Using LLMs to Analyze Spark SQL Plans

This article describes an automated workflow that uses large language models to examine Spark SQL execution plans, identifying performance bottlenecks and suggesting optimizations. The system detects anti-patterns like missed broadcast joins, data skew, and missing filters, cutting runtime by 40-95% on long-running jobs.