Forum Discussion
Your Compute session is disconnected
Hi Ojicletus ,
This error means your Fabric capacity has reached the concurrent Spark jobs limit. This is a SKU/capacity-level throttling issue, not necessarily a problem with your code.
Learn more here: https://learn.microsoft.com/fabric/data-engineering/spark-job-concurrency-and-queueing
I would recommend reviewing the following:
1. Review and cancel active jobs
Go to Workspace Settings → Data Engineering/Science → Spark settings → Jobs and cancel any non-critical Spark jobs.
There are often "zombie" notebook sessions consuming Spark slots without doing anything useful.
https://learn.microsoft.com/fabric/data-engineering/job-concurrency-queue-monitoring
2. Activate High Concurrency (if applicable)
This can help improve Spark session utilization and reduce concurrency-related issues.
3. Review Spark compute configuration
In fact, I ran into the same error today and immediately thought of you.
In my case, I adjusted the Spark configuration. I had a Medium node running on an F4 capacity, and I changed it to Small, also adjusting the number of nodes. That resolved the issue for me.
Give it a try and let us know if it works for you: https://learn.microsoft.com/en-us/fabric/data-engineering/environment-manage-compute
Additional references that may help:
https://learn.microsoft.com/fabric/data-engineering/job-queueing-for-fabric-spark
https://learn.microsoft.com/fabric/data-engineering/autoscale-billing-for-spark-overview
https://learn.microsoft.com/fabric/data-engineering/troubleshoot-permissions-capacity#capacity-and-r...
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Thank you!
Hello Ojicletus,
This looks like a Spark capacity issue rather than a dataset issue.
The TooManyRequestsForCapacity (HTTP 430) error means Fabric Spark compute is unavailable or a Spark/API rate limit has been hit.
Since you're using the trial version, try these quick checks:
1. Go to Monitoring hub and cancel any running or queued Spark jobs.
2. Check Workspace settings → Job management for queued jobs or capacity contention.
3. Disconnect the current compute session, reconnect it, then rerun the job after a short wait.
Docs:
Concurrency limits and queueing in Apache Spark for Microsoft Fabric
This error is typically related to Fabric Spark capacity limits rather than the dataset itself. Try cancelling any running or queued Spark jobs, reconnecting your Spark session, and rerunning the job after a few minutes. If it continues, check the Spark session logs for additional details that could point to capacity contention or a specific job issue.