The Design And Implement Of Cloud Storage System Client Based On Hadoop

Hadoop is a cloud computing platform which is the open source implementation of Google's GFS and MapReduce. Although hadoop now is mainly focused on the technology of processing of mass data calculate, we can not ignore the powerful data storage capacity of hadoop which is reflected in the design and implementation of hadoop. The powerful data storage capacity of hadoop is mainly Reflected in the design of distributed file system HDFS. HDFS is a network-based distributed file system which can handle very large amounts of data effectively, the user'file data could be stored distributed through HDFS.In the research of hadoop platform, we mainly focus on the following three aspects. Firstly we analyze the mechanisms of data processing method and reading and writing process in the HDFS. We also analyze the defects of this design idea. The analysis will help us to build a hadoop-based cloud storage service system. Secondly we analyze the job scheduling algorithms in the hadoop platform and implement a new scheduling algorithm - based on feedback scheduling algorithm, which the main idea is the current job scheduling decisions will affect the next scheduling decision-making, and constantly modify the configuration parameters of the cluster system to achieve a more stable job processing performance. Finally, we implement a cloud storage system based on hadoop. The main achievement is the client management interface, through this platform user can manage their own storage space and file, and upload the local file to cluster servers for storage. The data of user will be processed by the HDFS before stored to the disks .