面向轨道交通集群调度系统的数据分片中间件的研究
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摘要
在分析现有的数据分片中间件的基础上设计了一种面向轨道交通集群调度系统的数据分片中间件,该中间件采用离散与连续结合的数据分片策略,在保证数据查询效率的同时,避免了离散分片方式数据库扩容所带来的数据迁移问题和连续分片方式新数据集中读写所带来的数据热点问题。
This paper, on the basis of analyzing the existing data partition middleware, designes a data partition middleware for the rail traffic cluster scheduling system. The middleware uses the discrete and continuous data partitioning strategy, which ensures the efficiency of data query and at the same time avoids the data migration of the discrete piecewise square database expansion and data hot problems of reading and writing in new data sets brought by continuous partition.
This paper, on the basis of analyzing the existing data partition middleware, designes a data partition middleware for the rail traffic cluster scheduling system. The middleware uses the discrete and continuous data partitioning strategy, which ensures the efficiency of data query and at the same time avoids the data migration of the discrete piecewise square database expansion and data hot problems of reading and writing in new data sets brought by continuous partition.
引文
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[2]Lai Y C,Ip C S.An integrated framework for assessing service efficiency and stability of rail transit systems[J].Transportation Research Part C:Emerging Technologies,2017(79):18-41.
[3]Caspi R,Billington R,Fulcher C A,et al.The Meta Cyc database of metabolic pathways and enzymes[J].Nucleic Acids Research,2017(2):231-241.
[4]Dong X,Li X.A Novel Distributed Database Solution Based on My SQL[C].IEEE International Conference on Information Technology in Medicine and Education,2016:329-333.
[5]Wee C K,Nayak R.A Novel Database Exploitation Detection and Privilege Control System Using Data Mining[M]//Modern Approaches for Intelligent Information and Database Systems.Springer,Cham,2018:505-516.
[6]Hulbert A,Kunicki T,Hughes J N,et al.An experimental study of big spatial data systems[C].IEEE International Conference on Big Data,2017:2664-2671.
[7]Sun Y,Wang Y,Yang H.Bidirectional Database Storage and SQL Query Exploiting RRAM-Based Process-inMemory Structure[J].ACM Transactions on Storage(TOS),2018,14(1):8.
[8]Wang Z,Wei Z,Liu H.Research on high availability architecture of SQL and No SQL[C]//AIP Conference Proceedings.AIP Publishing,2017,1820(1):090021.
[9]Ye W,Wang M,Le J.Query Execution Optimization Based on Incremental Update in Database Distributed Middleware[C]//International Conference on Algorithms and Architectures for Parallel Processing.Springer,Cham,2015:257-270.
[10]Vo H,Aji A,Wang F.SATO:a spatial data partitioning framework for scalable query processing[C]//Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.ACM,2014:545-548.
[11]Blomstedt P,Tang J,Xiong J,et al.A Bayesian predictive model for clustering data of mixed discrete and continuous type[J].IEEE transactions on pattern analysis and machine intelligence,2015(3):489-498.
[12]张鹏,刘庆云,熊翠文,等.基于内存的分布式隐私流查询系统[J].计算机研究与发展,2014(2):1-9.
[13]Won J,Kang S,Jo S,et al.Distributed Processing System for Aggregate/Analytical Functions on CUBRID Shard Distributed Databases[J].KIISE Transactions on Computing Practices,2015(8):537-542.