this paper, we propose a novel persistent index called BPTree to fit with these new features. The core idea of BPTree is to buffer multiple writes in DRAM first, and later persist them in batches to PM to reduce the write amplification. We add a buffer layer in BPTree to enable the batch persistence, and design a GC-friendly log structure on PM to guarantee the buffer’s durability. To improve the scalability, we also implement a hybrid concurrency control strategy to ensure most of the operations on PM are lock-free, and move the lock from PM to DRAM for the operations that must be locked. Our experiments on Optane DC PM show that BPTree reduces 256B PM writes by a factor of 1.95–2.48x compared to the state-of-the-art persistent indexes. Moreover, BPTree has better scalability in the concurrent environment.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 26th International Conference, DASFAA 2021, Proceedings
EditorsChristian S. Jensen, Ee-Peng Lim, De-Nian Yang, Wang-Chien Lee, Vincent S. Tseng, Vana Kalogeraki, Jen-Wei Huang, Chih-Ya Shen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages478-486
Number of pages9
ISBN (Print)9783030731991
DOIs
StatePublished - 2021
Event26th International Conference on Database Systems for Advanced Applications, DASFAA 2021 - Taipei, Taiwan, Province of China
Duration: 11 Apr 202114 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12683 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Database Systems for Advanced Applications, DASFAA 2021
Country/TerritoryTaiwan, Province of China
CityTaipei
Period11/04/2114/04/21

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