turbaszek commented on a change in pull request #18197:
URL: https://github.com/apache/airflow/pull/18197#discussion_r707056889
##########
File path: airflow/providers/google/cloud/operators/dataproc.py
##########
@@ -48,6 +54,83 @@
)
+class DataProcCreateWorkflowBaseOperator(BaseOperator):
+ """Helper class for preparing configs from workflow template"""
+
+ def __init__(self, **kwargs):
+ super().__init__(**kwargs)
+
+ def prepare_template(self) -> None:
+ try:
+ # if no file is specified, skip
+ if
isinstance(self.template["placement"]["managed_cluster"]["config"], str):
+ if
urlparse(self.template["placement"]["managed_cluster"]["config"]).scheme ==
"gs":
+ config = self._build_cluster_config(
+ self.template["placement"]["managed_cluster"]["config"]
+ )
+
+ # Dataproc workflows do not accept life cycle_config
+ if "lifecycle_config" in config:
+ self.log.warning(
+ "Workflow does not accept lifecycle in config,
removing it from config"
+ )
+ config.pop("lifecycle_config", None)
+ self.template["placement"]["managed_cluster"]["config"] =
config
+ else:
+ self.log.warning(
+ "Workflow Template config accepts only gcs path string
or dictioanry type, "
+ "skipping build cluster config from yml file"
+ )
+ except KeyError:
+ pass
Review comment:
Hm, I'm not sure if ignoring any `KeyError` is a good approach. Or do we
expect that the template will be wrong and the validation will happen on
Dataproc side?
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