Examples of groovyx.gpars.dataflow.operator.DataflowOperator

groovyx.gpars.dataflow.operator.DataflowOperator
Dataflow selectors and operators (processors) form the basic units in dataflow networks. They are typically combined into oriented graphs that transform data. They accept a set of input and output dataflow channels so that once values are available to be consumed in all the input channels the operator's body is triggered on the values, potentially generating values to be written into the output channels. The output channels at the same time are suitable to be used as input channels by some other dataflow processors. The channels allow processors to communicate.
Dataflow selectors and operators enable creation of highly concurrent applications yet the abstraction hides the low-level concurrency primitives and exposes much friendlier API. Since selectors and operators internally leverage the actor implementation, they reuse a pool of threads and so the actual number of threads used by the calculation can be kept much lower than the actual number of processors used in the network.
@author Vaclav PechDate: Sep 9, 2009

     * @param channels A map specifying "inputs" and "outputs" - dataflow channels (instances of the DataflowQueue or DataflowVariable classes) to use for inputs and outputs
     * @param code     The operator's body to run each time all inputs have a value to read
     * @return A new started operator instance with all the channels set
     */
    public final DataflowProcessor operator(final Map channels, @DelegatesTo(DataflowOperator.class) final Closure code) {
        return new DataflowOperator(this, channels, code).start();
    }

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     */
    public final DataflowProcessor operator(final List inputChannels, final List outputChannels, @DelegatesTo(DataflowOperator.class) final Closure code) {
        final HashMap<String, List> params = new HashMap<String, List>(5);
        params.put(DataflowProcessor.INPUTS, inputChannels);
        params.put(DataflowProcessor.OUTPUTS, outputChannels);
        return new DataflowOperator(this, params, code).start();
    }

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    public final DataflowProcessor operator(final List inputChannels, final List outputChannels, final int maxForks, @DelegatesTo(DataflowOperator.class) final Closure code) {
        final HashMap<String, Object> params = new HashMap<String, Object>(5);
        params.put(DataflowProcessor.INPUTS, inputChannels);
        params.put(DataflowProcessor.OUTPUTS, outputChannels);
        params.put(DataflowProcessor.MAX_FORKS, maxForks);
        return new DataflowOperator(this, params, code).start();
    }

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     */
    public final DataflowProcessor operator(final DataflowReadChannel input, final DataflowWriteChannel output, @DelegatesTo(DataflowOperator.class) final Closure code) {
        final HashMap<String, List> params = new HashMap<String, List>(5);
        params.put(DataflowProcessor.INPUTS, asList(input));
        params.put(DataflowProcessor.OUTPUTS, asList(output));
        return new DataflowOperator(this, params, code).start();
    }

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    public final DataflowProcessor operator(final DataflowReadChannel input, final DataflowWriteChannel output, final int maxForks, @DelegatesTo(DataflowOperator.class) final Closure code) {
        final HashMap<String, Object> params = new HashMap<String, Object>(5);
        params.put(DataflowProcessor.INPUTS, asList(input));
        params.put(DataflowProcessor.OUTPUTS, asList(output));
        params.put(DataflowProcessor.MAX_FORKS, maxForks);
        return new DataflowOperator(this, params, code).start();
    }

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        if (inputChannel == null || outputChannels == null || outputChannels.isEmpty())
            throw new IllegalArgumentException(A_SPLITTER_NEEDS_AN_INPUT_CHANNEL_AND_AT_LEAST_ONE_OUTPUT_CHANNEL_TO_BE_CREATED);
        final HashMap<String, List> params = new HashMap<String, List>(5);
        params.put(DataflowProcessor.INPUTS, asList(inputChannel));
        params.put(DataflowProcessor.OUTPUTS, outputChannels);
        return new DataflowOperator(this, params, new DataflowProcessorAtomicBoundAllClosure()).start();
    }

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            throw new IllegalArgumentException(A_SPLITTER_NEEDS_AN_INPUT_CHANNEL_AND_AT_LEAST_ONE_OUTPUT_CHANNEL_TO_BE_CREATED);
        final HashMap<String, Object> params = new HashMap<String, Object>(5);
        params.put(DataflowProcessor.INPUTS, asList(inputChannel));
        params.put(DataflowProcessor.OUTPUTS, outputChannels);
        params.put(DataflowProcessor.MAX_FORKS, maxForks);
        return new DataflowOperator(this, params, new DataflowProcessorAtomicBoundAllClosure()).start();
    }

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