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!
Hi Ojicletus ,
I ran into a similar issue when trying to use Load to Table on a CSV file to load data into a Lakehouse table — I was getting the 430 error as well.
Here's an alternative approach that worked for me. Sharing it in case it helps you too:
Workaround Steps:
- Created a new Notebook in Microsoft Fabric.
- From the Data Items tab inside the notebook, added a new Lakehouse.
- Uploaded my CSV files directly to the Lakehouse.
- Started a New High Concurrency session instead of a New Standard session — the Standard session was triggering the same 430 error.
- Used PySpark to load the data into a table
df = spark.read.csv("Files/DimProducts.csv", header=True)
df.write.mode("overwrite").saveAsTable("DimProducts")
Do let me know if this works for you!
In the meantime, I'm also exploring the following and will update this thread if I find a resolution:
- How to get Load to Table working
- How to run successfully with a New Standard session
If this helped, ✓ Mark as Solution | 👍 Kudos appreciated
Ajitesh Churewal 🔗Connect with me on LinkedIn