Microsoft Fabric: [TooManyRequestsForCapacity] HTTP Response code 430: This Spark job can’t be run b

[TAnalytics]

Hello guys,

I've set up a free Fabric trial and also in Azure I've created a trial work Fabric workspace. However, If I create a OneLake and try to load a csv file into a table I get the following error message:

[TooManyRequestsForCapacity] HTTP Response code 430: This Spark job can’t be run because you’ve hit a Spark compute or API rate limit. To proceed, cancel an active Spark job through the Monitoring hub, choose a larger capacity SKU, or try again later. For more visibility and control, go to Workspace settings → Job management (Job Concurrency & Queue Monitoring) to review running and queued Spark jobs, understand capacity contention, and take action as needed. [Learn more at 'https://go.microsoft.com/fwlink/?linkid=2356970&clcid=0x409'].

This is the CSV file, which is btw from Microsoft Learning Platform: https://raw.githubusercontent.com/MicrosoftLearning/dp-data/main/sales.csv

[timeseriesIQR]

Your first mudtake is trying to load a .csv datafile into Azure and access with Spark. WASTE of time. Just place your .csv datafile on ONEDRIVE and connect to it and query through PowerQuery. I can sell you a template for this. Azure is only for complex data with multiple tables. 

[v-nmadadi-msft]

Hi @TAnalytics 

May I check if this issue has been resolved? If not, Please feel free to contact us if you have any further questions.

Thank you

[v-nmadadi-msft]

Hi @TAnalytics 

I wanted to check if you had the opportunity to review the information provided. Please feel free to contact us if you have any further questions.

Thank you.

[v-nmadadi-msft]

Hi @TAnalytics   ,
Thanks for reaching out to the Microsoft Fabric Community forum. 

Please try the following troubleshooting steps:

• Check the Monitoring Hub for any active or queued Spark jobs. If there are jobs that are no longer needed, cancel them and retry the operation.
• Try restarting the Spark session (if one is active) or closing any open notebooks that may be consuming Spark resources.
• Wait 15–30 minutes and try again, as trial capacities can occasionally experience temporary resource contention or throttling.
• Create a new Lakehouse and attempt to load the same sample CSV there to determine whether the issue is specific to the Lakehouse or workspace.
• Verify that the workspace is correctly assigned to the Fabric trial capacity and that the trial is still active.
• Test with an alternative ingestion method, such as:
• Uploading the CSV directly to the Lakehouse Files section first and then creating a table from the file.
• Loading the file through a notebook using Spark.
• Try creating a new Fabric workspace attached to the trial capacity and repeat the test to rule out a workspace-specific issue.

I hope this information helps. Please do let us know if you have any further queries.
Thank you

[ati_puri]

HI @TAnalytics ,

This is a common problem in Fabric Trial as usually a Trial capacity is either F4 or F64 with very minimum number of cores.

ALso, job queuing is not supported for Spark jobs.

Workarounds:

1) Cancel any other active Spark jobs from Monitoring hub and retry csv load.

2) Wait for spark session timeout(~20mins by default)- you can reduce it from Spark settings.

3) Close all open notebooks and retry.

Let me know if any of the abobe solution works for you.

Thanks

Ati Puri

[deborshi_nag]

Hello @TAnalytics 

Fabric trial capacity is shared, so when there are no free cores, pipeline jobs are queued and interactive jobs may fail. That’s why you’re seeing the error message. You can check the Monitoring Hub and try loading the CSV file when activity is lower. Alternatively, you could use Dataflow Gen2 for CSV ingestion in a pipeline.