This technical report extends the SIGMOD 2025 paper "A Modular Graph-Native Query Optimization Framework" by providing a comprehensive exposition of GOpt's advanced technical mechanisms, implementation strategies, and extended evaluations. While the original paper introduced GOpt's unified intermediate representation (GIR) and demonstrated its performance benefits, this report delves into the framework's implementation depth: (1) the full specification of GOpt's optimization rules; (2) a systematic treatment of semantic variations (e.g., homomorphism vs. edge-distinct matching) across query languages and their implications for optimization; (3) the design of GOpt's Physical integration interface, enabling seamless integration with transactional (Neo4j) and distributed (GraphScope) backends via engine-specific operator customization; and (4) a detailed analysis of plan transformations for LDBC benchmark queries.

翻译：本技术报告对SIGMOD 2025论文《模块化图原生查询优化框架》进行了扩展，全面阐述了GOpt框架的高级技术机制、实现策略及扩展评估。原论文介绍了GOpt的统一中间表示（GIR）并论证了其性能优势，而本报告则深入探讨了该框架的实现细节：（1）完整规范了GOpt的优化规则；（2）系统处理了不同查询语言间的语义变体（如同态匹配与边区分匹配）及其对优化的影响；（3）设计了GOpt的物理集成接口，通过引擎特定的算子定制，实现了与事务型（Neo4j）和分布式（GraphScope）后端系统的无缝集成；（4）对LDBC基准查询的计划转换进行了详细分析。