The Data Wrangler Export does not consider the multi-line detection setting

When exporting a Data Wrangler flow to an inference pipeline, issues with multi-line detection can cause problems in the exported data. This is a known limitation when working with data that contains new line characters within fields.

While the multi-line detection setting works correctly during the initial data import process in SageMaker Canvas Data Wrangler (allowing you to see the data displayed properly in the interface), this setting might not be properly carried over when exporting the flow to an inference pipeline.

The error you're experiencing could be related to this discrepancy between how Data Wrangler handles multi-line data during import versus export. When you receive the "An unexpected error occurred when preparing your flow for inference" message, it could be because the export process is not properly handling the multi-line content in your data.

To troubleshoot this issue, you could try:

1. Pre-processing your data to handle the new line characters before importing it into Data Wrangler (perhaps replacing them with another character)
2. Checking if there are any empty columns in your dataset, as this can sometimes cause export issues
3. Adding a transformation step that explicitly handles the multi-line content before export

If these approaches don't resolve the issue, you may need to reach out to AWS Support for further assistance, as they can investigate the specific details of your setup and provide more targeted guidance.
Sources
Error Exporting Data Wrangler Flow to Inference Pipeline | AWS re:Post
Create a data flow - Amazon SageMaker