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 …
Complex Graph Patterns (CGPs), which combine pattern matching with relational operations, are widely used in real-world applications. Existing systems rely on monolithic architectures for CGPs, which restrict their ability to integrate multiple query …
GOpt is built on top of a unified intermediate representation (IR) that is capable of capturing both graph and relational operations, thereby streamlining the optimization of graph queries.
We develop GLogS system, allowing users to interactively submit queries using a declarative language, which will be compiled and automatically optimized, and eventually executed on the GAIA dataflow engine.
The recent ISO SQL:2023 standard adopts SQL/PGQ (Property Graph Queries), facilitating graph-like querying within relational databases. This advancement, however, underscores a significant gap in how to effectively optimize SQL/PGQ queries within …
Interactive GPM (iGPM) is becoming increasingly important for data scientists to explore graphs in real life, where a series of graph pattern matching (GPM) queries are created and submitted in an interactive manner based on the insights provided by …
To develop a graph pattern matching system in the distributed context, while gluing together the academic results of optimal join algorithms and industrial efforts of query language