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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A new catalog classifying 35 data error types into missing, incorrect, and redundant categories for tabular data, with definitions and examples to improve data quality management.
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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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A Catalog of Data Errors
A new catalog classifying 35 data error types into missing, incorrect, and redundant categories for tabular data, with definitions and examples to improve data quality management.