@Internal public abstract class HiveScalarFunction<UDFType> extends ScalarFunction implements HiveFunction<UDFType>
UDF
and GenericUDF
functions.HiveFunction.HiveFunctionInputStrategy, HiveFunction.HiveFunctionOutputStrategy
Modifier and Type | Field and Description |
---|---|
protected HiveFunctionArguments |
arguments |
protected UDFType |
function |
protected HiveFunctionWrapper<UDFType> |
hiveFunctionWrapper |
protected org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector |
returnInspector |
Modifier and Type | Method and Description |
---|---|
Object |
eval(Object... args) |
protected abstract Object |
evalInternal(Object[] args)
Evaluation logical, args will be wrapped when is a single array.
|
HiveFunctionWrapper<UDFType> |
getFunctionWrapper()
Gets the wrapper for the Hive 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.
|
void |
open(FunctionContext context)
Setup method for user-defined function.
|
protected abstract void |
openInternal()
|
void |
setArguments(CallContext callContext)
Sets input arguments for the function.
|
getKind, getParameterTypes, getResultType
close, functionIdentifier, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
createTypeInference, inferReturnType
getRequirements, supportsConstantFolding
protected final HiveFunctionWrapper<UDFType> hiveFunctionWrapper
protected HiveFunctionArguments arguments
protected transient UDFType function
protected transient org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector returnInspector
public boolean isDeterministic()
FunctionDefinition
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.
isDeterministic
in interface FunctionDefinition
public void open(FunctionContext context)
UserDefinedFunction
open
in class UserDefinedFunction
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 ScalarFunction
protected abstract void openInternal()
protected abstract Object evalInternal(Object[] args)
public void setArguments(CallContext callContext)
HiveFunction
setArguments
in interface HiveFunction<UDFType>
public HiveFunctionWrapper<UDFType> getFunctionWrapper()
HiveFunction
getFunctionWrapper
in interface HiveFunction<UDFType>
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