T
- final result type of the aggregationACC
- intermediate result type during the aggregation@PublicEvolving public abstract class TableAggregateFunction<T,ACC> extends ImperativeAggregateFunction<T,ACC>
Similar to an AggregateFunction
, the behavior of a TableAggregateFunction
is
centered around the concept of an accumulator. The accumulator is an intermediate data structure
that stores the aggregated values until a final aggregation result is computed.
For each set of rows that needs to be aggregated, the runtime will create an empty accumulator
by calling ImperativeAggregateFunction.createAccumulator()
. Subsequently, the accumulate()
method of the
function is called for each input row to update the accumulator. Once all rows have been
processed, the emitValue()
or emitUpdateWithRetract()
method of the function is
called to compute and return the final result.
The main behavior of an TableAggregateFunction
can be defined by implementing a custom
accumulate method. An accumulate method must be declared publicly, not static, and named
accumulate
. Accumulate methods can also be overloaded by implementing multiple methods
named accumulate
.
By default, input, accumulator, and output data types are automatically extracted using
reflection. This includes the generic argument ACC
of the class for determining an
accumulator data type and the generic argument T
for determining an accumulator data
type. Input arguments are derived from one or more accumulate()
methods. If the
reflective information is not sufficient, it can be supported and enriched with DataTypeHint
and FunctionHint
annotations.
A TableAggregateFunction
needs at least three methods:
createAccumulator
accumulate
emitValue
or emitUpdateWithRetract
There are a few other methods that are optional:
retract
merge
All these methods must be declared publicly, not static, and named exactly as the names mentioned above to be called by generated code.
For storing a user-defined function in a catalog, the class must have a default constructor and must be instantiable during runtime. Anonymous functions in Table API can only be persisted if the function is not stateful (i.e. containing only transient and static fields).
Processes the input values and updates the provided accumulator instance. The method
accumulate can be overloaded with different custom types and arguments. A table aggregate function
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 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 method must be implemented for
bounded OVER aggregates over unbounded tables.
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 method must be
implemented for unbounded session and hop window grouping aggregates and
bounded 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: iterable an java.lang.Iterable pointed to a group of accumulators that will be
merged.
public void merge(ACC accumulator, java.lang.Iterable<ACC> iterable)
Called every time when an aggregation result should be materialized. The returned value could
be either an early and incomplete result (periodically emitted as data arrives) or the final
result of the aggregation.
param: accumulator the accumulator which contains the current aggregated results
param: out the collector used to output data.
public void emitValue(ACC accumulator, org.apache.flink.util.Collector<T> out)
Called every time when an aggregation result should be materialized. The returned value could
be either an early and incomplete result (periodically emitted as data arrives) or the final
result of the aggregation.
Compared to emitValue(), emitUpdateWithRetract() is used to emit values that have been updated. This method
outputs data incrementally in retraction mode (also known as "update before" and "update after"). Once
there is an update, we have to retract old records before sending new updated ones. The emitUpdateWithRetract()
method will be used in preference to the emitValue() method if both methods are defined in the table aggregate
function, because the method is treated to be more efficient than emitValue as it can output
values incrementally.
param: accumulator the accumulator which contains the current aggregated results
param: out the retractable collector used to output data. Use the collect() method
to output(add) records and use retract method to retract(delete)
records.
public void emitUpdateWithRetract(ACC accumulator, RetractableCollector<T> out)
If an accumulator needs to store large amounts of data, ListView
and MapView
provide advanced features for leveraging Flink's state backends in unbounded data scenarios.
Modifier and Type | Class and Description |
---|---|
static interface |
TableAggregateFunction.RetractableCollector<T>
Collects a record and forwards it.
|
Constructor and Description |
---|
TableAggregateFunction() |
Modifier and Type | Method and Description |
---|---|
FunctionKind |
getKind()
Returns the kind of function this definition describes.
|
TypeInference |
getTypeInference(DataTypeFactory typeFactory)
Returns the logic for performing type inference of a call to this function definition.
|
createAccumulator, getAccumulatorType, getResultType
close, functionIdentifier, open, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getRequirements, isDeterministic, supportsConstantFolding
public final FunctionKind getKind()
FunctionDefinition
public TypeInference getTypeInference(DataTypeFactory typeFactory)
UserDefinedFunction
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.
getTypeInference
in interface FunctionDefinition
getTypeInference
in class UserDefinedFunction
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