---
sourceDocument: Australia ServiceNow AI Platform Administration
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/platform-administration

 Release :

    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia ServiceNow AI Platform Administration

ft:clusterId :

    - platadm

bundleId :

    - platadm

workflow :

    - Platform


---

# Manage table cleaner resource usage

# Manage table cleaner resource usage {#ariaid-title1}

Release version: Australia  
Updated March 12, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 1 minute to read  
Control the system resources used table cleaner by updating the table cleaner job.

## Before you begin

Role required: admin

## About this task

By default, the table cleaner job runs asynchronously with multiple producer threads creating chunks of records for deletion and multiple consumer threads processing the chunks and deleting records.

You can mitigate the impact to system performance by starting a table cleaner run using a smaller
dataset, checking resource usage as it runs, and then adjusting the number of producer and consumer threads as necessary to complete the job with minimal impact to your users.

## Procedure

1. Open the DMJobs \[sys_dm_job\] table by entering <kbd class="ph userinput">sys_dm_job.list</kbd> in the filter navigator.
2. Select the DMTableCleaner job record.
3. **Optional:** Contact ServiceNow Support to change the number of producers or consumers devoted to creating or deleting chunks of records.
4. Select Update.

## Result

Table cleaner begins the next run using the updated DMTableCleaner job configuration.

## What to do next

Check the status of the next table cleaner run by checking the values in the Chunks Errored column in the DMJob Runs \[sys_dm_run\] table. If a problem occurs, determine whether the issue occurred in all chunks or a single
chunk. View the status of the individual chunks in the DMJob Chunks \[sys_dm_chunk\] table by checking the values in the Message and State columns.