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bigquery-troubleshooting

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Provides diagnostic workflows and step-by-step root-cause analysis procedures for actively broken, failing, or slow BigQuery jobs, execution graph and query plan stage bottlenecks, system performance issues, or unexpectedly expensive workloads. Use when interpreting symptoms, isolating bottlenecks, diagnosing cost spikes (on-demand query spend, capacity slot autoscaling, storage growth), execution graph stages or substep variables, identifying root causes, and determining remediation steps. Don't use for writing or optimizing SQL, proactive capacity planning, or storage layout design (use bigquery-optimization), or when the user already knows which telemetry they want and just needs the query (use bigquery-observability).

When to use

• diagnosing broken or failing BigQuery jobs
• analyzing slow BigQuery jobs
• identifying execution graph and query plan stage bottlenecks
• diagnosing system performance issues
• investigating unexpectedly expensive workloads
• diagnosing cost spikes in on-demand query spend
• diagnosing capacity slot autoscaling issues
• diagnosing storage growth issues

When not to use

• writing or optimizing SQL
• proactive capacity planning
• storage layout design
• retrieving specific telemetry when the user already knows which query to run

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