/**
 * 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.hcatalog.utils;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.FloatWritable;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
import org.apache.hcatalog.common.HCatConstants;
import org.apache.hcatalog.data.HCatRecord;
import org.apache.hcatalog.mapreduce.HCatInputFormat;
import org.apache.hcatalog.mapreduce.InputJobInfo;

/**
 * This is a map reduce test for testing hcat which goes against the "numbers"
 * table. It performs a group by on the first column and a SUM operation on the
 * other columns. This is to simulate a typical operation in a map reduce program
 * to test that hcat hands the right data to the map reduce program
 * 
 * Usage: hadoop jar sumnumbers <serveruri> <output dir> <-libjars hive-hcat jar>
            The <tab|ctrla> argument controls the output delimiter
            The hcat jar location should be specified as file://<full path to jar>
 */
public class SumNumbers {

    private static final String NUMBERS_TABLE_NAME = "numbers";
    private static final String TAB = "\t";
    
  public static class SumMapper 
       extends Mapper<WritableComparable, HCatRecord, IntWritable, SumNumbers.ArrayWritable>{
      
      IntWritable intnum1000;
      // though id is given as a Short by hcat, the map will emit it as an
      // IntWritable so we can just sum in the reduce
      IntWritable id;
      
      // though intnum5 is handed as a Byte by hcat, the map() will emit it as
      // an IntWritable so we can just sum in the reduce
      IntWritable intnum5;
      IntWritable intnum100;
      IntWritable intnum;
      LongWritable longnum;
      FloatWritable floatnum;
      DoubleWritable doublenum;
    @Override
  protected void map(WritableComparable key, HCatRecord value, 
          org.apache.hadoop.mapreduce.Mapper<WritableComparable,HCatRecord,
          IntWritable,SumNumbers.ArrayWritable>.Context context) 
    throws IOException ,InterruptedException {
        intnum1000 = new IntWritable((Integer)value.get(0));
        id = new IntWritable((Short) value.get(1));
        intnum5 = new IntWritable(((Byte)value.get(2)));
        intnum100 = new IntWritable(((Integer) value.get(3)));
        intnum = new IntWritable((Integer) value.get(4));
        longnum = new LongWritable((Long) value.get(5));
        floatnum = new FloatWritable((Float) value.get(6));
        doublenum = new DoubleWritable((Double) value.get(7));
        SumNumbers.ArrayWritable outputValue = new SumNumbers.ArrayWritable(id, 
                intnum5, intnum100, intnum, longnum, floatnum, doublenum);
        context.write(intnum1000, outputValue);

    }
  }
  
  public static class SumReducer extends Reducer<IntWritable, SumNumbers.ArrayWritable, 
  LongWritable, Text> {
      
      
    LongWritable dummyLong = null;
      @Override
    protected void reduce(IntWritable key, java.lang.Iterable<ArrayWritable> 
      values, org.apache.hadoop.mapreduce.Reducer<IntWritable,ArrayWritable,LongWritable,Text>.Context context) 
      throws IOException ,InterruptedException {
          String output = key.toString() + TAB;
          Long sumid = 0l;
          Long sumintnum5 = 0l;
          Long sumintnum100 = 0l;
          Long sumintnum = 0l;
          Long sumlongnum = 0l;
          Float sumfloatnum = 0.0f;
          Double sumdoublenum = 0.0;
          for (ArrayWritable value : values) {
            sumid += value.id.get();
            sumintnum5 += value.intnum5.get();
            sumintnum100 += value.intnum100.get();
            sumintnum += value.intnum.get();
            sumlongnum += value.longnum.get();
            sumfloatnum += value.floatnum.get();
            sumdoublenum += value.doublenum.get();
        }
          output += sumid + TAB;
          output += sumintnum5 + TAB;
          output += sumintnum100 + TAB;
          output += sumintnum + TAB;
          output += sumlongnum + TAB;
          output += sumfloatnum + TAB;
          output += sumdoublenum + TAB;
          context.write(dummyLong, new Text(output));
      }
  }
  
