Package org.apache.flink.table.functions.python

Class PythonTableAggregateFunction

java.lang.Object
org.apache.flink.table.functions.UserDefinedFunction
org.apache.flink.table.functions.ImperativeAggregateFunction<T,ACC>
org.apache.flink.table.functions.TableAggregateFunction
org.apache.flink.table.functions.python.PythonTableAggregateFunction
All Implemented Interfaces:
Serializable, FunctionDefinition, PythonFunction
@Internal public class PythonTableAggregateFunction extends TableAggregateFunction implements PythonFunction
The wrapper of user defined python table aggregate function.
See Also:

  • Constructor Details

    • PythonTableAggregateFunction

      public PythonTableAggregateFunction(String name, byte[] serializedTableAggregateFunction, DataType[] inputTypes, DataType resultType, DataType accumulatorType, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)

    • PythonTableAggregateFunction

      public PythonTableAggregateFunction(String name, byte[] serializedTableAggregateFunction, String[] inputTypesString, String resultTypeString, String accumulatorTypeString, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)

    • PythonTableAggregateFunction

      public PythonTableAggregateFunction(String name, byte[] serializedTableAggregateFunction, PythonFunctionKind pythonFunctionKind, boolean deterministic, boolean takesRowAsInput, PythonEnv pythonEnv)

  • Method Details

    • accumulate

      public void accumulate(Object accumulator, Object... args)

    • emitValue

      public void emitValue(Object accumulator, Object out)

    • createAccumulator

      public Object createAccumulator()
      Description copied from class: ImperativeAggregateFunction
      Creates and initializes the accumulator for this ImperativeAggregateFunction.

      The accumulator is an intermediate data structure that stores the aggregated values until a final aggregation result is computed.

      Specified by:
      createAccumulator in class ImperativeAggregateFunction
      Returns:
      the accumulator with the initial value

    • 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

    • getResultType

      public org.apache.flink.api.common.typeinfo.TypeInformation getResultType()
      Description copied from class: ImperativeAggregateFunction
      Returns the TypeInformation of the ImperativeAggregateFunction's result.
      Overrides:
      getResultType in class ImperativeAggregateFunction
      Returns:
      The TypeInformation of the ImperativeAggregateFunction's result or null if the result type should be automatically inferred.

    • getAccumulatorType

      public org.apache.flink.api.common.typeinfo.TypeInformation getAccumulatorType()
      Description copied from class: ImperativeAggregateFunction
      Returns the TypeInformation of the ImperativeAggregateFunction's accumulator.
      Overrides:
      getAccumulatorType in class ImperativeAggregateFunction
      Returns:
      The TypeInformation of the ImperativeAggregateFunction's accumulator or null if the accumulator type should be automatically inferred.

    • 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 TableAggregateFunction

    • 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