SQL Server 2025 Series : ABORT_QUERY_EXECUTION Explained with Full Live Demo!

If you manage production workloads, you’ve probably seen situations where one problematic query keeps hurting performance for everyone else. In SQL Server 2025, Microsoft highlights ABORT_QUERY_EXECUTION as a Query Store hint that lets administrators block the future execution of a known problematic query without changing application code. That makes it a practical DBA-focused safeguard when you need control quickly.

In this blog, I’ll explain what ABORT_QUERY_EXECUTION is, why it matters, the prerequisites, and then walk through a full live demo using only the code shown below. I’ll also show how to verify whether the hint is configured and how to list blocked queries recorded in Query Store. Microsoft’s product and demo references position this feature as part of the broader query-processing and administrative control improvements in SQL Server 2025.


What is ABORT_QUERY_EXECUTION?

ABORT_QUERY_EXECUTION is a query hint showcased for SQL Server 2025 that can be applied through Query Store hints to block future executions of a specific query. The available Microsoft and demo references consistently describe it as an administrative control for stopping a known bad query from continuing to impact workload stability, while avoiding application code changes.

One important clarification: this feature is described as preventing future executions of the targeted query. The references do not describe it as a general-purpose replacement for terminating a query that is already running.


Why was this introduced?

The purpose is simple and practical. Sometimes a query is known to be expensive or disruptive, but the application team cannot change the code immediately. In that situation, Query Store hints already provide a way to influence query behavior without redeploying code, and ABORT_QUERY_EXECUTION extends that model by allowing the query to be blocked from future execution.

Available references describe this feature as a way to stop rogue or problematic queries from harming the rest of the workload and to improve reliability during incidents. That is what makes it a useful operational safety valve for DBAs.


Prerequisites

Before testing this feature, the main prerequisite is that Query Store must be enabled, because ABORT_QUERY_EXECUTION works through Query Store hints. This requirement is explicitly reflected in the demo references and supporting guidance.

For this walkthrough, you need:

  • SQL Server 2025
  • A database where your demo query can be captured in Query Store
  • Query Store enabled for that database

Full Demo Code

-- ABORT_QUERY_EXECUTION
CREATE OR ALTER procedure [dbo].[usp_procdisplaydata] @Col2 int
as
begin
SELECT top (150000)
[Col1],
[Col2],
[Col3],
[Col4],
[Col5]
FROM dbo.Table1
WHERE [Col2] = @Col2
ORDER BY [Col3];
END
EXEC [dbo].[usp_procdisplaydata] @Col2=2
SELECT TOP (20)
q.query_id,
qt.query_sql_text,
rs.count_executions,
rs.avg_duration,
rs.last_duration
FROM sys.query_store_query_text qt
JOIN sys.query_store_query q
ON qt.query_text_id = q.query_text_id
JOIN sys.query_store_plan p
ON q.query_id = p.query_id
JOIN sys.query_store_runtime_stats rs
ON p.plan_id = rs.plan_id
WHERE qt.query_sql_text LIKE N'%SELECT top (150000)%'
ORDER BY rs.last_execution_time DESC;
GO -- Query Id 38
EXEC sys.sp_query_store_set_hints
@query_id = 38,
@query_hints = N'OPTION (USE HINT (''ABORT_QUERY_EXECUTION''))';
GO
SELECT *
FROM sys.query_store_query_hints
WHERE query_id = 38;
GO
EXEC [dbo].[usp_procdisplaydata] @Col2=2
EXEC sys.sp_query_store_clear_hints
@query_id = 38;
GO
-- Blocked queries in Query Store
SELECT qsh.query_id,
q.query_hash,
qt.query_sql_text
FROM sys.query_store_query_hints AS qsh
INNER JOIN sys.query_store_query AS q
ON qsh.query_id = q.query_id
INNER JOIN sys.query_store_query_text AS qt
ON q.query_text_id = qt.query_text_id
WHERE UPPER(qsh.query_hint_text) LIKE '%ABORT[_]QUERY[_]EXECUTION%'

Step-by-Step Demo Explanation

1) Create the procedure and execute it once

The first part of the demo creates a stored procedure and executes it so the query text is captured in Query Store. That step is important because the feature is implemented through Query Store hints, and you need the corresponding query_id before you can apply the hint.

2) Find the query in Query Store

The next query searches the Query Store catalog views using the text pattern SELECT top (150000) to identify the relevant query and retrieve its query_id. In this demo script, the query id used is 38. The overall approach aligns with the feature’s dependency on Query Store metadata.

