What Causes 'Timeout expired' Errors in SQL Server and How Can I Troubleshoot Them?

SQL Server Timeout Errors: Troubleshooting and Prevention

The error message "Timeout expired. The timeout period elapsed prior to completion of the operation or the server is not responding. The statement has been terminated" often indicates a query exceeding its allotted execution time. Let's explore common causes and solutions.

Root Causes:

Several factors can contribute to SQL Server timeouts:

• Deadlocks: Concurrent processes vying for the same resources can create a deadlock, halting progress indefinitely.
• Inaccurate Database Statistics: Outdated statistics lead to inefficient query plans, prolonging execution.
• Complex Queries: Intricate queries with numerous joins or subqueries can be computationally expensive.

Resolution Strategies:

Follow these steps to diagnose and resolve timeout issues:

1. Deadlock Detection:

Use SQL Server Management Studio (SSMS): Access the "Activity Monitor" to identify blocked processes. Examine their status and associated queries to pinpoint the deadlock.

2. Statistics Update:

Refresh database statistics using these commands:

EXEC sp_updatestats;
DBCC FREEPROCCACHE;

sp_updatestats updates statistical information, while DBCC FREEPROCCACHE clears the procedure cache, forcing a new query plan generation.

3. Forced Plan Recompilation:

If a specific query is consistently causing timeouts, force recompilation to prevent the use of potentially inefficient cached plans:

SELECT <your_query> OPTION (RECOMPILE);

4. Query Optimization:

For persistently slow queries, detailed optimization is necessary. Execute the problematic query in SSMS and analyze its execution plan. If you need assistance optimizing a specific query, please provide it in a separate question.

Application Startup Considerations:

The example code's call to sp_OnlineUsers_Update_SessionEnd_And_Online during application startup might negatively impact performance if the OnlineUsers table is large. Consider implementing techniques like pagination or batch processing to improve startup time and reduce database load.

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