This research explores LLM agents for database join order optimization through iterative testing.
- •Agents test multiple join orders iteratively, learning from results to optimize query plans
- •Frontier models achieved 1.288x improvement in query latency and 41% P90 reduction on Join Order Benchmark
- •Handles complex queries where traditional optimizers fail with LIKE predicates
- •Structured outputs ensure proposed join orders remain valid through grammar enforcement
- •Anytime algorithm allows larger time budgets to incrementally improve performance
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