Forum Discussion
Error message on notebook sql
Hi Krishsaba ,
This error means your Fabric capacity has hit the concurrent Spark jobs limit. It's a SKU-level throttling issue, not a problem with your code.
Learn : https://learn.microsoft.com/fabric/data-engineering/spark-job-concurrency-and-queueing
I see this:
Activate high concurrency: https://learn.microsoft.com/es-es/fabric/data-engineering/configure-high-concurrency-session-notebooks-in-pipelines#configure-high-concurrency-mode
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 slots without doing anything useful. https://learn.microsoft.com/fabric/data-engineering/job-concurrency-queue-monitoring
2. Wait and retry
If the load is temporary (end of day, scheduled pipelines firing at the same time), waiting a few minutes and retrying is usually enough. The timestamp is 20:00h, which may coincide with scheduled workloads.
3. Check the Monitor Hub
Filter by "Running" status and check how many Spark jobs are active simultaneously. You can also see if there's contention from other workspaces on the same capacity (noisy neighbor scenario).
More:
https://learn.microsoft.com/fabric/data-engineering/job-queueing-for-fabric-spark .
https://learn.microsoft.com/fabric/data-engineering/autoscale-billing-for-spark-overview
If this response has been helpful, please don't forget to give it a Like and mark it as a Solution so other community members can find it easily.
Thank you!
Hi Krishsaba ,
This error means your Fabric capacity has hit the concurrent Spark jobs limit. It's a SKU-level throttling issue, not a problem with your code.
Learn : https://learn.microsoft.com/fabric/data-engineering/spark-job-concurrency-and-queueing
I see this:
Activate high concurrency: https://learn.microsoft.com/es-es/fabric/data-engineering/configure-high-concurrency-session-notebooks-in-pipelines#configure-high-concurrency-mode
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 slots without doing anything useful. https://learn.microsoft.com/fabric/data-engineering/job-concurrency-queue-monitoring
2. Wait and retry
If the load is temporary (end of day, scheduled pipelines firing at the same time), waiting a few minutes and retrying is usually enough. The timestamp is 20:00h, which may coincide with scheduled workloads.
3. Check the Monitor Hub
Filter by "Running" status and check how many Spark jobs are active simultaneously. You can also see if there's contention from other workspaces on the same capacity (noisy neighbor scenario).
More:
https://learn.microsoft.com/fabric/data-engineering/job-queueing-for-fabric-spark .
https://learn.microsoft.com/fabric/data-engineering/autoscale-billing-for-spark-overview
If this response has been helpful, please don't forget to give it a Like and mark it as a Solution so other community members can find it easily.
Thank you!