pankajkoti commented on code in PR #41700:
URL: https://github.com/apache/airflow/pull/41700#discussion_r1729209328
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tests/system/providers/databricks/example_databricks_workflow.py:
##########
@@ -32,34 +32,53 @@
EXECUTION_TIMEOUT = int(os.getenv("EXECUTION_TIMEOUT", 6))
-DATABRICKS_CONN_ID = os.getenv("DATABRICKS_CONN_ID", "databricks_conn")
+DATABRICKS_CONN_ID = os.getenv("DATABRICKS_CONN_ID", "databricks_default")
DATABRICKS_NOTIFICATION_EMAIL = os.getenv("DATABRICKS_NOTIFICATION_EMAIL",
"[email protected]")
GROUP_ID = os.getenv("DATABRICKS_GROUP_ID", "1234").replace(".", "_")
USER = os.environ.get("USER")
-QUERY_ID = os.environ.get("QUERY_ID", "c9cf6468-babe-41a6-abc3-10ac358c71ee")
-WAREHOUSE_ID = os.environ.get("WAREHOUSE_ID", "cf414a2206dfb397")
+QUERY_ID = os.environ.get("QUERY_ID", "d3773b5a-56f9-422c-ae60-048eaa90aa33")
+WAREHOUSE_ID = os.environ.get("WAREHOUSE_ID", "368fe30b92228713")
+
+
+## We can use below specs for AWS databricks
+# "job_cluster_key": "Shared_job_cluster",
+# "new_cluster": {
+# "cluster_name": "",
+# "spark_version": "11.3.x-scala2.12",
+# "aws_attributes": {
+# "first_on_demand": 1,
+# "availability": "SPOT_WITH_FALLBACK",
+# "zone_id": "us-east-2b",
+# "spot_bid_price_percent": 100,
+# "ebs_volume_count": 0,
+# },
+# "node_type_id": "i3.xlarge",
+# "spark_env_vars": {"PYSPARK_PYTHON":
"/databricks/python3/bin/python3"},
+# "enable_elastic_disk": False,
+# "data_security_mode": "LEGACY_SINGLE_USER_STANDARD",
+# "runtime_engine": "STANDARD",
+# "num_workers": 8,
Review Comment:
The current example DAG change shows job_cluster_spec for Databricks on
Azure.
The commented out piece is an alternative for the users who would like to
use Databricks on AWS. I modified the comment a bit.
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