A Cube Analytical Mining Framework for Stream Data
Stream data has been one of the most significant data format recently. OLAM（online analytical mining） operation could provide multi-level data views for analysts. However, OLAM operations depend on data aggregation, which is in conflict with the continuous incensement and dynamic nature of stream da...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2014-09-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.3969／j.issn.1000-0801.2014.09.009/ |
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| _version_ | 1841529371434680320 |
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| author | Canghong Jin Zemin Liu Minghui Wu Jing Ying |
| author_facet | Canghong Jin Zemin Liu Minghui Wu Jing Ying |
| author_sort | Canghong Jin |
| collection | DOAJ |
| description | Stream data has been one of the most significant data format recently. OLAM（online analytical mining） operation could provide multi-level data views for analysts. However, OLAM operations depend on data aggregation, which is in conflict with the continuous incensement and dynamic nature of stream data. Thus, partial materialized view from stream data directly by typical OLAP approaches cannot be created and all data cells for the limitation of storage cannot be saved. In order to solve the above problems, an advanced sketch based OLAM framework named sketch cube to analyze stream data was proposed. Sketch cube maps a set of attributes to a unique number and stores it in sub-linear data structure, and then builds an inverted index by tiled time window. The precondition of using sketch cube by theoretical analysis was given and the storage efficiency and query performance on mass mobile data corpus was evaluated, which supports requirements of real-time analysis. |
| format | Article |
| id | doaj-art-d5c764a23b9d4387ba5a42839a7d79e2 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2014-09-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-d5c764a23b9d4387ba5a42839a7d79e22025-01-15T03:18:56ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012014-09-0130617159619455A Cube Analytical Mining Framework for Stream DataCanghong JinZemin LiuMinghui WuJing YingStream data has been one of the most significant data format recently. OLAM（online analytical mining） operation could provide multi-level data views for analysts. However, OLAM operations depend on data aggregation, which is in conflict with the continuous incensement and dynamic nature of stream data. Thus, partial materialized view from stream data directly by typical OLAP approaches cannot be created and all data cells for the limitation of storage cannot be saved. In order to solve the above problems, an advanced sketch based OLAM framework named sketch cube to analyze stream data was proposed. Sketch cube maps a set of attributes to a unique number and stores it in sub-linear data structure, and then builds an inverted index by tiled time window. The precondition of using sketch cube by theoretical analysis was given and the storage efficiency and query performance on mass mobile data corpus was evaluated, which supports requirements of real-time analysis.http://www.telecomsci.com/zh/article/doi/10.3969／j.issn.1000-0801.2014.09.009/stream datasketch cubeonline analytical miningreal-time analysis |
| spellingShingle | Canghong Jin Zemin Liu Minghui Wu Jing Ying A Cube Analytical Mining Framework for Stream Data Dianxin kexue stream data sketch cube online analytical mining real-time analysis |
| title | A Cube Analytical Mining Framework for Stream Data |
| title_full | A Cube Analytical Mining Framework for Stream Data |
| title_fullStr | A Cube Analytical Mining Framework for Stream Data |
| title_full_unstemmed | A Cube Analytical Mining Framework for Stream Data |
| title_short | A Cube Analytical Mining Framework for Stream Data |
| title_sort | cube analytical mining framework for stream data |
| topic | stream data sketch cube online analytical mining real-time analysis |
| url | http://www.telecomsci.com/zh/article/doi/10.3969／j.issn.1000-0801.2014.09.009/ |
| work_keys_str_mv | AT canghongjin acubeanalyticalminingframeworkforstreamdata AT zeminliu acubeanalyticalminingframeworkforstreamdata AT minghuiwu acubeanalyticalminingframeworkforstreamdata AT jingying acubeanalyticalminingframeworkforstreamdata AT canghongjin cubeanalyticalminingframeworkforstreamdata AT zeminliu cubeanalyticalminingframeworkforstreamdata AT minghuiwu cubeanalyticalminingframeworkforstreamdata AT jingying cubeanalyticalminingframeworkforstreamdata |