3) Apply ABORT_QUERY_EXECUTION

The core configuration step is:

EXEC sys.sp_query_store_set_hints
@query_id = 38,
@query_hints = N'OPTION (USE HINT (''ABORT_QUERY_EXECUTION''))';

This applies the ABORT_QUERY_EXECUTION query hint through Query Store for the specific query. The available demo and product materials explicitly show this feature being implemented through sp_query_store_set_hints.

4) Verify that the hint is configured

The following verification query checks the Query Store catalog view for the configured hint:

SELECT *
FROM sys.query_store_query_hints
WHERE query_id = 38;

This is a practical way to verify whether ABORT_QUERY_EXECUTION has been configured for that query in your database.

5) Execute the procedure again

After the hint is applied, the procedure is executed again so you can validate the configured behavior. Based on the available references, ABORT_QUERY_EXECUTION is designed to block future executions of the targeted query once the hint is in place.

6) Clear the hint

Once testing is complete, the hint is removed using:

EXEC sys.sp_query_store_clear_hints
@query_id = 38;

This completes the full end-to-end lifecycle: identify the query, apply the hint, verify it, test it, and clear it when it is no longer needed.

7) List blocked queries in Query Store

The final query in the script looks for entries in sys.query_store_query_hints where the configured hint text contains ABORT_QUERY_EXECUTION. This is useful when you want to audit or review queries that have been configured with this hint

SELECT qsh.query_id,
q.query_hash,
qt.query_sql_text
FROM sys.query_store_query_hints AS qsh
INNER JOIN sys.query_store_query AS q
ON qsh.query_id = q.query_id
INNER JOIN sys.query_store_query_text AS qt
ON q.query_text_id = qt.query_text_id
WHERE UPPER(qsh.query_hint_text) LIKE '%ABORT[_]QUERY[_]EXECUTION%'

ABORT_QUERY_EXECUTION is one of the more practical DBA-oriented capabilities highlighted in SQL Server 2025. It gives administrators a way to block the future execution of a known problematic query using Query Store hints, without changing application code. That makes it especially valuable when immediate workload protection is needed.


Watch the Full Demo

I’ve recorded a complete walkthrough of this setup on my YouTube channel JBSWiki. If you’re a visual learner, go check it out!

👉 Watch here: https://www.youtube.com/watch?v=SjjC18u-jjM


Thank You,
Vivek Janakiraman

Disclaimer:
The views expressed on this blog are mine alone and do not reflect the views of my company or anyone else. All postings on this blog are provided “AS IS” with no warranties, and confers no rights.

Proactively Managing Transactional Replication Latency with SQL Server

Transactional replication is a critical component of many SQL Server environments, providing high availability, load balancing, and other essential benefits. However, managing replication latency, the delay between an action occurring on the publisher and it being reflected on the subscriber, is vital for ensuring system performance and data integrity. In this blog post, we’ll explore a proactive approach to monitor and alert on replication latency, helping database administrators (DBAs) maintain optimal system health.

The Issue:

Replication latency can sometimes go unnoticed until it impacts the system performance or data accuracy, leading to potential data loss or business disruptions. Traditional monitoring techniques may not provide real-time alerts or may require significant manual intervention, making them less effective for immediate latency identification and resolution.

The Script:

To address this challenge, we introduce a SQL script designed by Vivek Janakiraman from JBSWiki, specifically crafted to monitor transactional replication latency in SQL Server environments. This script efficiently posts tracer tokens to specified publications and measures the time taken for these tokens to move through the replication components, providing a clear picture of any latency present in the system.

/*
Author: Vivek Janakiraman
Company: JBSWiki
Description: This script is used to alert in case there is Transactional replication Log reader or distribution agent latency.
It posts tracer tokens to specified publications and measures the latency to the distributor and subscriber.
*/

-- Switch to the publisher database to insert tracer tokens.
USE [Publisher_Database_Here] -- Use your publisher database name here.
-- Insert tracer tokens into the specified publications.
EXEC sys.sp_posttracertoken @publication = 'Publication_Name' -- Change appropriate Publication that should be monitored.
EXEC sys.sp_posttracertoken @publication = 'Publication_Name1' -- Change appropriate Publication that should be monitored.
-- Wait for 5 minutes to allow the tokens to propagate.
WAITFOR DELAY '00:05:00'

