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Research of Metadata Management in Multiple MetaData Servers Environment

Author: PanLeiYing
Tutor: FengDan
School: Huazhong University of Science and Technology
Course: Computer System Architecture
Keywords: Object Storage System Multivariate data server Distributed Metadata Management Hot metadata
CLC: TP311.13
Type: Master's thesis
Year: 2007
Downloads: 138
Quote: 2
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Abstract


Typically, the user request into a data request and metadata requests. Although the element data is small , but the operation of the storage system , metadata operations accounted for 50 % to 80% . Therefore, efficient management of metadata is very important. With the increasing size of the storage system and data access density increases, centralized metadata management has gradually incompetent . Not only for today's high-performance computing storage system I / O bandwidth and metadata processing performance and a high demand, but the size of the storage system and scalability are also in high demand . Single metadata server has been unable to meet the application on the scale and performance growing demand. Multivariate data server storage system is the inevitable trend of development . In PB -class storage system, usually by several metadata server cluster to form tens of thousands of concurrent users accessing meet . Metadata should be evenly distributed to each of the metadata server to ensure that the load balancing in the general case . In object-based storage system to achieve a number based on the parent directory object hash method (Directory Object ID and Filename Hashing, DOIDFH) distributed metadata management solution that combines the sub-tree and hash partitioning method has the advantage , you can use the same directory files evenly distributed to multiple the MDS and partially retained in the same directory storage locality. Simultaneously with the sub-tree partitioning scheme compares the performance results show that DOIDFH scheme roadway data server load more balanced, and the system response speed and throughput are better than the sub-tree partitioning scheme . Distributed storage system performance with the metadata in multiple metadata servers is closely related to the distribution , if a large number of access focused on some specific metadata ( hot spots ) , the system performance will be greatly affected . Different scenarios under different circumstances hotspot problem solving is not the same . By looking on each server has become a hot hot Metadata Metadata then make a mirror on the other node method to reduce the metadata hotspots impact on system performance .

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