Diagnoses and optimizes slow Dremio queries using job profiles, reflection analysis, and execution plan inspection.
This skill provides a systematic workflow for developers to troubleshoot performance issues in Dremio Cloud. It automates the process of identifying slow jobs, analyzing planning versus execution times, evaluating reflection usage, and detecting common SQL anti-patterns like broad SELECT * statements or missing partition pruning. By leveraging Dremio's system tables and job profiles, the skill offers actionable recommendations—such as creating specific reflections or rewriting queries—to improve throughput, reduce latency, and lower cloud compute costs.
주요 기능
015 GitHub stars
02Detection of SQL anti-patterns and partition pruning failures
03Automated identification of slow jobs using recent history
04Evaluation of reflection status and matching logic
05Verification of performance improvements after applying optimizations
06Deep analysis of job profiles to pinpoint execution bottlenecks
사용 사례
01Troubleshooting a specific slow-running dashboard query in Dremio Cloud
02Identifying why a query is hitting raw data instead of using an active reflection
03Optimizing resource-intensive scans to reduce query execution time and costs
