org.redisson.api.mapreduce.RCollectionMapReduce Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of redisson-all Show documentation

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API, Apache Tomcat, Hibernate, Spring, Set, Multimap, SortedSet, Map, List, Queue, Deque, Semaphore, Lock, AtomicLong, Map Reduce, Bloom filter, Scheduler, RPC

There is a newer version: 3.40.2

Show newest version

/**
 * Copyright (c) 2013-2024 Nikita Koksharov
 *
 * Licensed 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.redisson.api.mapreduce;

import java.util.concurrent.TimeUnit;

import org.redisson.api.RList;
import org.redisson.api.RScoredSortedSet;
import org.redisson.api.RSet;
import org.redisson.api.RSetCache;
import org.redisson.api.RSortedSet;

/**
 * 
 * MapReduce allows to process large amount of data stored in 
 * {@link RSet}, {@link RList}, {@link RSetCache}, {@link RScoredSortedSet}, {@link RSortedSet} and others  
 * using Mapper, Reducer and/or Collator tasks launched across Redisson Nodes. 
 * 
 * Usage example:
 * 
 * 
 *   public class WordMapper implements RCollectionMapper<String, String, Integer> {
 *
 *       public void map(String value, RCollector<String, Integer> collector) {
 *           String[] words = value.split("[^a-zA-Z]");
 *           for (String word : words) {
 *               collector.emit(word, 1);
 *           }
 *       }
 *       
 *   }
 *   
 *   public class WordReducer implements RReducer<String, Integer> {
 *
 *       public Integer reduce(String reducedKey, Iterator<Integer> iter) {
 *           int sum = 0;
 *           while (iter.hasNext()) {
 *              Integer i = (Integer) iter.next();
 *              sum += i;
 *           }
 *           return sum;
 *       }
 *       
 *   }
 *
 *   public class WordCollator implements RCollator<String, Integer, Integer> {
 *
 *       public Integer collate(Map<String, Integer> resultMap) {
 *           int result = 0;
 *           for (Integer count : resultMap.values()) {
 *               result += count;
 *           }
 *           return result;
 *       }
 *       
 *   }
 *   
 *   RList<String> list = redisson.getList("myWords");
 *   
 *   Map<String, Integer> wordsCount = list.<String, Integer>mapReduce()
 *     .mapper(new WordMapper())
 *     .reducer(new WordReducer())
 *     .execute();
 *
 *   Integer totalCount = list.<String, Integer>mapReduce()
 *     .mapper(new WordMapper())
 *     .reducer(new WordReducer())
 *     .execute(new WordCollator());
 *
 * 
 * 
 * @author Nikita Koksharov
 *
 * @param  input value
 * @param  output key
 * @param  output value
 */
public interface RCollectionMapReduce extends RMapReduceExecutor {

    /**
     * Defines timeout for MapReduce process
     * 
     * @param timeout for process
     * @param unit of timeout
     * @return self instance
     */
    RCollectionMapReduce timeout(long timeout, TimeUnit unit);
    
    /**
     * Setup Mapper object
     * 
     * @param mapper used during MapReduce
     * @return self instance
     */
    RCollectionMapReduce mapper(RCollectionMapper mapper);
    
    /**
     * Setup Reducer object
     * 
     * @param reducer used during MapReduce
     * @return self instance
     */
    RCollectionMapReduce reducer(RReducer reducer);
    
}