ReSequel uses LLMs guided by metadata-derived templates and sampling-based verification to rewrite SQL queries, delivering up to 16x workload speedups over native DBMSs and 22x over prior LLM baselines across eight benchmarks and three systems.
Agarwal, Ashish Mittal, Saksham Chintalapani, Rekha Singhal, and Biswapesh Chatterjee
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.DB 2years
2026 2representative citing papers
Presto is extended to GPU-aware execution using cuDF experiments on TPC-H, delivering up to 6x cost/performance gains over CPU Presto via optimized data paths and inter-operator communication.
citing papers explorer
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ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling
ReSequel uses LLMs guided by metadata-derived templates and sampling-based verification to rewrite SQL queries, delivering up to 16x workload speedups over native DBMSs and 22x over prior LLM baselines across eight benchmarks and three systems.
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Accelerating Presto with GPUs
Presto is extended to GPU-aware execution using cuDF experiments on TPC-H, delivering up to 6x cost/performance gains over CPU Presto via optimized data paths and inter-operator communication.