- java.lang.Object
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- com.pervasive.datarush.operators.AbstractLogicalOperator
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- com.pervasive.datarush.operators.StreamingOperator
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- com.pervasive.datarush.operators.ExecutableOperator
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- com.pervasive.datarush.operators.record.RemapFields
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- All Implemented Interfaces:
LogicalOperator
,PipelineOperator<RecordPort>
,RecordPipelineOperator
public class RemapFields extends ExecutableOperator implements RecordPipelineOperator
Rearranges and renames fields in a record. Two options are provided for handling source fields not specifically referenced in the field renaming:- Unmapped fields are removed from the result. This achieves
the same effect as combining the renaming operation with
SelectFields
. - Unmapped fields are kept in the result, with the names of the fields remaining the same as in the source. For example, if the source schema is [A,B,C] and the mapping is {B -> Z}, the resulting schema will be [A,Z,C].
- See Also:
SelectFields
,RetainFields
,RemoveFields
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Constructor Summary
Constructors Constructor Description RemapFields()
Maps all fields in the input to the same fields in the output.RemapFields(FieldRemapping remapping)
Maps fields in the input to fields in the output using the specified mapping.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description protected ExecutableOperator
cloneForExecution()
Performs a deep copy of the operator for execution.protected void
computeMetadata(StreamingMetadataContext ctx)
Implementations must adhere to the following contractsprotected void
execute(ExecutionContext ctx)
Executes the operator.FieldRemapping
getFieldRemapping()
Gets how input fields are mapped to output fields,RecordPort
getInput()
Returns the input portRecordPort
getOutput()
Returns the output portvoid
setFieldRemapping(FieldRemapping remapping)
Defines how input fields are to be mapped to output fields.-
Methods inherited from class com.pervasive.datarush.operators.ExecutableOperator
getNumInputCopies, getPortSettings, handleInactiveOutput
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Methods inherited from class com.pervasive.datarush.operators.AbstractLogicalOperator
disableParallelism, getInputPorts, getOutputPorts, newInput, newInput, newOutput, newRecordInput, newRecordInput, newRecordOutput, notifyError
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface com.pervasive.datarush.operators.LogicalOperator
disableParallelism, getInputPorts, getOutputPorts
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Constructor Detail
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RemapFields
public RemapFields()
Maps all fields in the input to the same fields in the output. This effectively copies records from the input to the output. UsesetFieldRemapping(FieldRemapping)
to define a mapping to apply.
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RemapFields
public RemapFields(FieldRemapping remapping)
Maps fields in the input to fields in the output using the specified mapping.- Parameters:
remapping
- a mapping defining how input fields are mapped to output fields
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Method Detail
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getInput
public RecordPort getInput()
Description copied from interface:PipelineOperator
Returns the input port- Specified by:
getInput
in interfacePipelineOperator<RecordPort>
- Returns:
- the input port
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getOutput
public RecordPort getOutput()
Description copied from interface:PipelineOperator
Returns the output port- Specified by:
getOutput
in interfacePipelineOperator<RecordPort>
- Returns:
- the output port
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getFieldRemapping
public FieldRemapping getFieldRemapping()
Gets how input fields are mapped to output fields,- Returns:
- the mapping of source fields to target fields
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setFieldRemapping
public void setFieldRemapping(FieldRemapping remapping)
Defines how input fields are to be mapped to output fields.- Parameters:
remapping
- a mapping defining how input fields are mapped to output fields
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computeMetadata
protected void computeMetadata(StreamingMetadataContext ctx)
Description copied from class:StreamingOperator
Implementations must adhere to the following contractsGeneral
Regardless of input ports/output port types, all implementations must do the following:- Validation. Validation of configuration should always be performed first.
- Declare parallelizability.. Implementations must declare parallelizability by calling
StreamingMetadataContext.parallelize(ParallelismStrategy)
.
Input record ports
Implementations with input record ports must declare the following:- Required data ordering: Implementations that have data ordering requirements must declare them by calling
- Required data distribution (only applies to parallelizable operators): Implementations that have data distribution requirements must declare them by calling
RecordPort#setRequiredDataOrdering
, otherwise data may arrive in any order.RecordPort#setRequiredDataDistribution
, otherwise data will arrive in anunspecified partial distribution
.RecordPort#getSourceDataDistribution
andRecordPort#getSourceDataOrdering
. These should be viewed as a hints to help chose a more efficient algorithm. In such cases, though, operators must still declare data ordering and data distribution requirements; otherwise there is no guarantee that data will arrive sorted/distributed as required.Output record ports
Implementations with output record ports must declare the following:- Type: Implementations must declare their output type by calling
RecordPort#setType
.
- Output data ordering: Implementations that can make guarantees as to their output
ordering may do so by calling
RecordPort#setOutputDataOrdering
- Output data distribution (only applies to parallelizable operators): Implementations that can make guarantees as to their output
distribution may do so by calling
RecordPort#setOutputDataDistribution
Input model ports
In general, there is nothing special to declare for input model ports. Models are implicitly duplicated to all partitions when going from non-parallel to parallel operators. The case of a model going from a parallel to a non-parallel node is a special case of a "model reducer" operator. In the case of a model reducer, the downstream operator, must declare the following:- Merge handler: Model reducers must declare a merge handler by
calling
AbstractModelPort#setMergeHandler
.
MergeModel
is a convenient, re-usable model reducer, parameterized with a merge-handler.Output model ports
SimpleModelPort
's have no associated metadata and therefore there is never any output metadata to declare.PMMLPort
's, on the other hand, do have associated metadata. For all PMMLPorts, implementations must declare the following:- pmmlModelSpec: Implementations must declare the PMML model spec
by calling
PMMLPort.setPMMLModelSpec
.
- Specified by:
computeMetadata
in classStreamingOperator
- Parameters:
ctx
- the context
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execute
protected void execute(ExecutionContext ctx)
Description copied from class:ExecutableOperator
Executes the operator. Implementations should adhere to the following contracts:- Following execution, all input ports must be at end-of-data.
- Following execution, all output ports must be at end-of-data.
- Specified by:
execute
in classExecutableOperator
- Parameters:
ctx
- context in which to lookup physical ports bound to logical ports
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cloneForExecution
protected ExecutableOperator cloneForExecution()
Description copied from class:ExecutableOperator
Performs a deep copy of the operator for execution. The default implementation is implemented in terms of JSON serialization: we perform a JSON serialization followed by a JSON deserialization. As a best-practice, operator implementations should not override this method. If they must override, though, then they must guarantee that cloneForExecution copies any instance variables that are modified by execute.- Overrides:
cloneForExecution
in classExecutableOperator
- Returns:
- a deep copy of this operator
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