TY - GEN
T1 - BPTree
T2 - 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021
AU - Huang, Chenchen
AU - Hu, Huiqi
AU - Zhou, Aoying
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85104793109
U2 - 10.1007/978-3-030-73200-4_32
DO - 10.1007/978-3-030-73200-4_32
M3 - 会议稿件
AN - SCOPUS:85104793109
SN - 9783030731991
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 478
EP - 486
BT - Database Systems for Advanced Applications - 26th International Conference, DASFAA 2021, Proceedings
A2 - Jensen, Christian S.
A2 - Lim, Ee-Peng
A2 - Yang, De-Nian
A2 - Lee, Wang-Chien
A2 - Tseng, Vincent S.
A2 - Kalogeraki, Vana
A2 - Huang, Jen-Wei
A2 - Shen, Chih-Ya
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 11 April 2021 through 14 April 2021
ER -