Abstract
Hadoop distributed file system (HDFS) becomes a representative cloud platform, benefiting from its reliable, scalable and low-cost storage capability. Unfortunately, HDFS does not perform well for huge number of small files because massive small files imposed heavy burden on NameNode of HDFS. This paper introduces an optimized scheme, structured index file merging (SIFM), using two-level index file and structure metadata storage, to reduce the I/O operations and improve the access efficiency. Extensive experiments demonstrate that the proposed SIFM can effectively achieve better performance in terms of storing and accessing for huge number of small files on HDFS, compared with native HDFS and Hadoop Archive (HAR).
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