   public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    args = new GenericOptionsParser(conf, args).getRemainingArgs();
    String[] otherArgs = new String[4];
    int j = 0;
    for(int i = 0; i < args.length; i++) {
        if(args[i].equals("-libjars")) {
            // generic options parser doesn't seem to work!
            conf.set("tmpjars", args[i+1]);
            i = i+1; // skip it , the for loop will skip its value                
        } else {
            otherArgs[j++] = args[i];
        }
    }
    if (otherArgs.length != 4) {
      System.err.println("Usage: hadoop jar sumnumbers <serveruri> <output dir> <-libjars hive-hcat jar>\n" +
            "The <tab|ctrla> argument controls the output delimiter.\n" +
            "The hcat jar location should be specified as file://<full path to jar>\n");
      System.exit(2);
    }
    String serverUri = otherArgs[0];
    String tableName = NUMBERS_TABLE_NAME;
    String outputDir = otherArgs[1];
    String dbName = "default";
    
    String principalID = System.getProperty(HCatConstants.HCAT_METASTORE_PRINCIPAL);
    if(principalID != null)
    conf.set(HCatConstants.HCAT_METASTORE_PRINCIPAL, principalID);
    Job job = new Job(conf, "sumnumbers");
    HCatInputFormat.setInput(job, InputJobInfo.create(
    		dbName, tableName, null));
    // initialize HCatOutputFormat
    
    job.setInputFormatClass(HCatInputFormat.class);
    job.setOutputFormatClass(TextOutputFormat.class);
    job.setJarByClass(SumNumbers.class);
    job.setMapperClass(SumMapper.class);
    job.setReducerClass(SumReducer.class);
    job.setMapOutputKeyClass(IntWritable.class);
    job.setMapOutputValueClass(ArrayWritable.class);
    job.setOutputKeyClass(LongWritable.class);
    job.setOutputValueClass(Text.class);
    FileOutputFormat.setOutputPath(job, new Path(outputDir));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
   
   public static class ArrayWritable implements Writable {

       // though id is given as a Short by hcat, the map will emit it as an
       // IntWritable so we can just sum in the reduce
       IntWritable id;
       
       // though intnum5 is handed as a Byte by hcat, the map() will emit it as
       // an IntWritable so we can just sum in the reduce
       IntWritable intnum5;
       
       IntWritable intnum100;
       IntWritable intnum;
       LongWritable longnum;
       FloatWritable floatnum;
       DoubleWritable doublenum;
       
       /**
     * 
     */
    public ArrayWritable() {
        id = new IntWritable();
        intnum5 = new IntWritable();
        intnum100 = new IntWritable();
        intnum = new IntWritable();
        longnum = new LongWritable();
        floatnum = new FloatWritable();
        doublenum = new DoubleWritable();
    }
    
    
    /**
     * @param id
     * @param intnum5
     * @param intnum100
     * @param intnum
     * @param longnum
     * @param floatnum
     * @param doublenum
     */
    public ArrayWritable(IntWritable id, IntWritable intnum5,
            IntWritable intnum100, IntWritable intnum, LongWritable longnum,
            FloatWritable floatnum, DoubleWritable doublenum) {
        this.id = id;
        this.intnum5 = intnum5;
        this.intnum100 = intnum100;
        this.intnum = intnum;
        this.longnum = longnum;
        this.floatnum = floatnum;
        this.doublenum = doublenum;
    }


    @Override
    public void readFields(DataInput in) throws IOException {
        id.readFields(in);
        intnum5.readFields(in);
        intnum100.readFields(in);
        intnum.readFields(in);
        longnum.readFields(in);
        floatnum.readFields(in);
        doublenum.readFields(in);
    }

    @Override
    public void write(DataOutput out) throws IOException {
        id.write(out);
        intnum5.write(out);
        intnum100.write(out);
        intnum.write(out);
        longnum.write(out);
        floatnum.write(out);
        doublenum.write(out);
        
    }
       
   }
}