Single Node Jobs creation leads to Missing required field: settings.cluster_spec.new_cluster.size Databricks CLI 0.200.2

[zyeiy2]

Setup

1. Creating a Simple Job via Databricks UI and exporting the Job definition Json
2. Create the job via Databricks CLI with the previous Job definition Json

Description
Azure Databricks CLI logged several events related to a process involving the creation of a job on Databricks. The Azure Databricks CLI on Linux version used was 0.200.2.

The DEFAULT profile from "/root/.databrickscfg" was used for authentication and correct configured because the other operations work well. In the .databrickscfg API Verison 2.1 and 2.0 were already tested and lead to the same result.

However, the job creation failed due to a missing required field in the cluster specification: "settings.cluster_spec.new_cluster.size." As a result, the CLI returned an error with the code "INVALID_PARAMETER_VALUE" and the message "Cluster validation error: Missing required field: settings.cluster_spec.new_cluster.size."

Running this command lead to the error above:
databricks jobs create --json @b.json

Find the content of the b.json file below.

{
    "run_as": {
        "user_name": "u.name@company.de"
    },
    "name": "UC Test",
    "email_notifications": {
        "no_alert_for_skipped_runs": false
    },
    "webhook_notifications": {},
    "timeout_seconds": 0,
    "max_concurrent_runs": 1,
    "tasks": [
        {
            "task_key": "Task",
            "notebook_task": {
                "notebook_path": "/Shared/z-job/NB_Start_Job",
                "source": "WORKSPACE"
            },
            "job_cluster_key": "Job_cluster",
            "timeout_seconds": 0,
            "email_notifications": {}
        }
    ],
    "job_clusters": [
        {
            "job_cluster_key": "Job_cluster",
            "new_cluster": {
                "spark_version": "12.2.x-scala2.12",
                "spark_conf": {
                    "spark.databricks.delta.preview.enabled": "true",
                    "spark.master": "local[*, 4]",
                    "spark.databricks.cluster.profile": "singleNode"
                },
                "azure_attributes": {
                    "first_on_demand": 1,
                    "availability": "ON_DEMAND_AZURE",
                    "spot_bid_max_price": -1
                },
                "node_type_id": "Standard_DS3_v2",
                "custom_tags": {
                    "ResourceClass": "SingleNode"
                },
                "spark_env_vars": {
                    "PYSPARK_PYTHON": "/databricks/python3/bin/python3"
                },
                "enable_elastic_disk": true,
                "data_security_mode": "SINGLE_USER",
                "runtime_engine": "STANDARD",
                "num_workers": 0
            }
        }
    ],
    "format": "MULTI_TASK"
}

The log of the command executed can be found here

And leads also to the error:
time=2023-08-01T07:52:58.409+02:00 level=ERROR source=root.go:96 msg="failed execution" exit_code=1 error="Cluster validation error: Missing required field: settings.cluster_spec.new_cluster.size"

[alexott]

Please report it to https://github.com/databricks/cli

[zyeiy2]

Please report it to https://github.com/databricks/cli

Hey @alexott thank you for the hint. It was hard to determine what was the right place to post.

Issue is already known, Failed to create a job with single-node cluster

[dvinesett]

I have a workaround until the fix arrives. Cross posting it in this old CLI repo since the issue is still open. I experienced the issue with reset rather than create, but it seems that the bug is shared. You can opt to hit the databricks api command group instead of databricks jobs. As an example:

Not working:

$ databricks jobs reset --json @example.json
Error: Cluster validation error: Missing required field: settings.cluster_spec.new_cluster.size

Working:

$ databricks api post /api/2.1/jobs/reset --json @example.json
{}

This was done in Databricks CLI v0.205.0.

[kucm-pg]

Thanks @dvinesett for sharing the workaround. Works like a charm, even though it complicates my CD pipeline.
It's saddening to see that this issue got no traction with Databrick's dev team.

[dvinesett]

Hey @kucm-pg, this issue was posted to the Legacy Databricks CLI and likely won't be fixed here. However, it was fixed in the newer, separate version of the Databricks CLI. You'll need to migrate to that version to receive the update. That is, installing the CLI from the instructions here rather than the old way using pip.

[kucm-pg]

Hey @dvinesett thanks for sharing! This issue can be closed, I guess.