Data Wrangler: Data Flow: Export to S3 using Jupyter Notebook

Question

When I have created a Data flow using data wrangler and when I am trying to Export to export to S3 using Jupyter Notebook and when I am running the notebook, I am getting the below mentioned error every time when creating a processing job:
 
Error:  An error occurred (ResourceLimitExceeded) when calling the CreateProcessingJob operation: The account-level service limit 'ml.m5.4xlarge for processing job usage' is 0 Instances, with current utilization of 0 Instances and a request delta of 2 Instances. Please contact AWS support to request an increase for this limit.
 
Please provide me with the solution for this. I have increased the service quota for running apps and Notebook instance also but then also same issue arises.

Answer

When you export a data flow to S3, you're starting a SageMaker processing job that will run the script and store data in S3.

So, increase your account limit for *Processing Job instances*, for the instance type ml.m5.4xlarge (instead of running apps/notebook instances).

Data Wrangler: Data Flow: Export to S3 using Jupyter Notebook

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