A Dynamic Method for Metadata Partitioning Based on Intensive Access of Spatial Data
In the object-based storage architecture of spatial data, accesses to metadata are 50％ to 80％ of the total data accesses, so metadata management and partitioning are very important However, many typical and traditional methods for metadata partitioning, such as directory subtree partitioning, hashing partitioning, etc., should face the issues of hotspot and load balancing. In this paper, we analyzed the accesses to spatial data that follows Zipf-like distribution and has locality of reference, and proposed a dynamic method for metadata partitioning based on intensive access pattern of spatial data. This method considered the temporal locality and spatial locality of accesses to tile, put forward tile access rank algorithm based on the sum of access times per interval time, and got tile access probability by Zipf-likes law for dynamic hashing partitioning of metadata. The experiment results presented the improving of efficiency in tile access rank, and showed that the method for metadata partitioning is an effective solution for hotspot and load balancing issues.
Zipf-like distribution access pattern metadata partitioning load balancing
Lin Yanping, Li Rui Xu Zhengquan Guo Rui
State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing Wuhan University Wuhan, China
国际会议
重庆
英文
680-683
2011-08-20（万方平台首次上网日期，不代表论文的发表时间）