Nav-Index: A High-Performance, Adaptive Index for Shortest Path Queries in RDBMS
Maximilian Reif, Thomas Neumann
摘要
Shortest path queries are a fundamental operation on graphs with numerous applications. Efficiently executing shortest path searches in RDBMS is challenging, as graphs can not only be static relations but might also occur as ad-hoc intermediate results of complex analytical queries. Especially single-pair shortest path queries are difficult to accelerate, because they require minimizing the search space and intermediate results cannot be shared e.g. for multiple destinations. To address these challenges, we present Nav-Index, an adaptive index for relational DBMS that accelerates large-scale shortest path queries with seamless integration into SQL and relational algebra. Nav-Index switches adaptively between three modes: an ad-hoc generic mode using Dijkstra's algorithm, an ad-hoc optimized mode for sparse graphs leveraging contraction hierarchies (CH), and a table index mode for static graphs also leveraging CHs.
Graph DBMS typically provide specific implementations for such queries and are valuable for many workloads. In practice, however, existing systems show limited throughput for large-scale graphs such as road networks and offer limited optimization for analytical relational processing. Embedding Nav-Index into an RDBMS allows for a seamless composition with other relational operators, query decorrelation, cost-based optimization, morsel-driven parallelism, and pipelining. In the case of sparse graphs, Nav-Index's CH mode transforms the graph into a contraction hierarchy, allowing algorithmic speedups by orders of magnitude.
We implemented Nav-Index into the compiling RDBMS Umbra and evaluate it extensively on road networks from small cities to the whole planet and social graphs. In our experiments, Nav-Index outperforms all other database systems that we have tested by orders of magnitude due to algorithmic advantages and an efficient implementation. It can index the road network of Europe in under 12 minutes and Earth in less than 68 minutes, allowing planet-scale shortest path queries in milliseconds in a general-purpose RDBMS.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper4
- The LDBC Social Network Benchmark: Business Intelligence WorkloadGábor Szárnyas, Jack Waudby, Benjamin A. Steer, Dávid Szakállas 等VLDB 2023 · 被引用 103 次
- Robust Join Processing with Diamond Hardened JoinsAltan Birler, Alfons Kemper, Thomas NeumannVLDB 2024 · 被引用 23 次
- Breaking the Sorting Barrier for Directed Single-Source Shortest PathsRan Duan, Jiayi Mao, Xiao Mao, Xinkai Shu 等STOC 2025 · 被引用 8 次
- Robust Recursive Query Parallelism in Graph Database Management SystemsAnurag Chakraborty, Semih SalihogluVLDB 2025
相关 Paper
- Towards Efficient Shortest Path Counting on Billion-Scale GraphsYiqi Wang, Long Yuan, Zi Chen, Wenjie Zhang 等ICDE 2023 · 被引用 21 次
- Efficient Shortest Path Index Maintenance on Dynamic Road Networks with Theoretical GuaranteesDian Ouyang, Long Yuan, Lu Qin, Lijun Chang 等VLDB 2020 · 被引用 79 次
- Efficient Shortest Path Counting on Large Road NetworksYu-Xuan Qiu, Dong Wen, Lu Qin, Wentao Li 等VLDB 2022 · 被引用 22 次
- NaviX: A Native Vector Index Design for Graph DBMSs With Robust Predicate-Agnostic Search PerformanceGaurav Sehgal, Semih SalihogluVLDB 2025 · 被引用 12 次
- A Robust and Globally-Accurate Hierarchical Hub Labeling Index for SP-Distance Queries in Dynamic Road NetworksWei Liu, Ziqiang Yu, Xiaohui Yu, Yang Liu 等ICDE 2026
