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

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    - xanadu

ft:locale :

    - en-US

ft:publication_title :

    - Xanadu ServiceNow AI Platform Administration

ft:clusterId :

    - platadm

bundleId :

    - platadm

workflow :

    - Platform


---

# Import set performance

# Import set performance {#ariaid-title1}

* Release version: Xanadu
* 
* Updated January 30, 2025
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 1 minute to read

The algorithm transforms import sets from their staging table into their final
destination.  
Importing data via an import set requires two phases:

1. The data is loaded from a data source into a staging table
2. The data is transformed from the staging table into a target table
{#c_ImportSetsPerformImprovements__ol_dxl_1l4_y4}

The transform algorithm operates in "blocks" of 100 records at a time as opposed to the
previous algorithm which transformed a single record at a time. The newer approach allows the
application server to pre-fetch a variety of information relevant to each block of records,
reducing the number of unique interactions with the database and improving throughput.

Who should expect to see a performance improvement?

Any customer using import sets should expect to see a performance improvement in large
transformations.

What kinds of transformations benefit the most from these changes?

Transformations with a large number of reference or choice type columns see the largest
improvement.

What kind of transformations benefit the least?

Transformations that with complex or unkeyed coalesce conditions see a proportionately smaller
benefit.