7 papers · 1 filter
Demonstrating GenDB: Instance-Optimized and Customized Query Processing Code Generation via LLM Agents
Jiale Lao, Immanuel Trummer
Traditional query processing engines require continuous development and extensions to support new techniques and user requirements, and in some cases, entirely new systems must be…
WAter: A Workload-Adaptive Knob Tuning System based on Workload Compression
Yibo Wang, Jiale Lao, Chen Zhang +3
Selecting appropriate values for the configurable parameters of Database Management Systems (DBMS) to improve performance is a significant challenge. Recent machine learning (ML)-b…
SemBench: A Benchmark for Semantic Query Processing Engines
Jiale Lao, Andreas Zimmerer, Olga Ovcharenko +12
We present a benchmark targeting a novel class of systems: semantic query processing engines. Those systems rely inherently on generative and reasoning capabilities of state-of-the…
GenDB: The Next Generation of Query Processing -- Synthesized, Not Engineered
Jiale Lao, Immanuel Trummer
Traditional query processing relies on engines that are carefully optimized and engineered by many experts. However, new techniques and user requirements evolve rapidly, and existi…
QUITE: A Query Rewrite System Beyond Rules with LLM Agents
Yuyang Song, Hanxu Yan, Jiale Lao +5
Query rewrite transforms SQL queries into semantically equivalent forms that run more efficiently. Existing approaches mainly rely on predefined rewrite rules, but they handle a li…
SQLBarber: A System Leveraging Large Language Models to Generate Customized and Realistic SQL Workloads
Jiale Lao, Immanuel Trummer
Database research and development often require a large number of SQL queries for benchmarking purposes. However, acquiring real-world SQL queries is challenging due to privacy con…