Research on distributed competition big data hierarchical storage method based on Ceph architecture

Xiang Chen, Qing Liu, Bijun Zhang, Gang Li, Shaoping Wu
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Abstract

In the face of intensive data access requests, the current big data storage methods have the problem of poor concurrent read-write performance. Based on Ceph architecture, a distributed big data hierarchical storage method is designed to realize the robust storage service of data files. According to the frequency and popularity of the access object, the cold data with low frequency is eliminated, and the access cache pool or back-end storage pool is selected. Standardize the I/O performance, load and capacity values in the OSD set, calculate the comprehensive weight, and determine the priority of node access. The entire Ceph architecture balances the data distribution. When highly concurrent data access operations occur, a random number is selected to execute the read service of the storage node to ensure the interconnection communication in different clusters. The test results show that the write and read time of the hierarchical storage method based on Ceph architecture is greatly reduced, and good results are achieved in terms of cache hit rate, which can effectively manage and store competitive big data.
基于Ceph架构的分布式竞争大数据分层存储方法研究
面对密集的数据访问请求,当前的大数据存储方式存在并发读写性能差的问题。基于Ceph架构,设计了一种分布式大数据分层存储方法,实现数据文件的鲁棒存储服务。根据访问对象的频率和热度,剔除频率较低的冷数据,选择访问缓存池或后端存储池。统一OSD集中的I/O性能、负载和容量值,计算综合权重,确定节点访问优先级。整个Ceph体系结构平衡了数据分布。当出现高并发的数据访问操作时,随机选择一个号码执行该存储节点的读业务,以保证不同集群间的互联通信。测试结果表明,基于Ceph架构的分层存储方法大大减少了读写时间,在缓存命中率方面取得了良好的效果,能够有效地管理和存储竞争性大数据。
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