Monitoring and evaluating queries

Perform real-time workload monitoring of your WarehousePG (WHPG) queries, identify resource-heavy statements, manage database sessions, and tune SQL execution plans with the Query Monitor panel from the left sidebar.

Identifying and resolving workload bottlenecks

Track real-time execution progress and prevent resource-heavy statements from impacting system stability by using the Active Queries tab.

• Observe the Status bar to see the distribution of session states. Focus on sessions marked as Idle in Transaction or Waiting, as they typically indicate application-level leaks or locking contention.
• Identify memory spill activity by reviewing the Spill Activity section to find queries forced to use disk space. High Spill Size or Temp Files counts indicate that specific queries are exceeding their memory quotas and require optimization.
• Isolate long-running queries by using the Advanced Search to filter sessions by duration or specific users.
• If you have Admin or Operator privileges, use the Cancel action to gracefully stop a statement consuming excessive resources.

Understanding query statuses

Monitor the real-time state of database connections to identify performance bottlenecks and resource contention.

Resolving connection leaks and session bloat

Identify connection leaks and manage dormant processes that consume system slots by accessing the Sessions tab:

• To find dormant connections, sort the list by Idle time and find connections that have been open for long periods without activity.
• Identify which specific service might be responsible for a connection spike. Review the Application column to see which tools (such as psql, pgadmin, or ETL drivers) are initiating connections.
• If a session is unresponsive or holding critical locks, use the Terminate action to forcefully close the connection and release all associated system resources.

Authoring and tuning SQL statements

Explore data and analyze execution plans in a read-only environment with the Query Editor tab.

• Generate execution plans with the EXPLAIN and ANALYZE buttons, which help you visualize how the engine intends to process a query. Review the motion analysis to see how data is redistributed, broadcast, or gathered across segments.
• Identify performance bottlenecks by reviewing the warnings provided in the execution plan. Focus on "sequential scans" on large tables or "missing statistics," which are common causes of slow performance.
• Use the Format SQL button to clean up raw SQL for better readability.
• Once a query successfully executes, you can download the entire result set as a CSV file, allowing data portability into spreadsheets or external reporting tools.

Optimizing queries with the AI Assistant

Use the integrated AI Assistant to accelerate SQL authoring and simplify the debugging of complex performance issues.

• Generate queries from natural language pressing the keys Ctrl + K and asking the assistant to write a query for you using plain English. Because the assistant is schema-aware, it will reference your actual table and column names accurately.
• Optimize slow-running statements by providing a slow query statement into the assistant and asking for optimization suggestions. The assistant will analyze join efficiency, index usage, and cluster resource utilization to recommend a more efficient version of your code.
• When a query fails, provide the Postgres error message to the assistant. It will explain the failure in plain language and suggest the specific corrections needed to resolve the error.

Managing query history and results

Manage your recent query activity and retrieve data without re-executing heavy statements with the Results subtab within the Query Editor tab.

• View results from queries run in the last 24 hours to re-examine data grids and success indicators without placing a new load on the cluster.
• Refine past queries using the Open in Editor action and reloading a previous statement for further tuning.