With the prevalence of cloud computing, users’ requirements for cloud databases are becoming increasingly complex. The current write-once-read-many cloud database system, based on shared storage, cannot support the dynamic expansion of write performance. Multiple master nodes provide write services simultaneously, which can cause cross-node read and write conflicts, eventually leading to inconsistencies in the cache of multiple master nodes. For this problem, optimistic conflict detection based on globally ordered transaction logs can detect cross-node transaction conflicts, roll back conflicting transactions, and maintain the isolation level and consistency of the overall system. By broadcasting and replaying the global orderly transaction log, moreover, the modification of the master node can be synchronized to the remaining nodes to ensure the independent service capability of each individual node. This multi-master cache consistency solution based on global transaction logs is implemented on the open source database MySQL, and the impact on system performance is verified through experiments.
WEI Xiaoxian
,
LIU Wenxin
,
CAI Peng
. Global transaction log of a multi-master cloud database[J]. Journal of East China Normal University(Natural Science), 2020
, 2020(5)
: 10
-20
.
DOI: 10.3969/j.issn.1000-5641.202091002
[1] VERBITSKI A, GUPTA A, SAHA D, et al. Amazon aurora: Design considerations for high throughput cloud-native relational databases [C]//Proceedings of the 2017 ACM International Conference on Management of Data. ACM, 2017: 1041-1052.
[2] VERBITSKI A, GUPTA A, SAHA D, et al. Amazon aurora: On avoiding distributed consensus for i/os, commits, and membership changes [C]//Proceedings of the 2018 International Conference on Management of Data. ACM, 2018: 789-796.
[3] CAO W, LIU Z J, WANG P, et al. PolarFS: An ultra-low latency and failure resilient distributed file system for shared storage cloud database [J]. Proceedings of the VLDB Endowment, 2018, 11(12): 1849-1862. DOI: 10.14778/3229863.3229872.
[4] HUANG G, CHENG X T, WANG J Y, et al. X-Engine: An optimized storage engine for large-scale E-commerce transaction processing [C]//Proceedings of the 2019 International Conference on Management of Data. ACM, 2019: 651-665.
[5] ANTONOPOULOS P, BUDOVSKI A, DIACONU C, et al. Socrates: The new SQL server in the cloud [C]//Proceedings of the 2019 International Conference on Management of Data. ACM, 2019: 1743-1756.
[6] DEPOUTOVITCH A, CHEN C, CHEN J, et al. Taurus database: How to be fast, available, and frugal in the cloud [C]//Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. ACM, 2020: 1463-1478.
[7] ORACLE. Oracle Real Application Clusters (RAC) [EB/OL].[2020-07-01]. https://www.oracle.com/database/technologies/rac.html.
[8] ZIKOPOULOS P, EATON C. What is DB2 pureScale? [EB/OL].(2010-01-22)[2020-07-01]. https://www.ibm.com/developerworks/data/library/dmmag/DBMag_2010_Issue1/DBMag_Issue109_pureScale/.
[9] 姜承尧. MySQL技术内幕: InnoDB存储引擎 [M]. 北京: 机械工业出版社, 2011.
[10] 阿里云RDS-数据库内核组. MySQL · 引擎特性 · InnoDB redo log漫游 [EB/OL]. (2015-05-01)[2020-07-01]. http://mysql.taobao.org/monthly/2015/05/01/.
[11] LAMPORT L. Paxos made simple [J]. ACM Sigact News, 2001, 32(4): 51-58.
[12] HERCULE K K, EUGENE M M, PAULIN B B, et al. Study of the master-slave replication in a distributed database [J]. International Journal of Computer Science Issues (IJCSI), 2011, 8(5): 319-326.
[13] BERNSTEIN P A, HADZILACOS V, GOODMAN N. Concurrency Control and Recovery in Database Systems [M]. [S.l.]: Addison-Wesley, 1987.
[14] ZHENG J J, LIN Q, XU J T, et al. PaxosStore: High-availability storage made practical in WeChat [J]. Proceedings of the VLDB Endowment, 2017, 10(12): 1730-1741. DOI: 10.14778/3137765.3137778.
[15] KOSSMANN D, KRASKA T, LOESING S. An evaluation of alternative architectures for transaction processing in the cloud [C]//Proceedings of the 2010 ACM SIGMOD International Conference on Management of data. ACM, 2010: 579-590.
[16] LARSON P Å, BLANAS S, DIACONU C, et al. High-performance concurrency control mechanisms for main-memory databases [J]. Proceedings of the VLDB Endowment, 2011, 5(4): 298-309. DOI: 10.14778/2095686.2095689.
[17] HARDING R, VAN AKEN D, PAVLO A, et al. An evaluation of distributed concurrency control [J]. Proceedings of the VLDB Endowment, 2017, 10(5): 553-564. DOI: 10.14778/3055540.3055548.