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๐Ÿ“Š Monitoring SQL Warehouses in Databricks โ€“ Key Insights! ๐Ÿ“Š

Ajay-Pandey
Esteemed Contributor III

In todayโ€™s data-driven world, visibility into SQL warehouse performance is crucial. Hereโ€™s a quick guide to monitoring a SQL warehouse directly from the Databricks UI.

When you open the Monitoring tab on your SQL warehouse, youโ€™ll find powerful metrics that can help you optimize performance and efficiency:

1๏ธโƒฃ Live Statistics: See real-time data on active and queued queries, warehouse status, and cluster count.

2๏ธโƒฃ Time Scale Filter: Customize your time range for deeper analysis. By default, you see the past 8 hours, but you can expand to 24 hours, 7 days, or even 14 days. Thereโ€™s also an option to set a custom period.

3๏ธโƒฃ Peak Query Count Chart: Track the highest number of concurrent queries (running or queued) in 5-minute intervals. This excludes metadata queries for a cleaner view.

4๏ธโƒฃ Running Clusters Chart: Monitor the clusters allocated to your warehouse, ensuring you stay within configured limits for peak efficiency.

5๏ธโƒฃ Query History Table: Review detailed records of all active queries during your time frame, including start times, durations, and users. Filters allow you to refine by user, query duration, status, and type.

Whether youโ€™re troubleshooting performance or optimizing resource use, these tools empower you to manage SQL warehouses with precision.

#Databicks #DataAnalytics #SQL #DataOps #DataMonitoring

Ajay Kumar Pandey
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