Class PythonScalarFunction
- java.lang.Object
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- org.apache.flink.table.functions.UserDefinedFunction
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- org.apache.flink.table.functions.ScalarFunction
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- org.apache.flink.table.functions.python.PythonScalarFunction
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- All Implemented Interfaces:
Serializable
,FunctionDefinition
,PythonFunction
@Internal public class PythonScalarFunction extends ScalarFunction implements PythonFunction
The wrapper of user defined python scalar function.- See Also:
- Serialized Form
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Constructor Summary
Constructors Constructor Description PythonScalarFunction(String name, byte[] serializedScalarFunction, String[] inputTypesString, String resultTypeString, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)
PythonScalarFunction(String name, byte[] serializedScalarFunction, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)
PythonScalarFunction(String name, byte[] serializedScalarFunction, DataType[] inputTypes, DataType resultType, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description Object
eval(Object... args)
TypeInformation[]
getParameterTypes(Class[] signature)
ReturnsTypeInformation
about the operands of the evaluation method with a given signature.PythonEnv
getPythonEnv()
Returns the Python execution environment.PythonFunctionKind
getPythonFunctionKind()
Returns the kind of the user-defined python function.TypeInformation
getResultType(Class[] signature)
Returns the result type of the evaluation method with a given signature.byte[]
getSerializedPythonFunction()
Returns the serialized representation of the user-defined python function.TypeInference
getTypeInference(DataTypeFactory typeFactory)
Returns the logic for performing type inference of a call to this function definition.boolean
isDeterministic()
Returns information about the determinism of the function's results.boolean
takesRowAsInput()
Returns Whether the Python function takes row as input instead of each columns of a row.String
toString()
Returns the name of the UDF that is used for plan explanation and logging.-
Methods inherited from class org.apache.flink.table.functions.ScalarFunction
getKind
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Methods inherited from class org.apache.flink.table.functions.UserDefinedFunction
close, functionIdentifier, open
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
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Methods inherited from interface org.apache.flink.table.functions.FunctionDefinition
getRequirements, supportsConstantFolding
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Constructor Detail
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PythonScalarFunction
public PythonScalarFunction(String name, byte[] serializedScalarFunction, DataType[] inputTypes, DataType resultType, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)
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PythonScalarFunction
public PythonScalarFunction(String name, byte[] serializedScalarFunction, String[] inputTypesString, String resultTypeString, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)
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PythonScalarFunction
public PythonScalarFunction(String name, byte[] serializedScalarFunction, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)
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Method Detail
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getSerializedPythonFunction
public byte[] getSerializedPythonFunction()
Description copied from interface:PythonFunction
Returns the serialized representation of the user-defined python function.- Specified by:
getSerializedPythonFunction
in interfacePythonFunction
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getPythonEnv
public PythonEnv getPythonEnv()
Description copied from interface:PythonFunction
Returns the Python execution environment.- Specified by:
getPythonEnv
in interfacePythonFunction
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getPythonFunctionKind
public PythonFunctionKind getPythonFunctionKind()
Description copied from interface:PythonFunction
Returns the kind of the user-defined python function.- Specified by:
getPythonFunctionKind
in interfacePythonFunction
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takesRowAsInput
public boolean takesRowAsInput()
Description copied from interface:PythonFunction
Returns Whether the Python function takes row as input instead of each columns of a row.- Specified by:
takesRowAsInput
in interfacePythonFunction
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isDeterministic
public boolean isDeterministic()
Description copied from interface:FunctionDefinition
Returns information about the determinism of the function's results.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 likerandom(), date(), now(), ...
this method must returnfalse
.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.- Specified by:
isDeterministic
in interfaceFunctionDefinition
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getParameterTypes
public TypeInformation[] getParameterTypes(Class[] signature)
Description copied from class:ScalarFunction
ReturnsTypeInformation
about the operands of the evaluation method with a given signature.- Overrides:
getParameterTypes
in classScalarFunction
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getResultType
public TypeInformation getResultType(Class[] signature)
Description copied from class:ScalarFunction
Returns the result type of the evaluation method with a given signature.- Overrides:
getResultType
in classScalarFunction
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getTypeInference
public TypeInference getTypeInference(DataTypeFactory typeFactory)
Description copied from class:UserDefinedFunction
Returns the logic for performing type inference of a call to this function definition.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.The type inference for user-defined functions is automatically extracted using reflection. It does this by analyzing implementation methods such as
eval() or accumulate()
and the generic parameters of a function class if present. If the reflective information is not sufficient, it can be supported and enriched withDataTypeHint
andFunctionHint
annotations.Note: Overriding this method is only recommended for advanced users. If a custom type inference is specified, it is the responsibility of the implementer to make sure that the output of the type inference process matches with the implementation method:
The implementation method must comply with each
DataType.getConversionClass()
returned by the type inference. For example, ifDataTypes.TIMESTAMP(3).bridgedTo(java.sql.Timestamp.class)
is an expected argument type, the method must accept a calleval(java.sql.Timestamp)
.Regular Java calling semantics (including type widening and autoboxing) are applied when calling an implementation method which means that the signature can be
eval(java.lang.Object)
.The runtime will take care of converting the data to the data format specified by the
DataType.getConversionClass()
coming from the type inference logic.- Specified by:
getTypeInference
in interfaceFunctionDefinition
- Overrides:
getTypeInference
in classScalarFunction
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toString
public String toString()
Description copied from class:UserDefinedFunction
Returns the name of the UDF that is used for plan explanation and logging.- Overrides:
toString
in classUserDefinedFunction
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