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

Class SubJobExecutor

  • All Implemented Interfaces:
    LogicalOperator, PipelineOperator<RecordPort>, RecordPipelineOperator
    public class SubJobExecutor
extends AbstractExecutableRecordPipeline
    The SubJobExecutor operator can be used to execute JSON serialized subgraphs within the current workflow. This can allow you to dynamically run a subgraph within the currently executing graph with alternative parameters or configuration. Within the subgraph itself two special operators can be used to dynamically configure the graph or to extract data produced by the the subgraph. A MockableExternalRecordSource explicitly named 'Start Node' and a MockableExternalRecordSink explicitly named 'Stop Node' can be used to utilized this feature. The input port should consist of a record containing one or more string fields with the first field always consisting of the path to the JSON serialized graph that should be executed. Any remaining fields in the input are considered override properties for the 'Start Node' with the field name being the key and the contents of the field used as the value. The override port can be used to override any applicable value within the graph and additionally contains several special overrides for altering JDBC connections. The first field should contain keys and the second field should contain the associated values. These work the same as when defining override values for a graph on the command line interface.

    • Constructor Detail

      • SubJobExecutor

        public SubJobExecutor()

    • Method Detail

      • getOverrides

        public RecordPort getOverrides()
        Get the optional overrides data port. If used should contain a record with two String fields representing the key, value pairs of the overrides and any additional DB specific overrides.
        Returns:
        input data port for override properties

      • getUseCustomConfig

        public boolean getUseCustomConfig()
        Get whether a custom engine configuration included in the serialized graphs should be used. Otherwise defaults to using the engine configuration of the parent graph.
        Returns:
        true if a custom engine configuration will be used

      • setUseCustomConfig

        public void setUseCustomConfig​(boolean useCustomConfig)
        Set whether a custom engine configuration included in the serialized graphs should be used. Otherwise defaults to using the engine configuration of the parent graph.
        Parameters:
        useCustomConfig - if a custom engine configuration should be used

      • getOutputType

        public RecordTokenType getOutputType()
        Get the configured output type of the subgraph.
        Returns:
        outputType of the subgraphs executed by this operator

      • setOutputType

        public void setOutputType​(RecordTokenType outputType)
        Set the configured output type of the subgraph. Should match the output type of the "Stop Node" if included in the subgraphs.
        Parameters:
        outputType - of the subgraphs executed by 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

      • 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