com.pervasive.datarush.ports.record

Class ExternalRecordSink

java.lang.Object

com.pervasive.datarush.operators.AbstractLogicalOperator

com.pervasive.datarush.operators.StreamingOperator

com.pervasive.datarush.operators.ExecutableOperator

com.pervasive.datarush.ports.record.ExternalRecordSink

All Implemented Interfaces:

LogicalOperator, RecordSinkOperator, SinkOperator<RecordPort>

public final class ExternalRecordSink
extends ExecutableOperator
implements RecordSinkOperator

Defines an external sink of record data. External record sinks are used in cases where an external, non-DataRush, application needs to receive data from a DataRush graph. Note that because external ports are not managed by the standard DataRush deadlock detection mechanisms, care must be taken to avoid deadlock. Specifically, consumers need to ensure that there is a thread per-sink draining the output data. Moreover, that thread cannot be the same thread that is running the LogicalGraph. The most common usage pattern is to start the LogicalGraph in the background using the method LogicalGraphInstance#start(). For example:

       //create the graph
       LogicalGraph graph= LogicalGraphFactory.newLogicalGraph();
       
       //add some operators to the graph
       op= graph.add(...);
       
       //add the external sink to the graph
       ExternalRecordSink sink= graph.add(new ExternalRecordSink());
       //connect the input to the sink
       graph.connect(op.getOutput(), sink.getInput());
       
       //compile the graph
       LogicalGraphInstance instance= graph.compile();
       
       //*always* call start to start in background, not run since run will deadlock!!
       instance.start();
       
       //process the sink results in this thread
       RecordInput rec= sink.getOutput();
       while ( rec.stepNext() ) {
           ...
       }
       
       //after processing all results, join on the graph
       //don't join before since it will deadlock!
       instance.join();
 

NOTE: this operator is non-parallel

Constructor Summary

Constructors

Constructor and Description
ExternalRecordSink() Default constructor.

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.
RecordPort	getInput() Gets the record port providing the input data to the sink.
RecordInput	getOutput() Returns the external port that an external application can use to receive data from this sink.
boolean	isIgnoreSortOrder() If set to true, the sink will return records in any order.
protected void	notifyError(Throwable e) Called to notify the operator that the graph terminated abnormally either before the operator had a chance to run or while the operator is running.
void	setIgnoreSortOrder(boolean ignoreSortOrder) If set to true, the sink will return records in any order.

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

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

ExternalRecordSink

public ExternalRecordSink()

Default constructor. No additional configuration is needed

Method Detail

getInput

public RecordPort getInput()

Description copied from interface: RecordSinkOperator

Gets the record port providing the input data to the sink.

Specified by:

getInput in interface RecordSinkOperator

Specified by:

getInput in interface SinkOperator<RecordPort>

Returns:

the input port for the sink

isIgnoreSortOrder

public boolean isIgnoreSortOrder()

If set to true, the sink will return records in any order. If false, the sink will preserve the current sorted state of the input.

Returns:

whether to ignore sort order.

setIgnoreSortOrder

public void setIgnoreSortOrder(boolean ignoreSortOrder)

If set to true, the sink will return records in any order. If false, the sink will preserve the current sorted state of the input.

Parameters:

ignoreSortOrder - whether to ignore sort order.

getOutput

public RecordInput getOutput()

Returns the external port that an external application can use to receive data from this sink.

Returns:

the external port.

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

notifyError

protected void notifyError(Throwable e)

Description copied from class: AbstractLogicalOperator

Called to notify the operator that the graph terminated abnormally either before the operator had a chance to run or while the operator is running. If this is a CompositeOperator, this method will be invoked if any of the components

Overrides:

notifyError in class AbstractLogicalOperator

Parameters:

e - the error that occured

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

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