Apache Kafka ‐ 카프카 스트림즈 - thought-corner/Backend-PlayGround GitHub Wiki

/**
 * A processor of key-value pair records.
 *
 * @param <KIn> the type of input keys
 * @param <VIn> the type of input values
 * @param <KOut> the type of output keys
 * @param <VOut> the type of output values
 */
@FunctionalInterface
public interface Processor<KIn, VIn, KOut, VOut> {

    /**
     * Initialize this processor with the given context. The framework ensures this is called once per processor when the topology
     * that contains it is initialized. When the framework is done with the processor, {@link #close()} will be called on it; the
     * framework may later re-use the processor by calling {@code #init()} again.
     * <p>
     * The provided {@link ProcessorContext context} can be used to access topology and record meta data, to
     * {@link ProcessorContext#schedule(Duration, PunctuationType, Punctuator) schedule} a method to be
     * {@link Punctuator#punctuate(long) called periodically} and to access attached {@link StateStore}s.
     *
     * @param context the context; may not be null
     */
    default void init(final ProcessorContext<KOut, VOut> context) {}

    /**
     * Process the record. Note that record metadata is undefined in cases such as a forward call from a punctuator.
     *
     * @param record the record to process
     */
    void process(Record<KIn, VIn> record);

    /**
     * Close this processor and clean up any resources. Be aware that {@code #close()} is called after an internal cleanup.
     * Thus, it is not possible to write anything to Kafka as underlying clients are already closed. The framework may
     * later re-use this processor by calling {@code #init()} on it again.
     * <p>
     * Note: Do not close any streams managed resources, like {@link StateStore}s here, as they are managed by the library.
     */
    default void close() {}
}

/**
 * The {@code Transformer} interface is for stateful mapping of an input record to zero, one, or multiple new output
 * records (both key and value type can be altered arbitrarily).
 * This is a stateful record-by-record operation, i.e, {@link #transform(Object, Object)} is invoked individually for
 * each record of a stream and can access and modify a state that is available beyond a single call of
 * {@link #transform(Object, Object)} (cf. {@link KeyValueMapper} for stateless record transformation).
 * Additionally, this {@code Transformer} can {@link ProcessorContext#schedule(Duration, PunctuationType, Punctuator) schedule}
 * a method to be {@link Punctuator#punctuate(long) called periodically} with the provided context.
 * <p>
 * Use {@link TransformerSupplier} to provide new instances of {@code Transformer} to Kafka Stream's runtime.
 * <p>
 * If only a record's value should be modified {@link ValueTransformer} can be used.
 *
 * @param <K> key type
 * @param <V> value type
 * @param <R> {@link KeyValue} return type (both key and value type can be set
 *            arbitrarily)
 * @see TransformerSupplier
 * @see ValueTransformer
 * @see KStream#map(KeyValueMapper)
 * @see KStream#flatMap(KeyValueMapper)
 * @deprecated Since 4.0. Use {@link org.apache.kafka.streams.processor.api.Processor api.Processor} instead.
 */
@Deprecated
public interface Transformer<K, V, R> {

    /**
     * Initialize this transformer.
     * This is called once per instance when the topology gets initialized.
     * When the framework is done with the transformer, {@link #close()} will be called on it; the
     * framework may later re-use the transformer by calling {@link #init(ProcessorContext)} again.
     * <p>
     * The provided {@link ProcessorContext context} can be used to access topology and record meta data, to
     * {@link ProcessorContext#schedule(Duration, PunctuationType, Punctuator) schedule} a method to be
     * {@link Punctuator#punctuate(long) called periodically} and to access attached {@link StateStore}s.
     * <p>
     * Note, that {@link ProcessorContext} is updated in the background with the current record's meta data.
     * Thus, it only contains valid record meta data when accessed within {@link #transform(Object, Object)}.
     *
     * @param context the context
     */
    void init(final ProcessorContext context);

    /**
     * Transform the record with the given key and value.
     * Additionally, any {@link StateStore state} that is attached to this operator can be accessed and modified
     * arbitrarily (cf. {@link ProcessorContext#getStateStore(String)}).
     * <p>
     * If only one record should be forward downstream, {@code transform} can return a new {@link KeyValue}. If
     * more than one output record should be forwarded downstream, {@link ProcessorContext#forward(Object, Object)}
     * and {@link ProcessorContext#forward(Object, Object, To)} can be used.
     * If no record should be forwarded downstream, {@code transform} can return {@code null}.
     *
     * Note that returning a new {@link KeyValue} is merely for convenience. The same can be achieved by using
     * {@link ProcessorContext#forward(Object, Object)} and returning {@code null}.
     *
     * @param key the key for the record
     * @param value the value for the record
     * @return new {@link KeyValue} pair&mdash;if {@code null} no key-value pair will
     * be forwarded to down stream
     */
    R transform(final K key, final V value);

    /**
     * Close this transformer and clean up any resources. The framework may
     * later re-use this transformer by calling {@link #init(ProcessorContext)} on it again.
     * <p>
     * To generate new {@link KeyValue} pairs {@link ProcessorContext#forward(Object, Object)} and
     * {@link ProcessorContext#forward(Object, Object, To)} can be used.
     */
    void close();

}