BigQuery Cost Monitoring
Last updated
Last updated
Paradime's BigQuery Cost Monitoring dashboard provides comprehensive insights into your BigQuery usage and costs. This tool enables you to monitor, analyze, and optimize your BigQuery operations, helping you make data-driven decisions to reduce expenses without compromising performance.
Prerequisites
Completed the Cost Management setup in Radar's Get Started guide.
The BigQuery Cost Optimization dashboard is divided into two main sections:
Overview: Provides a high-level summary of your BigQuery costs and usage. [link]
Details: Offers in-depth analytics for specific queries and performance metrics. [link]
The Overview section gives you a broad perspective on your BigQuery costs and usage patterns, allowing you to uncover key insights, including:
Value: Understand daily spending patterns across projects and query types.
How to use:
Monitor daily spend trends to identify any unusual spikes or patterns.
Compare spend across different projects and query types to prioritize optimization efforts.
Use this information to guide resource allocation and cost management strategies.
Value: Identify high-cost users and queries.
How to use:
Focus optimization efforts on the users and queries with the highest costs.
Investigate high-cost queries to determine if they can be optimized or if their usage justifies the cost.
Consider implementing user quotas or query optimization strategies for top spenders.
Value: Identify high-cost dbt models
How to use:
Focus optimization efforts on the dbt™ models with the highest costs.
Investigate if a dbt™ model's usage justifies the cost.
Value: Visualize slot usage and query patterns over time.
How to use:
Identify peak usage times for slot allocation and query volume.
Adjust your BigQuery reservation or scheduling based on observed patterns.
Look for opportunities to balance workloads across different hours of the day.
The Details section allows you to dive deep into specific query performance and cost metrics, providing comprehensive insights such as:
Value: Analyze costs and performance for individual queries.
How to use:
Enter a specific query hash to analyze its cost trends over time.
Identify which users are running high-cost queries most frequently.
Use this information to guide query optimization efforts and user education.
Value: Understand the resource consumption and runtime of your queries.
How to use:
Monitor the ratio of processed to shuffled bytes to identify queries that may benefit from optimization.
Track query runtime trends to spot performance degradation or improvements over time.
Use these metrics to prioritize which queries to optimize for better performance and cost-efficiency.
Value: Visualize slot usage patterns for better resource allocation.
How to use:
Identify days or periods with high slot usage.
Correlate slot usage with other metrics like query spend and runtime.
Use this information to adjust your BigQuery slot reservations or workload scheduling.
In the Overview section, use the "Select date range", "Select user", and "Select project" dropdowns to focus your analysis.
In the Details section, use the "Select date range" dropdown and the query hash input to analyze specific time periods and queries.
The dashboard will automatically update to reflect your selections, allowing for focused analysis of BigQuery costs and performance.
