Module datarush.library
Package 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 Details

    • ExternalRecordSink

      public ExternalRecordSink()
      Default constructor. No additional configuration is needed

  • Method Details

    • 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:
        2. 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):
        3. 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