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  1. University of Information Technology
  2. Faculty of Computer Science

Merging Small Files Based on Agglomerative Hierarchical Clustering on HDFS for Cloud Storage

http://hdl.handle.net/20.500.12678/0000002931
http://hdl.handle.net/20.500.12678/0000002931
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b263d667-5a33-4150-aa37-3475753356c3
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Merging Merging Small Files Based on Agglomerative Hierarchical Clustering on HDFS for Cloud Storage.pdf (239 Kb)
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Publication type
Conference paper
Upload type
Publication
Title
Title Merging Small Files Based on Agglomerative Hierarchical Clustering on HDFS for Cloud Storage
Language en
Publication date 2018-02-23
Authors
Khin Su Su Wai
Julia Myint
Tin Tin Yee
Description
Hadoop distributed file system (HDFS) was
originally designed for large files. HDFS stores each
small file as one separate block although the size of
several small files is lesser than the size of block size.
Therefore, a large number of blocks are created with
massive small files. When the large number of small
files is accessed, NameNode often becomes the
bottleneck. The problem of storing and accessing
large number of small files is named as small file
problem. In order to solve this issue in HDFS, an
approach of merging small files on HDFS is
proposed. In this paper, small files are merged into a
larger file based on the agglomerative hierarchical
clustering mechanism to reduce NameNode memory
consumption. This approach will provide small files
for cloud storage.
Keywords
HDFS, Small Files
Conference papers
ICCA 2018
22-23 February, 2018
16th International Conference on Computer Applications
Sedona Hotel, Yangon, Myanmar
https://www.ucsy.edu.mm/page228.do
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