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Drill-down Graphs

Some graphs in Performance Analyzer have a drill-down feature, allowing you to isolate and view workload telemetry within the specific context of a single database.

Step-by-Step Database Drill-down Procedure​

Follow these exact steps to trigger a database-scoped drill-down view:

  1. Open Performance Analyzer: Navigate to Performance Analyzer in the left sidebar. Go to the Overview, Queries, or Objects tab and click into a data source (or click Drill into: Workload – [source] from an insight card) to open its dashboard.

Dashboard Charts View

  1. Select the Database Metric Variant: On the dashboard's Analyzer tab, locate the metric dropdown selector on the top chart (which defaults to a metric like Load By Waits). Click the dropdown and select the (Database) variant — e.g., Load By Waits (Database).

  2. View Top Databases Chart: The chart instantly re-renders as a bar-per-database view titled Top Databases, displaying execution load broken down across databases.

  3. Trigger Database Drill-Down: Click directly on the bar corresponding to the database you want to inspect (e.g., postgres or testing_catalog).

  4. Database-Scoped Dashboard Reload: This action triggers the database drill-down. The page URL updates to a database-scoped route and reloads, displaying charts and metrics isolated strictly to that chosen database.

Metric Dropdown Selector​

You can dynamically switch the top chart metric at any time using the metric dropdown in the top right corner of the chart:

  • Load By Waits: Overall database load broken down by wait events (CPU, ClientRead, IO, etc.).
  • Load By Waits (Database): Load aggregated per database (drill-down trigger view).
  • Load By Waits (Host): Load broken down by client IP or host machine.
  • Load By Waits (BackendType): Load broken down by backend worker type.
  • Load By Waits (Application): Load broken down by connecting application name.
  • Load By Waits (User): Load broken down by database user account.
  • Load By Waits (Query): Load broken down by query hash / SQL ID.