TY - GEN
T1 - Adaptive Transaction Scheduling for Highly Contended Workloads
AU - Wang, Jixin
AU - Guo, Jinwei
AU - Zhou, Huan
AU - Cai, Peng
AU - Qian, Weining
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Traditional transaction scheduling mechanism—which is a key component in database systems—slows down the performance of concurrency control greatly in such environments for highly contended workloads. Obviously, to address this issue, there are two effective methods: (1) avoiding concurrent transactions that access the same high-contention tuple at the same time; (2) accelerating the execution of these high-contention transactions. In this demonstration, we present a new transaction scheduling mechanism, which aims to achieve the above goals. An adaptive group of first-class queues is introduced, where each queue is allocated to a specified worker thread and takes charge of transactions accessing specified high-contention tuples. We implement a system prototype and demonstrate that our transaction scheduling mechanism can effectively reduce the abort ratio of high-contention transactions and improve the system throughput dramatically.
AB - Traditional transaction scheduling mechanism—which is a key component in database systems—slows down the performance of concurrency control greatly in such environments for highly contended workloads. Obviously, to address this issue, there are two effective methods: (1) avoiding concurrent transactions that access the same high-contention tuple at the same time; (2) accelerating the execution of these high-contention transactions. In this demonstration, we present a new transaction scheduling mechanism, which aims to achieve the above goals. An adaptive group of first-class queues is introduced, where each queue is allocated to a specified worker thread and takes charge of transactions accessing specified high-contention tuples. We implement a system prototype and demonstrate that our transaction scheduling mechanism can effectively reduce the abort ratio of high-contention transactions and improve the system throughput dramatically.
UR - https://www.scopus.com/pages/publications/85065410066
U2 - 10.1007/978-3-030-18590-9_90
DO - 10.1007/978-3-030-18590-9_90
M3 - 会议稿件
AN - SCOPUS:85065410066
SN - 9783030185893
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 576
EP - 580
BT - Database Systems for Advanced Applications - DASFAA 2019 International Workshops
A2 - Yang, Jun
A2 - Li, Guoliang
A2 - Natwichai, Juggapong
A2 - Gama, Joao
A2 - Tong, Yongxin
PB - Springer Verlag
T2 - 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019
Y2 - 22 April 2019 through 25 April 2019
ER -