kafka Reducer 源码

  • 2022-10-20
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kafka Reducer 代码

文件路径:/streams/src/main/java/org/apache/kafka/streams/kstream/Reducer.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements. See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License. You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.kafka.streams.kstream;

import org.apache.kafka.streams.KeyValue;

/**
 * The {@code Reducer} interface for combining two values of the same type into a new value.
 * In contrast to {@link Aggregator} the result type must be the same as the input type.
 * <p>
 * The provided values can be either original values from input {@link KeyValue} pair records or be a previously
 * computed result from {@link Reducer#apply(Object, Object)}.
 * <p>
 * {@code Reducer} can be used to implement aggregation functions like sum, min, or max.
 *
 * @param <V> value type
 * @see KGroupedStream#reduce(Reducer)
 * @see KGroupedStream#reduce(Reducer, Materialized)
 * @see TimeWindowedKStream#reduce(Reducer)
 * @see TimeWindowedKStream#reduce(Reducer, Materialized)
 * @see SessionWindowedKStream#reduce(Reducer)
 * @see SessionWindowedKStream#reduce(Reducer, Materialized)
 * @see Aggregator
 */
public interface Reducer<V> {

    /**
     * Aggregate the two given values into a single one.
     *
     * @param value1 the first value for the aggregation
     * @param value2 the second value for the aggregation
     * @return the aggregated value
     */
    V apply(final V value1, final V value2);
}

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