Batch Hop-Constrained s-t Simple Path Query Processing in Large Graphs
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2023
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866910290521620480 |
|---|---|
| author | Yuan, Long Hao, Kongzhang Lin, Xuemin Zhang, Wenjie |
| author_facet | Yuan, Long Hao, Kongzhang Lin, Xuemin Zhang, Wenjie |
| contents | Hop-constrained s-t simple path (HC-s-t path) enumeration is a fundamental problem in graph analysis. Existing solutions for this problem focus on optimizing the processing performance of a single query. However, in practice, it is more often that multiple HC-s-t path queries are issued simultaneously and processed as a batch. Therefore, we study the problem of batch HC-s-t path query processing in this paper and aim to compute the results of all queries concurrently and efficiently as a batch. To achieve this goal, we first propose the concept of HC-s path query which can precisely characterize the common computation among different queries.We then devise a two-phase HC-s path query detection algorithm to identify the common HC-s path queries for the given HC-s-t path queries. Based on the detected HC-s path queries, we further devise an efficient HC-s-t path enumeration algorithm in which the common computation represented by HC-s path queries are effectively shared. We conduct extensive experiments on real-world graphs and the experimental results demonstrate that our proposed algorithm is efficient and scalable regarding processing multiple HC-s-t path queries in large graphs at billion-scale. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_01424 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Batch Hop-Constrained s-t Simple Path Query Processing in Large Graphs Yuan, Long Hao, Kongzhang Lin, Xuemin Zhang, Wenjie Databases Hop-constrained s-t simple path (HC-s-t path) enumeration is a fundamental problem in graph analysis. Existing solutions for this problem focus on optimizing the processing performance of a single query. However, in practice, it is more often that multiple HC-s-t path queries are issued simultaneously and processed as a batch. Therefore, we study the problem of batch HC-s-t path query processing in this paper and aim to compute the results of all queries concurrently and efficiently as a batch. To achieve this goal, we first propose the concept of HC-s path query which can precisely characterize the common computation among different queries.We then devise a two-phase HC-s path query detection algorithm to identify the common HC-s path queries for the given HC-s-t path queries. Based on the detected HC-s path queries, we further devise an efficient HC-s-t path enumeration algorithm in which the common computation represented by HC-s path queries are effectively shared. We conduct extensive experiments on real-world graphs and the experimental results demonstrate that our proposed algorithm is efficient and scalable regarding processing multiple HC-s-t path queries in large graphs at billion-scale. |
| title | Batch Hop-Constrained s-t Simple Path Query Processing in Large Graphs |
| topic | Databases |
| url | https://arxiv.org/abs/2312.01424 |