A new fragment re-allocation strategy for NoSQL database systems
作者:Zhikun Chen, Shuqiang Yang, Shuang Tan, Li He, Hong Yin, Ge Zhang
摘要
NoSQL databases are famed for the characteristics of high scalability, high availability, and high fault-tolerance. So NoSQL databases are used in a lot of applications. The data partitioning strategy and fragment allocation strategy directly affect NoSQL database systems’ performance. The data partition strategy of large, global databases is performed by horizontally, vertically partitioning or combination of both. In the general way the system scatters the related fragments as possible to improve operations’ parallel degree. But the operations are usually not very complicated in some applications, and an operation may access to more than one fragment. At the same time, those fragments which have to be accessed by an operation may interact with each other. The general allocation strategies will increase system’s communication cost during operations execution over sites. In order to improve those applications’ performance and enable NoSQL database systems to work efficiently, these applications’ fragments have to be allocated in a reasonable way that can reduce the communication cost i.e., to minimize the total volume of data transmitted during operations execution over sites. A strategy of clustering fragments based on hypergraph is proposed, which can cluster fragments which were accessed together in most operations to the same cluster. Themethod uses a weighted hypergraph to represent the fragments’ access pattern of operations. A hypergraph partitioning algorithmis used to cluster fragments in our strategy. This method can reduce the amount of sites that an operation has to span. So it can reduce the communication cost over sites. Experimental results confirm that the proposed technique will effectively contribute in solving fragments re-allocation problem in a specific application environment of NoSQL database system.
论文关键词:fragment allocation, NoSQL database, hypergraph partition, clustering fragments, fragment correlation
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论文官网地址:https://doi.org/10.1007/s11704-014-3480-4