Optimizing the Performance of Data Warehouse by Query Cache Mechanism
Fast access of data from Data Warehouse (DW) is a need for today’s Business Intelligence (BI). In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. DW has been widely used by several organizations to manage dat...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9698087/ |
| _version_ | 1819274746465878016 |
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| author | Ch Anwar Ul Hassan Muhammad Hammad Mueen Uddin Jawaid Iqbal Jawad Sahi Saddam Hussain Syed Sajid Ullah |
| author_facet | Ch Anwar Ul Hassan Muhammad Hammad Mueen Uddin Jawaid Iqbal Jawad Sahi Saddam Hussain Syed Sajid Ullah |
| author_sort | Ch Anwar Ul Hassan |
| collection | DOAJ |
| description | Fast access of data from Data Warehouse (DW) is a need for today’s Business Intelligence (BI). In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. DW has been widely used by several organizations to manage data and use it for Decision Support System (DSS). Many methods have been used to optimize the performance of fetching data from DW. Query cache method is one of those methods that play an effective role in optimization. The proposed work is based on a cache-based mechanism that helps DW in two aspects: the first one is to reduce the execution time by directly accessing records from cache memory, and the second is to save cache memory space by eliminating non-frequent data. Our target is to fill the cache memory with the most used data. To achieve this goal aging-based Least Frequently Used (LFU) algorithm is used by considering the size and frequency of data simultaneously. The priority and expiry age of the data in the cache memory is managed by dealing with both the size and frequency of data. LFU sets priorities and counts the age of data placed in cache memory. The entry with the lowest age count and priority is eliminated first from the cache block. Ultimately, the proposed cache mechanism efficiently utilized cache memory and fills a large performance gap between the main DW and the business user query. |
| first_indexed | 2024-12-23T23:13:20Z |
| format | Article |
| id | doaj.art-5f0b2b3b44734b3d92c5ed1d33ece878 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T23:13:20Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5f0b2b3b44734b3d92c5ed1d33ece8782022-12-21T17:26:36ZengIEEEIEEE Access2169-35362022-01-0110134721348010.1109/ACCESS.2022.31481319698087Optimizing the Performance of Data Warehouse by Query Cache MechanismCh Anwar Ul Hassan0Muhammad Hammad1Mueen Uddin2https://orcid.org/0000-0003-1919-3407Jawaid Iqbal3https://orcid.org/0000-0002-5045-7485Jawad Sahi4Saddam Hussain5https://orcid.org/0000-0003-1523-1330Syed Sajid Ullah6Department of Computer Science, Capital University of Science and Technology, Islamabad, PakistanDepartment of Computer Science, Capital University of Science and Technology, Islamabad, PakistanSchool of Digital Science, Universiti Brunei Darussalam, Gadong, Bandar Seri Begawan, BruneiDepartment of Computer Science, Capital University of Science and Technology, Islamabad, PakistanDepartment of Computer Science, COMSATS University, Islamabad, PakistanSchool of Digital Science, Universiti Brunei Darussalam, Gadong, Bandar Seri Begawan, BruneiDepartment of Electrical and Computer Engineering, Villanova University, Villanova, PA, USAFast access of data from Data Warehouse (DW) is a need for today’s Business Intelligence (BI). In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. DW has been widely used by several organizations to manage data and use it for Decision Support System (DSS). Many methods have been used to optimize the performance of fetching data from DW. Query cache method is one of those methods that play an effective role in optimization. The proposed work is based on a cache-based mechanism that helps DW in two aspects: the first one is to reduce the execution time by directly accessing records from cache memory, and the second is to save cache memory space by eliminating non-frequent data. Our target is to fill the cache memory with the most used data. To achieve this goal aging-based Least Frequently Used (LFU) algorithm is used by considering the size and frequency of data simultaneously. The priority and expiry age of the data in the cache memory is managed by dealing with both the size and frequency of data. LFU sets priorities and counts the age of data placed in cache memory. The entry with the lowest age count and priority is eliminated first from the cache block. Ultimately, the proposed cache mechanism efficiently utilized cache memory and fills a large performance gap between the main DW and the business user query.https://ieeexplore.ieee.org/document/9698087/Data warehouseoptimizationbig dataquery optimization |
| spellingShingle | Ch Anwar Ul Hassan Muhammad Hammad Mueen Uddin Jawaid Iqbal Jawad Sahi Saddam Hussain Syed Sajid Ullah Optimizing the Performance of Data Warehouse by Query Cache Mechanism IEEE Access Data warehouse optimization big data query optimization |
| title | Optimizing the Performance of Data Warehouse by Query Cache Mechanism |
| title_full | Optimizing the Performance of Data Warehouse by Query Cache Mechanism |
| title_fullStr | Optimizing the Performance of Data Warehouse by Query Cache Mechanism |
| title_full_unstemmed | Optimizing the Performance of Data Warehouse by Query Cache Mechanism |
| title_short | Optimizing the Performance of Data Warehouse by Query Cache Mechanism |
| title_sort | optimizing the performance of data warehouse by query cache mechanism |
| topic | Data warehouse optimization big data query optimization |
| url | https://ieeexplore.ieee.org/document/9698087/ |
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