[1]陆文星[] [],涂竹松[][],梁焱[]. 基于HBase的数据共享模型研究[J].计算机技术与发展,2016,26(04):36-40.
　LU Wen-xing[] [],TU Zhu-song[][],LIANG Yan[]. Research on Data Sharing Model Based on HBase[J].,2016,26(04):36-40.
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 基于HBase的数据共享模型研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年04期
页码:
36-40
栏目:
智能、算法、系统工程
出版日期:
2016-04-10

文章信息/Info

Title:
 Research on Data Sharing Model Based on HBase
文章编号:
1673-629X（2016)04-0036-05
作者:
 陆文星[1] [2]; 涂竹松[1][2];  梁焱[1]
1. 合肥工业大学 管理学院；2.过程优化与智能决策教育部重点实验室
Author(s):
 LU Wen-xing[1] [2]; TU Zhu-song[1][2];  LIANG Yan[1]
关键词:
 ; 数据共享; 数据集成; HBase ; 黑板系统
Keywords:
 ; data sharing; data integration; HBase; blackboard system
分类号:
TP31
文献标志码:
A
摘要:
 在信息化高速发展过程中，如何共享海量数据并提高其应用价值是当今云计算领域的研究热点之一。传统的数据共享方式不能满足大数据的存储要求和解除高速计算问题与数据的高容错性问题，这就需要新的共享方式来实现。文中在数据仓库的数据集成模式的基础上，根据黑板系统的思想和“发布-订阅”数据分发策略，提出了基于HBase数据库的数据共享模型，并分析了该模型的运行机理。基于HBase的数据共享方式不仅能够提高对海量数据的处理能力和速度，还能有效降低原有数据共享方式中在出现故障时对整个业务系统造成的不良影响。文中提出的基于HBase数据共享模型在云环境下实现海量数据共享的问题上为各大型企业提供了参考，不仅能够满足海量数据的量级持续增长和计算的需求，同时提高了系统可靠性。
Abstract:
 During the process of high-speed development of informatization,one of the research hotspots in the cloud computing area at present is how to share the tremendous amount of information and improve its application value. The traditional data sharing method can-not satisfy the storage requirements of large data and also cannot solve the problem of high speed calculation as well as the high fault tol-erance,which requires a new sharing method. Based on the data integration pattern of data warehouse,according to the idea of the black-board system and“Publish-Subscribe” data issue strategy,a data sharing model based on HBase database is put forward and the operating mechanism of it is analyzed. Data sharing based on Hadoop not only improves the ability and speed of processing of massive data,but also reduces the potential damage the original data sharing method may cause to the entire system. The study of data sharing based on Hadoop gives reference to large enterprises for sharing of massive data,which not only fulfills the needs of continual steep increasing and compu-tation of massive data,but also improves the reliability of the system.

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更新日期/Last Update: 2016-06-16