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Enabling top-n file retrieval in cloud storage using hadoop distributed file system

机译:使用hadoop分布式文件系统在云存储中启用top-n文件检索

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A storage system in cloud is well thought-out as a very big scale storage system that has independent storage servers. The service that cloud storage provides is, that can store user's data from remote through network and other authenticated users can access the data easily. Hadoop distributed file system is used to store large files consistently and to retrieve those files at very high bandwidth to user applications. Hadoop splits the files into large blocks and distributes them amongst the nodes in the cluster. When we retrieve data from the cloud, it is very important that the computation and communication overhead should be reduced. To reduce the communication overhead the server should send only the top-n files based on the keyword when the user asks for the data files. Since the owner need not maintain the copy of the files, it is all the more necessary to make check on the files available and also check the originality of the files stored in the server periodically. In HDFS the computation is done in parallel so that the execution time is drastically reduced. In the proposed system for retrieving top-n files we use Hadoop Distributed File System, so that the search time and the communication overhead is greatly reduced.
机译:众所周知,云中的存储系统是具有独立存储服务器的超大规模存储系统。云存储提供的服务是,可以通过网络从远程存储用户数据,其他经过身份验证的用户可以轻松访问数据。 Hadoop分布式文件系统用于一致地存储大文件,并以很高的带宽检索这些文件给用户应用程序。 Hadoop将文件分成大块,然后在群集的各个节点之间分配它们。当我们从云中检索数据时,减少计算和通信开销非常重要。为了减少通信开销,当用户请求数据文件时,服务器应仅基于关键字发送前n个文件。由于所有者不需要维护文件的副本,因此更需要检查可用文件并定期检查存储在服务器中的文件的原始性。在HDFS中,计算是并行进行的,因此可以大大减少执行时间。在提出的用于检索top-n文件的系统中,我们使用Hadoop分布式文件系统,从而大大减少了搜索时间和通信开销。

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