Distributed Subgraph Query Processing Using Filtering Scores on Spark
As various services have been generating large-scale graphs to represent multiple relationships between objects, studies have been conducted to obtain subgraphs with particular patterns. In this paper, we propose a distributed query processing method to efficiently search a subgraph for a large grap...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/17/3645 |
| _version_ | 1797582680458526720 |
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| author | Kyoungsoo Bok Minyoung Kim Hyeonbyeong Lee Dojin Choi Jongtae Lim Jaesoo Yoo |
| author_facet | Kyoungsoo Bok Minyoung Kim Hyeonbyeong Lee Dojin Choi Jongtae Lim Jaesoo Yoo |
| author_sort | Kyoungsoo Bok |
| collection | DOAJ |
| description | As various services have been generating large-scale graphs to represent multiple relationships between objects, studies have been conducted to obtain subgraphs with particular patterns. In this paper, we propose a distributed query processing method to efficiently search a subgraph for a large graph on Spark. To reduce unnecessary processing costs, the search order is determined by filtering scores using the probability distribution. The partitioned queries are searched in parallel in the distributed graph of each slave node according to the search order, and the local search results obtained from each slave node are combined and returned. The query is partitioned in triplets based on the determined search order. The performance of the proposed method is compared with the performance of existing methods to demonstrate its superiority. |
| first_indexed | 2024-03-10T23:24:52Z |
| format | Article |
| id | doaj.art-99b53b91826648318ff439c619dc2934 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T23:24:52Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-99b53b91826648318ff439c619dc29342023-11-19T08:02:05ZengMDPI AGElectronics2079-92922023-08-011217364510.3390/electronics12173645Distributed Subgraph Query Processing Using Filtering Scores on SparkKyoungsoo Bok0Minyoung Kim1Hyeonbyeong Lee2Dojin Choi3Jongtae Lim4Jaesoo Yoo5Department of Artificial Intelligence Convergence, Wonkwang University, Iksandae 460, Iksan 54538, Jeonbuk, Republic of KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-gu, Cheongju 28644, Chungbuk, Republic of KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-gu, Cheongju 28644, Chungbuk, Republic of KoreaDepartment of Computer Engineering, Changwon National University, Changwondaehak-ro 20, Uichang-gu, Changwon 51140, Gyeongsangnam, Republic of KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-gu, Cheongju 28644, Chungbuk, Republic of KoreaDepartment of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-gu, Cheongju 28644, Chungbuk, Republic of KoreaAs various services have been generating large-scale graphs to represent multiple relationships between objects, studies have been conducted to obtain subgraphs with particular patterns. In this paper, we propose a distributed query processing method to efficiently search a subgraph for a large graph on Spark. To reduce unnecessary processing costs, the search order is determined by filtering scores using the probability distribution. The partitioned queries are searched in parallel in the distributed graph of each slave node according to the search order, and the local search results obtained from each slave node are combined and returned. The query is partitioned in triplets based on the determined search order. The performance of the proposed method is compared with the performance of existing methods to demonstrate its superiority.https://www.mdpi.com/2079-9292/12/17/3645subgraph querysearch orderdistributed graphfiltering score |
| spellingShingle | Kyoungsoo Bok Minyoung Kim Hyeonbyeong Lee Dojin Choi Jongtae Lim Jaesoo Yoo Distributed Subgraph Query Processing Using Filtering Scores on Spark Electronics subgraph query search order distributed graph filtering score |
| title | Distributed Subgraph Query Processing Using Filtering Scores on Spark |
| title_full | Distributed Subgraph Query Processing Using Filtering Scores on Spark |
| title_fullStr | Distributed Subgraph Query Processing Using Filtering Scores on Spark |
| title_full_unstemmed | Distributed Subgraph Query Processing Using Filtering Scores on Spark |
| title_short | Distributed Subgraph Query Processing Using Filtering Scores on Spark |
| title_sort | distributed subgraph query processing using filtering scores on spark |
| topic | subgraph query search order distributed graph filtering score |
| url | https://www.mdpi.com/2079-9292/12/17/3645 |
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