Module datarush.library
Package com.pervasive.datarush.operators.model

Class PutModel<T>

java.lang.Object
com.pervasive.datarush.operators.AbstractLogicalOperator
com.pervasive.datarush.operators.StreamingOperator
com.pervasive.datarush.operators.ExecutableOperator
com.pervasive.datarush.operators.model.PutModel<T>
Type Parameters:
T - the type of the model
All Implemented Interfaces:
LogicalOperator, SourceOperator<AbstractModelPort<T>>
Direct Known Subclasses:
PutPMML
public class PutModel<T> extends ExecutableOperator implements SourceOperator<AbstractModelPort<T>>
Provides a way to inject an in-memory reference to a model object into a graph. This is typically used when a graph is embedded within a larger context where we already have a reference to a model object. This operator is always implicitly non-parallel; if the target is parallel, a scatter will be performed, sending a copy of the model to all partitions.

NOTE: this operator is non-parallel

  • Constructor Details

    • PutModel

      public PutModel(LogicalPortFactory<? extends AbstractModelPort<T>> factory)
      Injects a model into a graph. Prior to graph execution, the following required property must be set:
      1. model
      Parameters:
      factory - the port factory for the model

    • PutModel

      public PutModel(LogicalPortFactory<? extends AbstractModelPort<T>> factory, T model)
      Injects a model into a graph
      Parameters:
      factory - the port factory for the model
      model - the model to inject.

  • Method Details

    • getModel

      public final T getModel()
      Returns the model to be injected
      Returns:
      the model to be injected

    • setModel

      public final void setModel(T model)
      Sets the model to be injected
      Parameters:
      model - the model

    • getOutput

      public final AbstractModelPort<T> getOutput()
      Returns the output port which will transmit the model during graph execution
      Specified by:
      getOutput in interface SourceOperator<T>
      Returns:
      the output port

    • getModelReference

      public final Reference<T> getModelReference()
      For advanced use only; returns the reference location where the model is to be obtained.
      Returns:
      the reference location

    • setModelReference

      public final void setModelReference(Reference<T> reference)
      For advanced use only; sets the reference location where the model is to be obtained.
      Parameters:
      reference - the reference location

    • computeMetadata

      protected final 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

    • cloneForExecution

      protected final 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 final 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