spark version in dbx

[aneesha1122]

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Expected Behavior

We are using dbx to deploy and launch databricks jobs. Currently we are using 11.3 LTS runtime and now planning to migrate to 13.3 LTS. The runtime version is currently configured in deployment.yml in dbx for all jobs and also in cluster policy. For easy management, we would like to get rid of the spark version parameter from deployment.yml and get it enforced using the cluster policy. But, we are facing following errors.

Current Behavior

Scenario 1: YML Version = 11.X and Policy Version = 13.X . The job failed with the following error

{ 'error_code': 'INVALID_PARAMETER_VALUE', 'message': 'Cluster validation error: Validation failed for spark_version, ' 'must be 13.3.x-scala2.12 (is an element in ' '"List(11.3.x-aarch64-scala2.12, 11.3.x-scala2.12)")'}

Scenario 2: YML (Removed Spark Version Parameter ) and Policy Version = 13.x. The job failed with the following error.

ValidationError: 2 validation errors for Deployment workflows -> 0 -> Workflow -> job_clusters -> 0 -> new_cluster -> spark_version field required (type=value_error.missing) workflows -> 1 -> Workflow -> job_clusters -> 0 -> new_cluster -> spark_version field required (type=value_error.missing) ERROR during core_deployment workflow deployment (1)!

Context

We are using dbx to deploy and launch databricks jobs. Currently we are using 11.3 LTS runtime and now planning to migrate to 13.3 LTS. The runtime version is currently configured in deployment.yml in dbx for all jobs and also in cluster policy. For easy management, we would like to get rid of the spark version parameter from deployment.yml and get it enforced using the cluster policy. But, we are facing following errors.

• Databricks Runtime version: 11.3 LTS