blcksrx commented on code in PR #61528:
URL: https://github.com/apache/airflow/pull/61528#discussion_r2774453060
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providers/apache/spark/src/airflow/providers/apache/spark/hooks/spark_submit.py:
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@@ -265,10 +265,23 @@ def _resolve_connection(self) -> dict[str, Any]:
# Master can be local, yarn, spark://HOST:PORT, mesos://HOST:PORT
and
# k8s://https://<HOST>:<PORT>
conn = self.get_connection(self._conn_id)
- if conn.port:
- conn_data["master"] = f"{conn.host}:{conn.port}"
+
+ # connection comes from UI or it's a spark-master
+ if conn.conn_type == "spark":
+ if conn.host and ("://" in conn.host or not conn.port):
+ conn_data["master"] = conn.host
+ elif conn.port: # spark master/standalone has port
+ conn_data["master"] = f"spark://{conn.host or ''}"
else:
- conn_data["master"] = conn.host
+ if conn.conn_type != "yarn":
+ # For other conn_types (mesos, k8s, local, etc.):
reconstruct URL
+ conn_data["master"] = f"{conn.conn_type}://{conn.host or
''}"
+ else:
+ conn_data["master"] = conn.host
Review Comment:
I understand the complexity. but the complexity comes to answer this
question:
what `spark` in the connection means?
And it has two answer:
1. `spark` is a airflow`connection_type` such as `spark://local` or
`spark://yarn`
2. `spark` is refer to spark-master or stand-alone
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