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A tile-based scalable raster data management system based on HDFS

机译:基于HDFS的基于图块的可伸缩栅格数据管理系统

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Hadoop has become a worldwide popular open source platform for large data analysis in commercial application and Hadoop distributed file system (HDFS) is the core part of it. However, HDFS cannot be used directly for managing raster data, for the geographic location information is involved. In this paper, we describe the implementation of a tile-based scalable raster data management system based on HDFS. While reserving the basic architecture of HDFS, we reorganize the data structure in block, add some additional metadata, design an index data structure in block, keep an overlapping region between adjacent blocks, and offer a compression option for users. Besides, we provide functions for reading the raster data from HDFS in tile stream. These optimizations match the feature of raster data to the architecture of HDFS. MapReduce Applications can be built on the raster data management system.
机译:Hadoop已成为全球流行的开放源代码平台,用于商业应用程序中的大数据分析,并且Hadoop分布式文件系统(HDFS)是其核心部分。但是,由于涉及地理位置信息,因此HDFS不能直接用于管理栅格数据。在本文中,我们描述了基于HDFS的基于图块的可伸缩栅格数据管理系统的实现。在保留HDFS的基本体系结构的同时,我们重新组织了块中的数据结构,添加了一些其他元数据,在块中设计了索引数据结构,在相邻块之间保留了重叠区域,并为用户提供了压缩选项。此外,我们提供了从图块流中的HDFS读取栅格数据的功能。这些优化使栅格数据的功能与HDFS的体系结构相匹配。可以在栅格数据管理系统上构建MapReduce应用程序。

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