@PublicEvolving public interface FunctionDefinition
A pure function definition doesn't have to contain a runtime implementation. This can be
provided by the planner at later stages. A UserDefinedFunction
is a function definition
that includes a runtime implementation already.
UserDefinedFunction
Modifier and Type | Method and Description |
---|---|
FunctionKind |
getKind()
Returns the kind of function this definition describes.
|
default Set<FunctionRequirement> |
getRequirements()
Returns the set of requirements this definition demands.
|
TypeInference |
getTypeInference(DataTypeFactory typeFactory)
Returns the logic for performing type inference of a call to this function definition.
|
default boolean |
isDeterministic()
Returns information about the determinism of the function's results.
|
FunctionKind getKind()
TypeInference getTypeInference(DataTypeFactory typeFactory)
The type inference process is responsible for inferring unknown types of input arguments, validating input arguments, and producing result types. The type inference process happens independent of a function body. The output of the type inference is used to search for a corresponding runtime implementation.
Instances of type inference can be created by using TypeInference.newBuilder()
.
See BuiltInFunctionDefinitions
for concrete usage examples.
default Set<FunctionRequirement> getRequirements()
default boolean isDeterministic()
It returns true
if and only if a call to this function is guaranteed to
always return the same result given the same parameters. true
is assumed by
default. If the function is not purely functional like random(), date(), now(), ...
this method must return false
.
Furthermore, return false
if the planner should always execute this function
on the cluster side. In other words: the planner should not perform constant expression
reduction during planning for constant calls to this function.
Copyright © 2014–2024 The Apache Software Foundation. All rights reserved.