Introduction:

This document provides a comprehensive guide to resolving “Query Timeout Expired” errors in SQL Server. These errors typically occur when a query execution exceeds the configured timeout period due to long-running queries, blocking sessions, or insufficient system resources.

Document Purpose

The purpose of this document is to outline step-by-step procedures for identifying and addressing query timeout errors. Following these steps will help database administrators optimize query performance, manage system resources effectively, and maintain the integrity of SQL Server environments.

Document Structure:

  1. Blocking Session Identification:

Detailed steps to identify and resolve blocking sessions using SQL Server queries.

  1. Performance Tuning for Query Timeout Issues:

Procedures for identifying problematic queries, optimizing indexes and statistics, and improving execution plans.

  1. SQL Server Configuration for Timeout Settings:

      Guidelines for verifying and updating SQL Server and client application timeout settings.

Common Errors related to timeout expired

  1. Timeout expired. The timeout period elapsed prior to completion of the operation or the server is not responding. The statement has been terminated.
  2. Data.SqlClient.SqlException: Timeout expired. The timeout period elapsed prior to completion of the operation or the server is not responding.

This error is often caused by long-running queries, blocked processes, or insufficient system resources

Blocking session

To check the blocking session either we can use sp_who2 or the following query which provides the details of blocking session.

SELECT blocking_session_id AS BlockingSessionID, session_id AS BlockedSessionID, wait_type, wait_time, wait_resource
FROM sys.dm_exec_requests
WHERE blocking_session_id <> 0;

If we identify blocking, we can investigate the blocking session and resolve the conflict by terminating the blocking session.

Performance Tuning

To address query timeout expired errors, we can follow a two-step approach:

  1. Identify the query causing the timeout.
  2. Optimize the query performance by working with indexes and statistics.

Step 1: Identify the Query

We can either:

  • Ask the user to provide the database and table names involved in the SQL query causing the timeout.
  • Alternatively, we can ask the user to run the job that is generating the timeout error, allowing us to capture the query while it’s running.

While the query is running and causing the timeout, we can retrieve the SQL query being executed using the following query:

This will list all running queries and their relevant details

Select session_id,     status,     wait_type,     wait_time,     wait_resource,     blocking_session_id,    last_wait_type,     sql_text.text AS RunningSQLQuery
FROM sys.dm_exec_requests AS r
CROSS APPLY sys.dm_exec_sql_text(r.sql_handle) AS sql_text
WHERE r.status = ‘running’;

This query will give us the SQL query being executed, which will allow us to identify the table(s) involved.

Step 2: Optimize the Query

Once we’ve identified the query and the relevant table(s), we can proceed with optimization.

Check Index Fragmentation:

After identifying the tables involved, we can check the index fragmentation on the specific table. This will help us decide whether we should reorganize or rebuild the indexes. Rebuilding or reorganizing indexes can significantly improve query performance, especially if index fragmentation is high.

Use the following command to get index fragmentation statistics for a specific table:

Use [your_database_name]

SELECT S.name as ‘Schema’,

T.name as ‘Table’,

I.name as ‘Index’,

DDIPS.avg_fragmentation_in_percent,

DDIPS.page_count

FROM sys.dm_db_index_physical_stats (DB_ID(), NULL, NULL, NULL, NULL) AS DDIPS

INNER JOIN sys.tables T on T.object_id = DDIPS.object_id

INNER JOIN sys.schemas S on T.schema_id = S.schema_id

INNER JOIN sys.indexes I ON I.object_id = DDIPS.object_id

AND DDIPS.index_id = I.index_id

WHERE DDIPS.database_id = DB_ID() and T.name=’your_table_name

and I.name is not null

AND DDIPS.avg_fragmentation_in_percent > 0

ORDER BY DDIPS.avg_fragmentation_in_percent desc;

Steps to Reorganize or Rebuild Indexes:

We can use the following commands to reorganize or rebuild the indexes:

Reorganize Index (for fragmentation between 5% and 30%):

Use [your_database_name]

ALTER INDEX ALL ON dbo.your_table_name REORGANIZE;

Rebuild Index (for fragmentation greater than 30%):

Use [your_database_name]

ALTER INDEX ALL ON dbo.your_table_name REBUILD;

 Update Index Statistics:

After reorganizing or rebuilding the index, we should also update the statistics for the index to help SQL Server generate better query execution plans. We can use the following command to update statistics:

Use [your_database_name]

UPDATE STATISTICS dbo.your_table_name WITH FULLSCAN;

Updating statistics helps the query optimizer make better decisions about how to execute queries.

Ask the user to test Query Performance to see if the query timeout expired issue is resolved. If necessary, We can check the execution plan, and identify any further bottlenecks.

SQL Server Configuration (Query Timeout Settings)

Reason: The query timeout setting for the SQL Server or the client application is too short.

Solution:

Check the Job Properties in SQL Server Agent and verify if there is a timeout configured for the job step. We can user to increase the timeout if necessary.

SQL Server Timeout: In SSMS, the default query timeout is 0 (which means no timeout), but it can be set under Tools > Options > Query Execution > SQL Server > General.

Client Application Timeout: If the user is running the query from a client application (.NET application, ODBC connection), the query timeout is usually configurable in the connection string. Increase the timeout period in the connection string or application settings.

Increase the query timeout setting in SSMS or any application that connects to SQL Server to resolve the error.

Conclusion:

By following the steps above, we can address query timeout expired errors through database index optimization (reorganize/rebuild), statistics updates, and query performance improvements. Additionally, identifying and resolving issues like blocking, inefficient queries, or server resource bottlenecks will help to prevent query timeouts in the future.

It some times happen due to resource bottlenecks(Low Memory/CPU). Verify the memory and CPU utilization to further troubleshoot on this.

If issue persist we can enable SQL trace to further check on this.

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