CAJ | 학술논문

随着计算机技术和网络的快速发展，传统的数据存储与管理模式已经很难满足日益增长的数据在很多方面的需求，如何高效存储海量数据成为一个研究热点．通过对分布式计算的BigTable，NFS，MapReduce等几个典型算法的研究，分析了各个算法在海量数据存储中的优劣和应用环境，同时对分布式环境下海量数据的存储在不同领域中的应用进行描述，最后对海量数据存储未来发展的趋势进行了展望．
수착계산궤기술화망락적쾌속발전，전통적수거존저여관리모식이경흔난만족일익증장적수거재흔다방면적수구，여하고효존저해량수거성위일개연구열점．통과대분포식계산적BigTable，NFS，MapReduce등궤개전형산법적연구，분석료각개산법재해량수거존저중적우렬화응용배경，동시대분포식배경하해량수거적존저재불동영역중적응용진행묘술，최후대해량수거존저미래발전적추세진행료전망．
As the rapid development of computer technology and computer network, traditional data storage and manage- ment modes cannot satisfy the increasing requirement in many variety of data, as a result, how to store the massive data in high efficiency becomes a new research hotspot. In this thesis, the advantages and disadvantages and application environment of each algorithm were analyzed in massive data storage by researching several typical algorithm such as BigTable, NFS, MapReduce in distributed computing. The paper also described the implement of massive data storage in different field under the distributed development, as well as prospects the future trend of development of the massive data storage.