/*
* 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.item;
import com.google.common.collect.Lists;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.VarIntWritable;
import org.apache.mahout.math.VarLongWritable;
import org.apache.mahout.math.Vector;
import java.io.IOException;
import java.util.List;
/**
* we use a neat little trick to explicitly filter items for some users: we inject a NaN summand into the preference
* estimation for those items, which makes {@link org.apache.mahout.cf.taste.hadoop.item.AggregateAndRecommendReducer}
* automatically exclude them
*/
public class ItemFilterAsVectorAndPrefsReducer
extends Reducer<VarLongWritable,VarLongWritable,VarIntWritable,VectorAndPrefsWritable> {
@Override
protected void reduce(VarLongWritable itemID, Iterable<VarLongWritable> values, Context ctx)
throws IOException, InterruptedException {
int itemIDIndex = TasteHadoopUtils.idToIndex(itemID.get());
Vector vector = new RandomAccessSparseVector(Integer.MAX_VALUE, 1);
/* artificial NaN summand to exclude this item from the recommendations for all users specified in userIDs */
vector.set(itemIDIndex, Double.NaN);
List<Long> userIDs = Lists.newArrayList();
List<Float> prefValues = Lists.newArrayList();
for (VarLongWritable userID : values) {
userIDs.add(userID.get());
prefValues.add(1.0f);
}
ctx.write(new VarIntWritable(itemIDIndex), new VectorAndPrefsWritable(vector, userIDs, prefValues));
}
}