-- Switch to the distribution database to query latency information.
USE distribution
;WITH LatestEntries AS (
-- Select the latest entries for each publication and agent.
SELECT publication_id, agent_id, MAX(publisher_commit) AS MaxDate
FROM MStracer_tokens t
JOIN MStracer_history h ON t.tracer_id = h.parent_tracer_id
GROUP BY publication_id, agent_id
)
-- Select latency information for the latest tokens.
SELECT c.name, t.publication_id, h.agent_id, t.publisher_commit,
ISNULL(DATEDIFF(s,t.publisher_commit,t.distributor_commit), 299) as 'Time To Dist (sec)',
ISNULL(DATEDIFF(s,t.distributor_commit,h.subscriber_commit), 299) as 'Time To Sub (sec)'
INTO #REPL_LATENCY
FROM MStracer_tokens t
JOIN MStracer_history h ON t.tracer_id = h.parent_tracer_id
JOIN distribution.dbo.MSdistribution_agents c ON h.agent_id = c.id
JOIN LatestEntries le ON t.publication_id = le.publication_id AND h.agent_id = le.agent_id AND t.publisher_commit = le.MaxDate
ORDER BY t.publisher_commit DESC

-- Check if there is any latency beyond acceptable limits and select those records.
IF EXISTS (SELECT 1 FROM #REPL_LATENCY WHERE ([Time To Dist (sec)] > 30 OR [Time To Sub (sec)] > 30))
BEGIN
SELECT name, publication_id, agent_id, publisher_commit, [Time To Dist (sec)], [Time To Sub (sec)]
INTO #REPL_LATENCY_Email
FROM #REPL_LATENCY
WHERE ([Time To Dist (sec)] > 30 OR [Time To Sub (sec)] > 30)
END

-- Prepare the HTML body content for the email alert.
DECLARE @body_content NVARCHAR(MAX);
SET @body_content = N'
<style>
table.GeneratedTable {
width: 100%;
background-color: #D3D3D3;
border-collapse: collapse;
border-width: 2px;
border-color: #A9A9A9;
border-style: solid;
color: #000000;
}
table.GeneratedTable td, table.GeneratedTable th {
border-width: 2px;
border-color: #A9A9A9;
border-style: solid;
padding: 3px;
}
table.GeneratedTable thead {
background-color: #A9A9A9;
}
</style>
<table class="GeneratedTable">
<thead>
<tr>
<th>name</th>
<th>publication_id</th>
<th>agent_id</th>
<th>publisher_commit</th>
<th>[Time To Dist (sec)]</th>
<th>[Time To Sub (sec)]</th>
</tr>
</thead>
<tbody>' +
CAST(
(SELECT td = name, '',
td = publication_id, '',
td = agent_id, '',
td = publisher_commit, '',
td = [Time To Dist (sec)], '',
td = [Time To Sub (sec)], ''
FROM [dbo].#REPL_LATENCY_Email
FOR XML PATH('tr'), TYPE
) AS NVARCHAR(MAX)
) +
N'</tbody>
</table>';

-- Send an email alert if there is any latency issue found.
IF EXISTS (SELECT TOP 1 * FROM [dbo].#REPL_LATENCY_Email)
BEGIN
EXEC msdb.dbo.sp_send_dbmail @profile_name = 'JBSWIKI',
@body = @body_content,
@body_format = 'HTML',
@recipients = 'jvivek2k1@yahoo.com',
@subject = 'ALERT: Transactional Replication Latency Alert';
END

-- Cleanup temporary tables.
DROP TABLE #REPL_LATENCY
DROP TABLE #REPL_LATENCY_Email

The Solution:

The script works by first posting tracer tokens to the specified publications within the publisher database. It then waits for a predetermined amount of time (defaulted to 5 minutes in the script) to allow the tokens to propagate through the system. Following this, the script measures the latency to the distributor and subscriber, providing a detailed report of the time taken in each stage of the replication process.

This information is then used to generate an HTML-formatted email alert if the latency exceeds predefined thresholds (30 seconds in the provided script), allowing for immediate action to be taken. The use of HTML formatting in the email ensures that the information is presented in an easily digestible format, facilitating quick understanding and response by the DBA.

Conclusion:

Proactive monitoring and management of transactional replication latency are paramount for maintaining the health and performance of SQL Server environments. The script provided offers a straightforward and effective solution for DBAs to stay ahead of potential replication issues. By automating the process of latency detection and alerting, this approach not only saves valuable time but also helps in preventing the negative impact of replication latency on business operations.

Remember, while this script serves as a valuable tool in your monitoring arsenal, it’s also important to tailor the solution to your specific environment and requirements. Regularly reviewing and adjusting the latency thresholds and monitoring frequency will ensure you continue to get the most out of your replication setup.

For more tutorials and tips on SQL Server, including performance tuning and database management, be sure to check out our JBSWiki YouTube channel.

Thank You,
Vivek Janakiraman

Disclaimer:
The views expressed on this blog are mine alone and do not reflect the views of my company or anyone else. All postings on this blog are provided “AS IS” with no warranties, and confers no rights.