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 * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
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 * accompanied this code).
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package java.util.stream;

/**
 * An operation in a stream pipeline that takes a stream as input and produces a stream, possibly of a different
 * type, as output.  An intermediate operation has an input type and an output type (and, an associated input
 * shape and output shape).  An intermediate operation also has a set of <em>operation flags</em> that describes
 * how the operation transforms characteristics of the stream (such as sortedness or size; see
 * {@link StreamOpFlag}).
 *
 * <p>Intermediate operations are implemented in terms of <em>sink transforms</em>; given a {@code Sink} for the
 * output type of the operation, produce a {@code Sink} for the input type of the operation, which, when fed with
 * values, has the effect of implementing the desired operation on the input values and feeding them to the output
 * sink.
 *
 * <p>Some intermediate operations are <em>stateful</em>.  This means that the sinks they produce as a result of
 * the above wrapping may maintain state from processing earlier elements.  Stateful intermediate operations must
 * implement the {@link StatefulOp} interface.
 *
 * @apiNote
 * As an example, consider the stream pipeline:
 * <pre>
 *     int oldestBob = people.stream().filter(p -> p.getFirstName.equals("Bob")).map(p -> p.getAge()).max();
 * </pre>
 *
 * <p>This pipeline has two intermediate operations, filter and map.  The filtering operation has input and output types
 * of {@code Person} (with input and output shape of {@code REFERENCE}), and the mapping operation has an input
 * type of {@code Person} and an output type of {@code Integer} (with shape {@code INT_VALUE}.)  When we construct
 * a sink chain, the mapping operation will be asked to transform a {@code Sink.OfInt} which computes the maximum
 * value into a {@code Sink} which accepts {@code Person} objects, and whose behavior is to take the supplied
 * {@code Person}, call {@code getAge()} on it, and pass the resulting value to the downstream sink.  This sink
 * transform might be implement as:
 *
 * <pre>
 *     new Sink.ChainedReference<U>(sink) {
 *         public void accept(U u) {
 *             downstream.accept(mappingFunction.applyAsInt(u));
 *         }
 *     }
 * </pre>
 *
 * @param <E_IN>  Type of input elements to the operation
 * @param <E_OUT> Type of output elements to the operation
 * @see TerminalOp
 * @see StatefulOp
 * @since 1.8
 */
interface IntermediateOp<E_IN, E_OUT> {

    /**
     * Get the shape of the input type of this operation
     * @implSpec The default returns {@code StreamShape.REFERENCE}
     * @return Shape of the input type of this operation
     */
    default StreamShape inputShape() { return StreamShape.REFERENCE; }

    /**
     * Get the shape of the output type of this operation
     * @implSpec The default returns {@code StreamShape.REFERENCE}
     * @return Shape of the output type of this operation
     */
    default StreamShape outputShape() { return StreamShape.REFERENCE; }

    /**
     * Get the operation flags of this operation.
     *
     * @implSpec The default returns {@code 0}
     * @return a bitmap describing the operation flags of this operation
     * @see StreamOpFlag
     */
    default int getOpFlags() { return 0; }

    /**
     * Return whether this operation is stateful or not.  If it is stateful, then the method
     * {@link #evaluateParallel(PipelineHelper)} must be overridden.
     *
     * @implSpec The default implementation returns {@code false}.
     *
     * @return {@code true} then operation is stateful
     */
    default boolean isStateful() { return false; }

    /**
     * Accept a {@code Sink} which will receive the results of this operation, and return a {@code Sink}
     * which accepts elements of the input type of this operation and which performs the operation, passing
     * the results to the provided {@code Sink}.
     *
     * <p>The implementation may use the {@code flags} parameter to optimize the sink wrapping.  For example, if
     * the input is already {@code DISTINCT}, the implementation for the {@code Stream#distinct()} method could
     * just return the sink it was passed.
     *
     * @param flags The combined stream and operation flags up to, but not including, this operation.
     * @param sink elements will be sent to this sink after the processing.
     * @return a sink which will accept elements and perform the operation upon
     *         each element, passing the results (if any) to the provided {@code Sink}.
     */
    Sink<E_IN> wrapSink(int flags, Sink<E_OUT> sink);

    /**
     * Perform a parallel evaluation of the operation using the specified {@code PipelineHelper}, which describes
     * the stream source and upstream intermediate operations.  Only called on stateful operations.
     * If {@link #isStateful()} returns true then implementations must override the default implementation.
     *
     * @implSpec The default implementation throws an {@link UnsupportedOperationException}
     *
     * @param helper the pipeline helper
     * @param <P_IN> the type of elements in the pipeline source
     * @return a {@code Node} describing the result of the evaluation
     */
    default <P_IN> Node<E_OUT> evaluateParallel(PipelineHelper<P_IN, E_OUT> helper) {
        throw new UnsupportedOperationException("Parallel evaluation is not supported");
    }
}