Usage → User
Analyze BigQuery usage patterns by user and service account to understand who is consuming resources and identify optimization opportunities.
The User tab provides detailed insights into how individual users and service accounts are consuming BigQuery resources. This view helps identify heavy users, understand usage patterns, and optimize resource allocation.
Overview
The User usage view enables you to:
- Track which users consume the most slots and process the most data
- Understand query patterns by user
- Identify users running inefficient queries
- Monitor service account usage for automated workloads
Page Controls
Project Filter
Filter metrics to specific BigQuery projects.
Cost Toggle
Toggle between resource metrics (slots, bytes) and cost estimates (USD).
Cards & Tables
Access Query Count by User
The primary table showing per-user metrics including:
- Query count (24h, 7d, 30d)
- Slots used or cost (24h, 7d, 30d)
- Bytes processed (24h, 7d, 30d)
Click on any user to see their detailed query history.
Query Elapsed Time Distribution
A histogram showing how query execution times are distributed across different time buckets (sub-second, seconds, minutes, etc.).
Query Execution Time Percentiles
A chart showing p50, p90, and p99 execution time trends over time, helping identify if query performance is degrading.
Slots Used Percentiles
A chart showing slot consumption percentiles over time to understand resource-intensive query patterns.
Bytes Processed Distribution
A histogram showing the distribution of data scanned per query.
Bytes Processed Percentiles
A chart showing bytes processed percentiles over time.
User Details Page
Click on any username to see:
- Summary metrics for the selected user
- Complete query history
- Tables accessed by this user
- Historical usage trends
Use Cases
Identifying Heavy Users
- Sort by slots used to find users consuming the most compute
- Review their query patterns to identify optimization opportunities
- Work with heavy users to optimize their workflows
Service Account Monitoring
- Monitor automated workloads for unexpected spikes
- Identify service accounts running inefficient scheduled queries
- Track costs from ETL/ELT pipelines
Cost Allocation
- Export user-level metrics for chargeback reporting
- Attribute costs to specific teams or departments
- Track cost trends by user over time
Updated 16 days ago