/*
 * 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.mahout.cf.taste.hadoop.pseudo;

import java.io.File;
import java.io.IOException;
import java.lang.reflect.Constructor;
import java.lang.reflect.InvocationTargetException;
import java.util.Iterator;
import java.util.List;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable;
import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.recommender.RecommendedItem;
import org.apache.mahout.cf.taste.recommender.Recommender;
import org.apache.mahout.math.VarLongWritable;

/**
 * <p>
 * The {@link Reducer} which takes as input the user IDs parsed out by the map phase, and for each unique user
 * ID, computes recommendations with the configured {@link Recommender}. The results are output as
 * {@link RecommendedItemsWritable}.
 * </p>
 * 
 * @see RecommenderJob
 */
public final class RecommenderReducer extends
    Reducer<VarLongWritable,NullWritable,VarLongWritable,RecommendedItemsWritable> {
  
  static final String RECOMMENDER_CLASS_NAME = "recommenderClassName";
  static final String RECOMMENDATIONS_PER_USER = "recommendationsPerUser";
  static final String DATA_MODEL_FILE = "dataModelFile";

  private Recommender recommender;
  private int recommendationsPerUser;

  @Override
  protected void setup(Context context) throws IOException {
    Configuration jobConf = context.getConfiguration();
    String dataModelFile = jobConf.get(DATA_MODEL_FILE);
    String recommenderClassName = jobConf.get(RECOMMENDER_CLASS_NAME);
    Path dataModelPath = new Path(dataModelFile);
    FileSystem fs = FileSystem.get(dataModelPath.toUri(), jobConf);
    File tempDataFile = File.createTempFile("mahout-taste-hadoop", "txt");
    tempDataFile.deleteOnExit();
    fs.copyToLocalFile(dataModelPath, new Path(tempDataFile.getAbsolutePath()));
    FileDataModel fileDataModel = new FileDataModel(tempDataFile);

    try {
      Class<? extends Recommender> recommenderClass = Class.forName(recommenderClassName).asSubclass(
        Recommender.class);
      Constructor<? extends Recommender> constructor = recommenderClass.getConstructor(DataModel.class);
      recommender = constructor.newInstance(fileDataModel);
    } catch (NoSuchMethodException nsme) {
      throw new IllegalStateException(nsme);
    } catch (ClassNotFoundException cnfe) {
      throw new IllegalStateException(cnfe);
    } catch (InstantiationException ie) {
      throw new IllegalStateException(ie);
    } catch (IllegalAccessException iae) {
      throw new IllegalStateException(iae);
    } catch (InvocationTargetException ite) {
      throw new IllegalStateException(ite.getCause());
    }
    recommendationsPerUser = jobConf.getInt(RECOMMENDATIONS_PER_USER, 10);
  }
  
  @Override
  protected void reduce(VarLongWritable key,
                        Iterable<NullWritable> values,
                        Context context) throws IOException, InterruptedException {
    long userID = key.get();
    List<RecommendedItem> recommendedItems;
    try {
      recommendedItems = recommender.recommend(userID, recommendationsPerUser);
    } catch (TasteException te) {
      throw new IllegalStateException(te);
    }
    Iterator<RecommendedItem> it = recommendedItems.iterator();
    while (it.hasNext()) {
      if (Float.isNaN(it.next().getValue())) {
        it.remove();
      }
    }
    RecommendedItemsWritable writable = new RecommendedItemsWritable(recommendedItems);
    context.write(key, writable);
    context.getCounter(ReducerMetrics.USERS_PROCESSED).increment(1L);
    context.getCounter(ReducerMetrics.RECOMMENDATIONS_MADE).increment(recommendedItems.size());
  }
}