/**
 * 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.preparation;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.VarLongWritable;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
import org.apache.mahout.math.hadoop.similarity.cooccurrence.Vectors;

import java.io.IOException;
import java.util.Iterator;

public class ToItemVectorsMapper
    extends Mapper<VarLongWritable,VectorWritable,IntWritable,VectorWritable> {

  public static final String SAMPLE_SIZE = ToItemVectorsMapper.class + ".sampleSize";

  enum Elements {
    USER_RATINGS_USED, USER_RATINGS_NEGLECTED
  }

  private int sampleSize;

  @Override
  protected void setup(Context ctx) throws IOException, InterruptedException {
    sampleSize = ctx.getConfiguration().getInt(SAMPLE_SIZE, Integer.MAX_VALUE);
  }

  @Override
  protected void map(VarLongWritable rowIndex, VectorWritable vectorWritable, Context ctx)
      throws IOException, InterruptedException {
    Vector userRatings = vectorWritable.get();

    int numElementsBeforeSampling = userRatings.getNumNondefaultElements();
    userRatings = Vectors.maybeSample(userRatings, sampleSize);
    int numElementsAfterSampling = userRatings.getNumNondefaultElements();

    int column = TasteHadoopUtils.idToIndex(rowIndex.get());
    VectorWritable itemVector = new VectorWritable(new RandomAccessSparseVector(Integer.MAX_VALUE, 1));
    itemVector.setWritesLaxPrecision(true);

    Iterator<Vector.Element> iterator = userRatings.iterateNonZero();
    while (iterator.hasNext()) {
      Vector.Element elem = iterator.next();
      itemVector.get().setQuick(column, elem.get());
      ctx.write(new IntWritable(elem.index()), itemVector);
    }

    ctx.getCounter(Elements.USER_RATINGS_USED).increment(numElementsAfterSampling);
    ctx.getCounter(Elements.USER_RATINGS_NEGLECTED).increment(numElementsBeforeSampling - numElementsAfterSampling);
  }

}