com.pervasive.datarush.operators.record

Class RemapFields

java.lang.Object

com.pervasive.datarush.operators.AbstractLogicalOperator

com.pervasive.datarush.operators.StreamingOperator

com.pervasive.datarush.operators.ExecutableOperator

com.pervasive.datarush.operators.record.RemapFields

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

Constructor Summary

Constructors

Constructor and 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.

Method Summary

Modifier and Type	Method and Description
protected ExecutableOperator	cloneForExecution() Performs a deep copy of the operator for execution.
protected void	computeMetadata(StreamingMetadataContext ctx) Implementations must adhere to the following contracts
protected void	execute(ExecutionContext ctx) Executes the operator.
FieldRemapping	getFieldRemapping() Gets how input fields are mapped to output fields,
RecordPort	getInput() Returns the input port
RecordPort	getOutput() Returns the output port
void	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

Methods inherited from class com.pervasive.datarush.operators.AbstractLogicalOperator

disableParallelism, getInputPorts, getOutputPorts, newInput, newInput, newOutput, newRecordInput, newRecordInput, newRecordOutput, notifyError

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface com.pervasive.datarush.operators.LogicalOperator

disableParallelism, getInputPorts, getOutputPorts

Constructor Detail

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. Use setFieldRemapping(FieldRemapping) to define a mapping to apply.

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

Method Detail

getInput

public RecordPort getInput()

Description copied from interface: PipelineOperator

Returns the input port

Specified by:

getInput in interface PipelineOperator<RecordPort>

Returns:

the input port

getOutput

public RecordPort getOutput()

Description copied from interface: PipelineOperator

Returns the output port

Specified by:

getOutput in interface PipelineOperator<RecordPort>

Returns:

the output port

getFieldRemapping

public FieldRemapping getFieldRemapping()

Gets how input fields are mapped to output fields,

Returns:

the mapping of source fields to target fields

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

computeMetadata

protected void computeMetadata(StreamingMetadataContext ctx)

Description copied from class: StreamingOperator

Implementations must adhere to the following contracts

General

Regardless of input ports/output port types, all implementations must do the following:

1. Validation. Validation of configuration should always be performed first.
2. Declare parallelizability.. Implementations must declare parallelizability by calling StreamingMetadataContext.parallelize(ParallelismStrategy).

Input record ports

Implementations with input record ports must declare the following:

1. Required data ordering:
Implementations that have data ordering requirements must declare them by calling RecordPort#setRequiredDataOrdering, otherwise data may arrive in any order.
2. Required data distribution (only applies to parallelizable operators):
Implementations that have data distribution requirements must declare them by calling RecordPort#setRequiredDataDistribution, otherwise data will arrive in an unspecified partial distribution.

Note that if the upstream operator's output distribution/ordering is compatible with those required, we avoid a re-sort/re-distribution which is generally a very large savings from a performance standpoint. In addition, some operators may chose to query the upstream output distribution/ordering by calling RecordPort#getSourceDataDistribution and RecordPort#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:

1. Type: Implementations must declare their output type by calling RecordPort#setType.

Implementations with output record ports may declare the following:

1. Output data ordering: Implementations that can make guarantees as to their output ordering may do so by calling RecordPort#setOutputDataOrdering
2. 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

Note that both of these properties are optional; if unspecified, performance may suffer since the framework may unnecessarily re-sort/re-distributed the data.

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:

1. Merge handler: Model reducers must declare a merge handler by calling AbstractModelPort#setMergeHandler.

Note that 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:

1. pmmlModelSpec: Implementations must declare the PMML model spec by calling PMMLPort.setPMMLModelSpec.

Specified by:

computeMetadata in class StreamingOperator

Parameters:

ctx - the context

execute

protected void execute(ExecutionContext ctx)

Description copied from class: ExecutableOperator

Executes the operator. Implementations should adhere to the following contracts:

1. Following execution, all input ports must be at end-of-data.
2. Following execution, all output ports must be at end-of-data.

Specified by:

execute in class ExecutableOperator

Parameters:

ctx - context in which to lookup physical ports bound to logical ports

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 class ExecutableOperator

Returns:

a deep copy of this operator