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: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2016-04-01
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| 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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| Summary: | 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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| ISSN: | 1000-436X |