org.apache.flink.table.functions.python

Class PythonScalarFunction

java.lang.Object

org.apache.flink.table.functions.UserDefinedFunction

org.apache.flink.table.functions.ScalarFunction

org.apache.flink.table.functions.python.PythonScalarFunction

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

Constructor Summary

Constructors

Constructor and Description
PythonScalarFunction(String name, byte[] serializedScalarFunction, DataType[] inputTypes, DataType resultType, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)

Method Summary

Modifier and Type	Method and Description
Object	eval(Object... args)
TypeInformation[]	getParameterTypes(Class[] signature) Returns TypeInformation 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

Methods inherited from class org.apache.flink.table.functions.UserDefinedFunction

close, functionIdentifier, open

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.flink.table.functions.FunctionDefinition

getRequirements

Constructor Detail

PythonScalarFunction

public PythonScalarFunction(String name,
                            byte[] serializedScalarFunction,
                            DataType[] inputTypes,
                            DataType resultType,
                            PythonFunctionKind pythonFunctionKind,
                            boolean deterministic,
                            boolean takesRowAsInput,
                            PythonEnv pythonEnv)

Method Detail

eval

public Object eval(Object... args)

getSerializedPythonFunction

public byte[] getSerializedPythonFunction()

Description copied from interface: PythonFunction

Returns the serialized representation of the user-defined python function.

Specified by:

getSerializedPythonFunction in interface PythonFunction

getPythonEnv

public PythonEnv getPythonEnv()

Description copied from interface: PythonFunction

Returns the Python execution environment.

Specified by:

getPythonEnv in interface PythonFunction

getPythonFunctionKind

public PythonFunctionKind getPythonFunctionKind()

Description copied from interface: PythonFunction

Returns the kind of the user-defined python function.

Specified by:

getPythonFunctionKind in interface PythonFunction

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 interface PythonFunction

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 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.

Specified by:

isDeterministic in interface FunctionDefinition

getParameterTypes

public TypeInformation[] getParameterTypes(Class[] signature)

Description copied from class: ScalarFunction

Returns TypeInformation about the operands of the evaluation method with a given signature.

Overrides:

getParameterTypes in class ScalarFunction

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 class ScalarFunction

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 with DataTypeHint and FunctionHint 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, if DataTypes.TIMESTAMP(3).bridgedTo(java.sql.Timestamp.class) is an expected argument type, the method must accept a call eval(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 interface FunctionDefinition

Overrides:

getTypeInference in class ScalarFunction

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 class UserDefinedFunction