topic How to check programmatically job cluster is unity catalog enabled or not in databricks in Data Engineering

How to check programmatically job cluster is unity catalog enabled or not in databricks

shreyassharmabh — Wed, 05 Jul 2023 07:17:03 GMT

Is there any way to check job cluster is unity catalog enabled or not in databricks using python.

I tried with jobs api https://{host_name}/api/2.0/jobs/get?job_id={job_id}, but I didn't that cluster is unity catalog enabled or not.

Could anyone suggest how to get that programmatically, it would be great help.

Re: How to check programmatically job cluster is unity catalog enabled or not in databricks

Sallyroque — Wed, 05 Jul 2023 08:57:29 GMT

@shreyassharmabh wrote:
Is there any way to check job cluster is unity catalog enabled or not in databricks using python.
I tried with jobs api https://{host_name}/api/2.0/jobs/get?job_id={job_id}, but I didn't that cluster is unity catalog enabled or not.
Could anyone suggest how to get that programmatically, it would be great help.

Hello,

To check if a job cluster is Unity Catalog enabled in Databricks programmatically using Python, you can make use of the Databricks REST API. The steps to achieve this are as follows:

Obtain an access token: You'll need an access token to authenticate your API requests. You can generate a token by following the instructions provided in the Databricks documentation: Generate a Personal Access Token.

Make an API request: Once you have the access token, you can use Python's requests library to make an HTTP GET request to the Databricks REST API. The API endpoint you need to call is /api/2.0/clusters/get, and you'll pass the cluster_id parameter to specify the cluster you want to check. The response will contain information about the cluster, including whether Unity Catalog is enabled.

Here's an example Python code snippet that demonstrates this process:

import requests

# Set up API request details
api_url = 'https://{your_databricks_host}/api/2.0/clusters/get'
headers = {'Authorization': 'Bearer <your_access_token>'}
params = {'cluster_id': '<your_cluster_id>'}

# Make the API request
response = requests.get(api_url, headers=headers, params=params)
data = response.json()

# Check if Unity Catalog is enabled
if 'catalog_is_unified' in data['cluster']:
is_unity_catalog_enabled = data['cluster']['catalog_is_unified']
print(f"Unity Catalog enabled: {is_unity_catalog_enabled}")
else:
print("Unity Catalog status not available for the cluster.")

Make sure to replace <your_databricks_host>, <your_access_token>, and <your_cluster_id> with the appropriate values for your Databricks environment.

Re: How to check programmatically job cluster is unity catalog enabled or not in databricks

KarenZak — Wed, 05 Jul 2023 10:46:39 GMT

To check if a job cluster is Unity catalog enabled in Databricks programmatically using Python, you can use the Databricks REST API. Here's an example of how you can do it:

Import the required modules:

import requests

Set up the necessary variables:
host_name = "<your_databricks_host_name>"
job_id = "<your_job_id>"
token = "<your_databricks_personal_access_token>"
Send a GET request to the Jobs API to retrieve the job details:
url = f"https://{host_name}/api/2.0/jobs/get?job_id={job_id}"
headers = {"Authorization": f"Bearer {token}"}
response = requests.get(url, headers=headers)
job_details = response.json()
Extract the cluster ID from the job details:
cluster_id = job_details["settings"]["existing_cluster_id"]
Send another GET request to the Clusters API to retrieve the cluster details:
url = f"https://{host_name}/api/2.0/clusters/get?cluster_id={cluster_id}"
response = requests.get(url, headers=headers)
cluster_details = response.json()
Check if Unity catalog is enabled for the cluster:
unity_catalog_enabled = cluster_details["cluster_source"]["unity_catalog_enabled"]
Print the result:
if unity_catalog_enabled:
print("Unity catalog is enabled for the job cluster.")
else:
print("Unity catalog is not enabled for the job cluster.")

Make sure to replace <your_databricks_host_name>, <your_job_id>, and <your_databricks_personal_access_token> with your actual values.

Please note that you need the appropriate permissions and a valid personal access token to access the Databricks REST API.