A Unified Architecture for Efficient Binary and Worst-Case Optimal Join Processing

2025-05-26

AI Summary

To address inefficient join processing in complex queries caused by intermediate result explosion, this paper proposes a unified join execution architecture that, for the first time, efficiently supports both traditional binary joins (hash and sort-based) and worst-case-optimal joins (WCOJs), such as Generic Join and Free Join. The architecture integrates multi-way merge, variable elimination, adaptive scheduling, and intermediate-result pruning—overcoming the limitation of prior work, which supports only a single join paradigm. Evaluated on standard benchmarks, our approach achieves 1.5× average speedup (up to 3.1×) over state-of-the-art systems for acyclic queries and 1.4× average speedup (up to 4.8×) for cyclic queries, significantly improving end-to-end performance for complex analytical workloads.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Data Mining & Knowledge Management: Intelligent Query Processing
• Search and Optimization: Distributed Search

Application Category

• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications

Abstract

Join processing is a fundamental operation in database management systems; however, traditional join algorithms often encounter efficiency challenges when dealing with complex queries that produce intermediate results much larger than the final query output. The emergence of worst-case optimal join (WCOJ) algorithms represents a significant advancement, offering asymptotically better performance by avoiding the enumeration of potentially exploding intermediate results. In this paper, we propose a unified architecture that efficiently supports both traditional binary joins and WCOJ processing. As opposed to the state-of-the-art, which only focuses on either hash-based or sort-based join implementations, our system accommodates both physical implementations of binary joins and WCOJ algorithms. Experimental evaluations demonstrate that our system achieves performance gains of up to 3.1x (on average 1.5x) and 4.8x (on average 1.4x) over the state-of-the-art implementation of Generic Join and Free Join methods, respectively, across acyclic and cyclic queries in standard query benchmarks.

Problem

• Efficiently process binary and worst-case optimal joins
• Unify traditional and advanced join algorithms
• Improve performance for complex database queries

Innovation

• Unified architecture for binary and WCOJ joins
• Supports hash-based and sort-based join implementations
• Achieves significant performance gains over existing methods