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