teradataml.store.feature_store.models.FeatureGroup.ingest_features = ingest_features(self, repo, data_domain=None)

DESCRIPTION:
    Ingests the features from feature group. Method considers associated DataSource 
    as data source for feature process and ingests the feature values in feature catalog.
 
PARAMETERS:
    repo:
        Required Argument.
        Specifies the name of the repository to ingest the features.
        Types: str.
 
    data_domain:
        Optional Argument.
        Specifies the name of the data domain to ingest the features for.
        Note:
            * If not specified, then default database name is considered as data domain.
        Types: str.
 
RETURNS:
    Object of FeatureProcess.
 
RAISES:
    TeradataMlException
 
EXAMPLES:
    >>> load_example_data('dataframe', ['sales'])
    >>> df = DataFrame("sales")
 
    >>> from teradataml import FeatureStore
    >>> fs = FeatureStore("vfs_test", data_domain='sales')
    Repo vfs_v1 does not exist. Run FeatureStore.setup() to create the repo and setup FeatureStore.
    >>> fs.setup()
    True
 
    # Example 1: create a FeatureGroup 'sales_data_fg' for above mentioned
    #            DataFrame and publish it to 'vfs_v1'.
    # First create the features.
    >>> jan_feature = Feature("sales:Jan", df.Jan)
    >>> feb_feature = Feature("sales:Fan", df.Feb)
    >>> mar_feature = Feature("sales:Mar", df.Mar)
    >>> apr_feature = Feature("sales:Apr", df.Apr)
 
    >>> # Create Entity.
    >>> entity = Entity("sales:accounts", df.accounts)
    
    # Create DataSource.
    >>> data_source = DataSource("sales_source", df.show_query())
    
    # Create FeatureGroup.
    >>> fg = FeatureGroup('Sales',
    ...                   features=[jan_feature, feb_feature, mar_feature, apr_feature],
    ...                   entity=entity,
    ...                   data_source=data_source)
 
    # Ingest the features.
    >>> fp = fg.ingest_features()
    Process 'e04fd157-6c23-11f0-8bd4-f020ffe7fe09' started.
    Process 'e04fd157-6c23-11f0-8bd4-f020ffe7fe09' completed.
    >>> fp
    FeatureProcess(repo=vfs_v1, data_domain=sales, process_id=e04fd157-6c23-11f0-8bd4-f020ffe7fe09)