Init MLflow support #2
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| def _generate_mlflow_root_task_sql(self): | ||
| return """ |
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Re-use self.TASK_TEMPLATE?
| sql_statements = [self._generate_root_task_sql()] | ||
| sql_statements = [ | ||
| self._generate_root_task_sql(), | ||
| self._generate_root_task_suspend_sql(), |
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Should be immediately execute suspend after execute? Will it work?
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Why not ? For a brand new pipeline it is always suspended - so does not take any effect - for a replaced one it should just change the state ?
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Or maybe it would make sense to always drop a whole pipeline and then recreate it from scratch - it would then fix #3 ?
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Could be, let's discuss it.
For the suspend vs execute - wouldn't the pipeline stop executing, because of the "suspend"?
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| ## Deployment to Snowflake and inference | ||
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| ### Deployment | ||
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Maybe just add link to https://github.com/Snowflake-Labs/mlflow-snowflake ?
| log_parameter(k, v) | ||
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| def log_model(model: RandomForestRegressor, X_train: pd.DataFrame, y_train: pd.Series): |
... cookiecutter.repo_name }}/src/{{ cookiecutter.python_package }}/pipelines/mlflow_helpers.py
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