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 Execution Timeout Expired.
Application Type
Traditional Web

Hi Community,  

I'm currently dealing with a critical issue where I encounter the following error:  

Error executing query. Execution Timeout Expired. The timeout period elapsed prior to completion of the operation or the server is not responding.  


The query works as expected before but it brokes suddenly. It takes an average of 980ms to execute, which I believe should be well within the timeout threshold and works fine in non-production environments and other sql tools but fails in production.  

The query itself appears to be optimized and doesn't show any obvious issues during testing.  

I’d appreciate your insights on what could be causing this issue in production. Are there any specific aspects I should investigate?  


Thanks in advance for your help!  

2024-09-12 02-43-38
Deepsagar Dubey

Hi @Sandip Saha 

I don't know exactly whats your use case but i also experienced same errors sometime in Traditional web apps and followed below steps -

1. First try to exceed timeout for specific SQL widget (i.e. 300 seconds)

2. if still there is error then try to debug query might be data you are trying to fetch has some issue, i.e. if there are many joins and data is not matched.

I hope it'll help you.

Thanks
Deep

2019-04-09 00-57-55
carl ruhle

Hi @Sandip Saha ,

on production environments normally there will have more data than the other environments. 

Have you looked at the explain plan of the statement? 

In the where clause does the columns have index? 

Is it a single table select or it's a join/union?

Are you fetching only the columns that you need? 

Group by and/or statements? 

Hope it helps you, best regards 

2021-11-12 04-59-31
Manikandan Sambasivam

Hi,

Please follow these steps:

  1. Increase Timeout: Increase the timeout setting and test the query.

  2. Test with Production Data in Lower Environment: Replicate the issue by testing the production data in a lower environment to identify potential problems.

  3. Optimize the Query:

    • Avoid using SELECT *; retrieve only the necessary columns.
    • Ensure indexes are utilized effectively.
    • Optimize JOINs, WHERE clauses, and GROUP BY operations for better performance.


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