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bigquery-cost-auditlisted

Use when reviewing BigQuery spend, query failure patterns, or scan inefficiencies -- identifying which jobs, users, or projects drive cost, or preparing optimization recommendations for a cost review.
yeaight7/agent-powerups · ★ 7 · AI & Automation · score 75
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# BigQuery Cost Audit ## When to Use - Reviewing BigQuery query costs, failure patterns, or performance inefficiencies. - Identifying which jobs, users, or projects are driving the highest spend. - Preparing optimization recommendations for an engineering or cost-review meeting. - Auditing governance: scheduled jobs, duplicated logic, or low-value recurring queries. ## Goals - Identify the main cost drivers by job, project, and user. - Detect repeated waste patterns (full scans, failed retries, duplicated logic). - Suggest realistic optimizations with estimated impact. - Translate technical waste into business-language findings. ## What to Inspect ### Cost hotspots ```sql -- Top 20 most expensive jobs in the past 7 days SELECT job_id, user_email, query, total_bytes_processed / POW(1024, 4) AS tb_processed, ROUND(total_bytes_processed / POW(1024, 4) * 6.25, 2) AS estimated_cost_usd, creation_time FROM `region-us`.INFORMATION_SCHEMA.JOBS WHERE creation_time > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY) AND job_type = 'QUERY' AND state = 'DONE' ORDER BY total_bytes_processed DESC LIMIT 20; ``` ### Repeated failures ```sql SELECT error_result.reason, COUNT(*) AS failure_count, user_email, ANY_VALUE(query) AS sample_query FROM `region-us`.INFORMATION_SCHEMA.JOBS WHERE creation_time > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY) AND error_result IS NOT NULL GROUP BY error_result.reason, user_email ORDER BY failure_count DESC; ``` ### Missing par