Aggregate

Summary

The Aggregate class describes an aggregation feature that is applied to a Batch or Stream Feature View via features param.

Example

from tecton import Aggregate, batch_feature_view, TimeWindow
from tecton.types import Int64
from datetime import timedelta

@batch_feature_view(
    # ...
    features=[
        Aggregate(
            input_column=Field("my_column", Int64),
            function="mean",
            time_window=TimeWindow(window_size=timedelta(days=7)),
        ),
        Aggregate(
            input_column=Field("another_column", Int64),
            function="mean",
            time_window=TimeWindow(window_size=timedelta(days=1)),
            name="1d_average",
            description="my aggregate feature description",
            tags={"tag": "value"}
        ),
    ],
)
def my_fv(data_source):
    pass

For a list of available aggregation functions, see Aggregation Functions.

Methods

__init__(...)

Parameters

• description: Optional[str] = None A human-readable description of the feature
• tags: Optional[Dict[str, str]] = None Tags associated with the feature (key-value pairs of user-defined metadata).
• function: AggregationFunction = None One of the built-in aggregation functions, such as "sum", "count", last(2) etc.
• time_window: Union[TimeWindow, TimeWindowSeries, LifetimeWindow] = None The window_size and optional offset over which to aggregate over.
• name: Optional[str] = None The name of this feature. Defaults to an autogenerated name, e.g. transaction_count_7d_1d.
• input_column: Field = None Describes name and type of the column that will be used in the aggregation.