T- the type of the aggregation result
ACC- the type of the aggregation accumulator. The accumulator is used to keep the aggregated values which are needed to compute an aggregation result. AggregateFunction represents its state using accumulator, thereby the state of the AggregateFunction must be put into the accumulator.
@PublicEvolving public abstract class AggregateFunction<T,ACC> extends UserDefinedAggregateFunction<T,ACC>
There are a few other methods that can be optional to have:
All these methods must be declared publicly, not static, and named exactly as the names
mentioned above. The method
UserDefinedAggregateFunction.createAccumulator() is defined in the
UserDefinedAggregateFunction function, and method
getValue(ACC) is defined in the
AggregateFunction while other methods are explained below.
Processes the input values and update the provided accumulator instance. The method accumulate can be overloaded with different custom types and arguments. An AggregateFunction requires at least one accumulate() method. param: accumulator the accumulator which contains the current aggregated results param: [user defined inputs] the input value (usually obtained from a new arrived data). public void accumulate(ACC accumulator, [user defined inputs])
Retracts the input values from the accumulator instance. The current design assumes the inputs are the values that have been previously accumulated. The method retract can be overloaded with different custom types and arguments. This function must be implemented for data stream bounded OVER aggregates. param: accumulator the accumulator which contains the current aggregated results param: [user defined inputs] the input value (usually obtained from a new arrived data). public void retract(ACC accumulator, [user defined inputs])
Merges a group of accumulator instances into one accumulator instance. This function must be implemented for data stream session window grouping aggregates and data set grouping aggregates. param: accumulator the accumulator which will keep the merged aggregate results. It should be noted that the accumulator may contain the previous aggregated results. Therefore user should not replace or clean this instance in the custom merge method. param: its an java.lang.Iterable pointed to a group of accumulators that will be merged. public void merge(ACC accumulator, java.lang.Iterable<ACC> iterable)
Resets the accumulator for this AggregateFunction. This function must be implemented for data set grouping aggregates. param: accumulator the accumulator which needs to be reset public void resetAccumulator(ACC accumulator)
|Constructor and Description|
|Modifier and Type||Method and Description|
Returns the kind of function this definition describes.
Returns the set of requirements this definition demands.
Returns the logic for performing type inference of a call to this function definition.
Called every time when an aggregation result should be materialized.
createAccumulator, getAccumulatorType, getResultType
close, functionIdentifier, open, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
accumulator- the accumulator which contains the current aggregated results
@Deprecated public boolean requiresOver()
AggregateFunctioncan only be applied in an OVER window.
AggregateFunctionrequires an OVER window,
public final FunctionKind getKind()
public 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
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
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
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
Regular Java calling semantics (including type widening and autoboxing) are applied when
calling an implementation method which means that the signature can be
The runtime will take care of converting the data to the data format specified by the
DataType.getConversionClass() coming from the type inference logic.
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