计算机工程2017，Vol.43Issue(3)：7-10,17,5.DOI:10.3969/j.issn.1000-3428.2017.03.002
基于冷热数据的MongoDB自动分片机制
Auto-Sharding Mechanism in MongoDB Based on Cold and Hot Data
摘要
Abstract
The Auto-Sharding mechanism in MongoDB database finishes shard migration only through the data quantity,which causes unbalanced load imbalance.Aiming at this problem,this paper proposes an optimized Auto-Sharding mechanism based on the access characteristics of hot and cold data.It uses the naive Bayes algorithm to determine the data access characteristics of hot and cold data,and takes the proportion of the hot data in a data block as the heat load to determine the data migration time.It establishes new data migration strategy through the heat load differences between data blocks.Experimental results show that the data throughput of the improved mechanism is obviously better than that of the original Auto-Sharding mechanism under high concurrent condition.关键词
自动分片机制/冷热数据/朴素贝叶斯/热负载/数据迁移Key words
Auto-Sharding mechanism/cold and hot data/Naive Bayes/heat load/data migration分类
信息技术与安全科学引用本文复制引用
冯超政,蒋溢,何军,马祥均..基于冷热数据的MongoDB自动分片机制[J].计算机工程,2017,43(3):7-10,17,5.基金项目
重庆市教委科学技术研究项目(KJ1400414) （KJ1400414）
工信部2012年物联网发展专项(2-5) （2-5）
重庆邮电大学博士启动基金(A2015-17). （A2015-17）
