Exceeding vcore quota

Question

I've recently moved a pipeline to a new Synapse Analytics workspace in my Enterprise. I did this to troubleshoot other issues, but now I'm getting this error on the ForEach activity of one of my pipelines:
{
"errorCode": "3250",
"message": "There is not enough resource available in the workspace, details: 'Your job requested 32 vcores. However, the workspace only has 18 vcores available out of quota of 50 vcores. Try ending the running job(s), reducing the numbers of vcores requested or increasing your vcore quota.'",
"failureType": "UserError",
"target": "FhirExportToParquetDataflow",
"details": []
}

I've read previous answers on here and the solution is always to request more vcores. But I have 4 vms in my Spark pool with Large node size. 16vcores/128GB. 10 to 200 nodes. Autoscale enabled. The error suggests ending running jobs, but there is only one Active job on my pool (the one running this pipeline). I don't understand why I need to request more vcores. How can I see, for sure, what/who is using the Spark pool? The other Synapse Workspace I transfered from has Small node size. 2 to 200 nodes. Autoscale enabled. So it would seem that if it run there it would run in the new one too.

If that is the only solution which Family of vCPUs do I need request the quota increase for? There are half a dozen in Usage sorted Quota screen.

BTW this is for Debug runs.

Answer 1

Hello @TerriblyVexed ,

Thanks for the question and using MS Q&A platform.

You can monitor the usage of the Apache Spark pools by selecting => Monitor => Under Analytics Pools => Select Apache Spark pools => Here you can see the complete pool details along with (Active Users, Allocated vCores, Allocated Memory and created on).

You can select the Apache Spark pool to get more details on the Active applications and running application, Current allocation & History of the vCore allocation along with user details.

This article explains how to monitor your Apache Spark pools, allowing you to keep an eye on the status of your pools, including how many vCores are in use by different workspace users.

Every Azure Synapse workspace comes with a default quota of vCores that can be used for Spark. The quota is split between the user quota and the dataflow quota so that neither usage pattern uses up all the vCores in the workspace. The quota is different depending on the type of your subscription but is symmetrical between user and dataflow. However if you request more vCores than are remaining in the workspace, then you will get the following error:

To resolve this issue, you need to request a capacity increase via the Azure portal by creating a new support ticket.

Step1: Create a new support ticket and select issue type as Service and subscription limits (quotas) and quota type as Azure Synapse Analytics.

Step2: In the Details tab, click on Enter details and choose quota type as Apache Spark (vCore) per workspace , select workspace, and request quota as shown below.

Step3: Select support method and create the ticket.

For more details, refer to Apache Spark in Azure Synapse Analytics Core Concepts.

Hope this will help. Please let us know if any further queries.

------------------------------

• Please don't forget to click on or upvote button whenever the information provided helps you. Original posters help the community find answers faster by identifying the correct answer. Here is how
• Want a reminder to come back and check responses? Here is how to subscribe to a notification
• If you are interested in joining the VM program and help shape the future of Q&A: Here is how you can be part of Q&A Volunteer Moderators

Answer 2

I have exactly the same issue, but I have requested and received a new core limit of 500 vCores as the guide here suggested. The (seemingly random) error I still get when I run dataflows (everything is sequential, nothing in parallel) is:

Operation on target source-bronze-CDC failed: There are not enough resources available in the workspace, details: 'Your job requested 48 vcores. However, the workspace only has 42 vcores available out of quota of 50 vcores for node size family [MemoryOptimized]. Try ending the running job(s), reducing the numbers of vcores requested or increasing your vcore quota.

This confuses me, as it mentions 50 vcores available while I expected this to be 500, and why is it mentioning MemoryOptimized when I configured the runtime to Basic Purpose? Am I mixing up concepts here, or should I have requested a different quota?

Please elaborate on this as the workspace is not stable enough as it is now.