Query optimization-oriented lateral expansion method of distributed geological borehole database
In order to reduce the resource occupancy and retrieval efficiency of geological drilling databases, this study proposes a distributed horizontal expansion method for query optimization of geological drilling databases by constructing a comprehensive geological data subtree, analyzing the characteri...
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2023-12-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2022-0554 |
| _version_ | 1797397437002809344 |
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| author | Luo Qingjia |
| author_facet | Luo Qingjia |
| author_sort | Luo Qingjia |
| collection | DOAJ |
| description | In order to reduce the resource occupancy and retrieval efficiency of geological drilling databases, this study proposes a distributed horizontal expansion method for query optimization of geological drilling databases by constructing a comprehensive geological data subtree, analyzing the characteristics of distributed databases and elements in geological databases, and quickly retrieving data resources based on element attributes. In addition, this study has designed a method to horizontally extend the database designed for drilling holes using a multi-constraint model in order to achieve extension optimization of the distributed geological drilling database. Experiments are conducted to verify the performance and applicability of the proposed method. The experiment shows that when the geological data capacity is 80 GB, the capacity level of the geological database can be extended to 41 × 105TB using the method proposed in this study. The retrieval efficiency is higher than 89% and the resource occupancy rate is lower than 12% after the horizontal expansion of the database. By using this research method, the horizontal expansion of the geological drilling database is more effective, and can effectively reduce the resource occupancy rate and retrieval efficiency of the geological drilling databases. This has value significance for geological drilling with efficiency improvement and development. |
| first_indexed | 2024-03-09T01:10:00Z |
| format | Article |
| id | doaj.art-bc3b109768ad48c6b7ac93739e7316b6 |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-03-09T01:10:00Z |
| publishDate | 2023-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-bc3b109768ad48c6b7ac93739e7316b62023-12-11T07:36:16ZengDe GruyterOpen Geosciences2391-54472023-12-01151641310.1515/geo-2022-0554Query optimization-oriented lateral expansion method of distributed geological borehole databaseLuo Qingjia0School of Information Engineering, Jiangmen Polytechnic, Jiangmen529090, ChinaIn order to reduce the resource occupancy and retrieval efficiency of geological drilling databases, this study proposes a distributed horizontal expansion method for query optimization of geological drilling databases by constructing a comprehensive geological data subtree, analyzing the characteristics of distributed databases and elements in geological databases, and quickly retrieving data resources based on element attributes. In addition, this study has designed a method to horizontally extend the database designed for drilling holes using a multi-constraint model in order to achieve extension optimization of the distributed geological drilling database. Experiments are conducted to verify the performance and applicability of the proposed method. The experiment shows that when the geological data capacity is 80 GB, the capacity level of the geological database can be extended to 41 × 105TB using the method proposed in this study. The retrieval efficiency is higher than 89% and the resource occupancy rate is lower than 12% after the horizontal expansion of the database. By using this research method, the horizontal expansion of the geological drilling database is more effective, and can effectively reduce the resource occupancy rate and retrieval efficiency of the geological drilling databases. This has value significance for geological drilling with efficiency improvement and development.https://doi.org/10.1515/geo-2022-0554query optimizationmultiple constraint modelgeological data subtreedistributed database |
| spellingShingle | Luo Qingjia Query optimization-oriented lateral expansion method of distributed geological borehole database Open Geosciences query optimization multiple constraint model geological data subtree distributed database |
| title | Query optimization-oriented lateral expansion method of distributed geological borehole database |
| title_full | Query optimization-oriented lateral expansion method of distributed geological borehole database |
| title_fullStr | Query optimization-oriented lateral expansion method of distributed geological borehole database |
| title_full_unstemmed | Query optimization-oriented lateral expansion method of distributed geological borehole database |
| title_short | Query optimization-oriented lateral expansion method of distributed geological borehole database |
| title_sort | query optimization oriented lateral expansion method of distributed geological borehole database |
| topic | query optimization multiple constraint model geological data subtree distributed database |
| url | https://doi.org/10.1515/geo-2022-0554 |
| work_keys_str_mv | AT luoqingjia queryoptimizationorientedlateralexpansionmethodofdistributedgeologicalboreholedatabase |