Compression strategies selection method based on classification of HBase data

Most of the current compression strategies selection methods for HBase data did not consider whether the data was cold or hot. Besides, problem of incompleteness and unreliability existed during selection process. To address the problems above, a compression strategies selection method based on clas...

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Main Authors: Hai-yan WANG, Cai-hang FU
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2016-04-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016068/
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author Hai-yan WANG
Cai-hang FU
author_facet Hai-yan WANG
Cai-hang FU
author_sort Hai-yan WANG
collection DOAJ
description Most of the current compression strategies selection methods for HBase data did not consider whether the data was cold or hot. Besides, problem of incompleteness and unreliability existed during selection process. To address the problems above, a compression strategies selection method based on classification of HBase data was put forward. HBase data was classified into cold and hot data according to the access frequency of each data file and an access level would be designated to each file. On this base, an evaluation layer was added and a compression strategies selection method based on access level with integration of neighbor sector and statistic column based selection methods. Simulation experiments and results demonstrate that the proposed compression strategies selection method based on classification of HBase data can not only save storage space but also greatly improve the query performance of HBase data.
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publisher Editorial Department of Journal on Communications
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series Tongxin xuebao
spelling doaj-art-c64986f484c14d379c19d71d29a90ec92025-01-14T06:55:09ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2016-04-0137122259700251Compression strategies selection method based on classification of HBase dataHai-yan WANGCai-hang FUMost of the current compression strategies selection methods for HBase data did not consider whether the data was cold or hot. Besides, problem of incompleteness and unreliability existed during selection process. To address the problems above, a compression strategies selection method based on classification of HBase data was put forward. HBase data was classified into cold and hot data according to the access frequency of each data file and an access level would be designated to each file. On this base, an evaluation layer was added and a compression strategies selection method based on access level with integration of neighbor sector and statistic column based selection methods. Simulation experiments and results demonstrate that the proposed compression strategies selection method based on classification of HBase data can not only save storage space but also greatly improve the query performance of HBase data.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016068/data compressionHBasecompression strategies selection methodcold and hot data
spellingShingle Hai-yan WANG
Cai-hang FU
Compression strategies selection method based on classification of HBase data
Tongxin xuebao
data compression
HBase
compression strategies selection method
cold and hot data
title Compression strategies selection method based on classification of HBase data
title_full Compression strategies selection method based on classification of HBase data
title_fullStr Compression strategies selection method based on classification of HBase data
title_full_unstemmed Compression strategies selection method based on classification of HBase data
title_short Compression strategies selection method based on classification of HBase data
title_sort compression strategies selection method based on classification of hbase data
topic data compression
HBase
compression strategies selection method
cold and hot data
url http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016068/
work_keys_str_mv AT haiyanwang compressionstrategiesselectionmethodbasedonclassificationofhbasedata
AT caihangfu compressionstrategiesselectionmethodbasedonclassificationofhbasedata