featurebyte.UserDefinedFunction.create¶
create(
name: str,
sql_function_name: str,
function_parameters: List[FunctionParameter],
output_dtype: Literal["BOOL", "CHAR", "DATE", "FLOAT", "INT", "TIME", "TIMESTAMP", "TIMESTAMP_TZ", "VARCHAR", "ARRAY", "DICT", "TIMEDELTA", "EMBEDDING", "FLAT_DICT", "UNKNOWN", "BINARY", "VOID", "MAP", "OBJECT", "STRUCT"],
is_global: bool=False
) -> UserDefinedFunctionDescription¶
Create a user-defined function.
Parameters¶
- name: str
Name of the user-defined function. This will be used as the name of the dynamically created function. - sql_function_name: str
The SQL function name of the user-defined function (which is used in SQL queries). - function_parameters: List[FunctionParameter]
The function parameters of the user-defined function. - output_dtype: Literal["BOOL", "CHAR", "DATE", "FLOAT", "INT", "TIME", "TIMESTAMP", "TIMESTAMP_TZ", "VARCHAR", "ARRAY", "DICT", "TIMEDELTA", "EMBEDDING", "FLAT_DICT", "UNKNOWN", "BINARY", "VOID", "MAP", "OBJECT", "STRUCT"]
The output data type of the user-defined function. - is_global: bool
default: False
Whether the user-defined function is global across all catalogs or not. Global user-defined functions can be used in any catalogs (as long as the feature store is the same), while local user-defined functions can only be used in the catalog where they are created.
Returns¶
- UserDefinedFunction
The created user-defined function.
Examples¶
Create a local (catalog-specific) user-defined function that computes the cosine of a number:
>>> cos_udf = UserDefinedFunction.create(
... name="cos",
... sql_function_name="cos",
... function_parameters=[fb.FunctionParameter(name="x", dtype=fb.enum.DBVarType.FLOAT)],
... output_dtype=fb.enum.DBVarType.FLOAT,
... is_global=False,
... )
>>> view = catalog.get_view("GROCERYINVOICE")
>>> view["cos(Amount)"] = cos_udf(view["Amount"])
>>> view[["Amount", "cos(Amount)"]].preview(3)
GroceryInvoiceGuid Timestamp Amount cos(Amount)
0 4fccfb1d-02b3-4047-87ab-4e5f910ccdd1 2022-01-03 12:28:58 10.68 -0.310362
1 9cf3c416-7b38-401e-adf6-1bd26650d1d6 2022-01-03 16:32:15 38.04 0.942458
2 0a5b99b2-9ff1-452a-a06e-669e8ed4a9fa 2022-01-07 16:20:04 1.99 -0.407033
>>> feature = catalog.get_feature("InvoiceCount_60days")
>>> cos_feat = cos_udf(feature)
>>> cos_feat.name = "cos(InvoiceCount_60days)"
>>> fb.FeatureGroup([feature, cos_feat]).preview(
... observation_set=pd.DataFrame({
... "POINT_IN_TIME": ["2022-06-01 00:00:00"],
... "GROCERYCUSTOMERGUID": ["a2828c3b-036c-4e2e-9bd6-30c9ee9a20e3" ]
... })
... )
POINT_IN_TIME GROCERYCUSTOMERGUID InvoiceCount_60days cos(InvoiceCount_60days)
0 2022-06-01 a2828c3b-036c-4e2e-9bd6-30c9ee9a20e3 10.0 -0.839072
The user-defined function can also be accessed via the UDF handle (the name of the UserDefinedFunction
object is used to access the corresponding function):