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(
column="my_column",
column_dtype=Int64,
function="mean",
time_window=TimeWindow(window_size=timedelta(days=7)),
),
Aggregate(
column="another_column",
column_dtype=Int64,
function="mean",
time_window=TimeWindow(window_size=timedelta(days=1)),
name="1d_average",
),
],
)
def my_fv(data_source):
pass
Methods​
__init__(...)​
Parameters​
-
column
(str
) – The name of the input/feature column -
column_dtype
(SdkDataType
) - The data type of the column -
function
(Union[
str
,AggregationFunction]
) – One of the built-in aggregation functions. See the aggregation functions reference for a list of aggregation functions. -
time_window
(TimeWindow
) – The window_size and optional offset over which to aggregate over. See Time Window Reference for more details on the TimeWindow class. -
name
(Optional
[str
]) – The name of this feature, e.g.transaction_count_7d_1d
. Defaults to an autogenerated name.