google_cloud_pipeline_components.experimental.forecasting package¶
Google Cloud Pipeline Experimental Forecasting Components.
- google_cloud_pipeline_components.experimental.forecasting.ForecastingPreprocessingOp(project: str, input_tables: str, preprocessing_bigquery_dataset: str = '')¶
Preprocesses BigQuery tables for training or prediction.
Creates a BigQuery table for training or prediction based on the input tables. For training, a primary table is required. Optionally, you can include some attribute tables. For prediction, you need to include all the tables that were used in the training, plus a plan table.
- Args:
project (str): The GCP project id that runs the pipeline. input_tables (str): Serialized Json array that specifies input BigQuery tables and specs. preprocessing_bigquery_dataset (str): Optional BigQuery dataset to save the preprocessing result BigQuery table. If not present, a new dataset will be created by the component.
- Returns:
None
- google_cloud_pipeline_components.experimental.forecasting.ForecastingValidationOp(input_tables: str, validation_theme: str)¶
Validates BigQuery tables for training or prediction.
Validates BigQuery tables for training or prediction based on predefined requirements. For training, a primary table is required. Optionally, you can include some attribute tables. For prediction, you need to include all the tables that were used in the training, plus a plan table.
- Args:
input_tables (str): Serialized Json array that specifies input BigQuery tables and specs. validation_theme (str): Theme to use for validating the BigQuery tables. Acceptable values are FORECASTING_TRAINING and FORECASTING_PREDICTION.
- Returns:
None