aws / aws/amazon-sagemaker-feedback

When loading in any csv file I get "Canvas can't process your request right now."

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#125 18 comments 3 reactions 0 assignees View on GitHub
bug
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Forks
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Description

### Product Version

- [ ] Amazon SageMaker Studio Classic
- [X] Amazon SageMaker Studio
- [ ] Issue is not related to SageMaker Studio

### Issue Description

Been a user for about 4 days - at first everything worked great, but now when I try to load a CSV locally or from S3 - even ones I've successfully loaded before I get

Canvas can't process your request right now. Try again in a few minutes, or contact your administrator and share the details below to resolve the issue.
If you're an administrator or an individual user, contact AWS support and provide the following code: <1121985d-e378-4f0c-8966-323ad8ddfd7e> to resolve the issue.

Super frustrating. I've tried logging out, shutting down canvas, logging out of AWS, logging back in again, starting it again a few times but no good.

I'm logged in as the root user (sorry!) so don't think is permissions.

Even a trivial file like the attached won't load in.

[test.csv](https://github.com/user-attachments/files/16766130/test.csv)

### Expected Behavior

Click data set on left sidebar, add tabular data set, drag a csv in, hit preview and it worked.

### Observed Behavior

Uploads, but on preview always shows

> Canvas can't process your request right now. Try again in a few minutes, or contact your administrator and share the details below to resolve the issue.
>
> If you're an administrator or an individual user, contact AWS support and provide the following code: <1121985d-e378-4f0c-8966-323ad8ddfd7e> to resolve the issue.

### Product Category

AutoML

### Feedback Category

Configuration and Setup

### Other Details

_No response_

Contributor guide

Open the contributing guide

Research direction

No repository files or tests are identified. Start by reproducing the CSV preview failure in Amazon SageMaker Studio with the attached file and both local and S3 sources, then record the displayed support code and relevant configuration details. Done means the failure's cause and an actionable resolution are documented.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws
Domain
cloud, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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