SequenceFile Storage Optimization Method Based on Pile Structure

Wenjing Wu, Huiyi Liu, Liting Duan, Si-Yuan Xu
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引用次数: 1

Abstract

Hadoop Distributed File System (HDFS) performs well when storing and managing large data sets, but its performance is significantly reduced when processing massive small files. In response to this problem, a SequenceFile file storage optimization method based on the pile structure (OPSS) is proposed. The method uses the pile as a unit to merge and merge small files in the pile into SequenceFile based on the worst-fit strategy, reducing the data blocks consumed by the same number of small files. In addition, this method stores the index information of small files in a global index file, and accesses the small files through the global index file, which improves the access efficiency and reduces the memory occupied by the index file. Experimental results show that this method effectively optimizes the performance of HDFS for accessing large amounts of small files.
基于桩结构的SequenceFile存储优化方法
HDFS (Hadoop Distributed File System)在存储和管理大型数据集时性能良好,但在处理海量小文件时性能明显下降。针对这一问题,提出了一种基于桩结构(OPSS)的SequenceFile文件存储优化方法。该方法以堆为单位,根据最差拟合策略将堆中的小文件合并并合并到SequenceFile中,减少了相同数量的小文件所消耗的数据块。此外,该方法将小文件的索引信息存储在全局索引文件中,通过全局索引文件访问小文件,提高了访问效率,减少了索引文件占用的内存。实验结果表明,该方法有效地优化了HDFS访问大量小文件的性能。
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