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I am looking at running spark batch jobs on azure synapse. I am currently able to test the runs by using az cli for synapse. On the production, I need to trigger these spark submissions via external application (prefect flows).

To submit the spark job, I am looking at using azure synapse sdk (https://learn.microsoft.com/en-us/python/api/azure-mgmt-synapse/azure.mgmt.synapse.synapsemanagementclient?view=azure-python) with

How do I pass the TokenCredential as mentioned here https://learn.microsoft.com/en-us/python/api/azure-mgmt-synapse/azure.mgmt.synapse.synapsemanagementclient?view=azure-python#constructor

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This was rather straightforward and I had overlooked the documentation.

The short code is below

from azure.identity import ClientSecretCredential from azure.synapse.spark import SparkClient from azure.synapse.spark.models import SparkBatchJobOptions def run(self, job_name: str, job_args): credential = ClientSecretCredential(self.tenant_id, self.client_id,self.client_secret) options = SparkBatchJobOptions.from_dict({ "tags": None, "artifactId": None, "name": f"{job_name}", "file": f"{job_name}.py", "className": None, "args": job_args, "jars": [], "files": [], "archives": [], "conf": None, "driverMemory": "4g", "driverCores": 4, "executorMemory": "2g", "executorCores": 2, "numExecutors": 2, } }) job = spark_client.spark_batch.create_spark_batch_job(options, detailed=False)
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