TY - GEN
T1 - A twin-buffer scheme for high-throughput logging
AU - Meng, Qingzhong
AU - Zhou, Xuan
AU - Wang, Shan
AU - Huang, Haiyan
AU - Liu, Xiaoli
N1 - Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - For a transactional database system, the efficiency of logging is usually crucial to its performance. The emergence of new hardware, such as NVM and SSD, eliminated the traditional I/O bottleneck of logging and released the potential of multi-core CPUs. As a result, the parallelism of logging becomes important. We propose a parallel logging subsystem called TwinBuf and implemented it in PostgreSQL. This solution can make better use of multi-core CPUs, and is generally applicable to all kinds of storage devices, such as hard disk, SSD and NVM. TwinBuf adopts per-thread logging slots to parallelize logging, and a twin-log-buffer mechanism to make sure that logging can be performed in a non-stop manner. It performs group commit to minimize the persistence overheads. Experimental evaluation was conducted to demonstrate its advantages.
AB - For a transactional database system, the efficiency of logging is usually crucial to its performance. The emergence of new hardware, such as NVM and SSD, eliminated the traditional I/O bottleneck of logging and released the potential of multi-core CPUs. As a result, the parallelism of logging becomes important. We propose a parallel logging subsystem called TwinBuf and implemented it in PostgreSQL. This solution can make better use of multi-core CPUs, and is generally applicable to all kinds of storage devices, such as hard disk, SSD and NVM. TwinBuf adopts per-thread logging slots to parallelize logging, and a twin-log-buffer mechanism to make sure that logging can be performed in a non-stop manner. It performs group commit to minimize the persistence overheads. Experimental evaluation was conducted to demonstrate its advantages.
UR - https://www.scopus.com/pages/publications/85048981618
U2 - 10.1007/978-3-319-91458-9_45
DO - 10.1007/978-3-319-91458-9_45
M3 - 会议稿件
AN - SCOPUS:85048981618
SN - 9783319914572
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 725
EP - 737
BT - Database Systems for Advanced Applications - 23rd International Conference, DASFAA 2018, Proceedings
A2 - Pei, Jian
A2 - Sadiq, Shazia
A2 - Li, Jianxin
A2 - Manolopoulos, Yannis
PB - Springer Verlag
T2 - 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018
Y2 - 21 May 2018 through 24 May 2018
ER -