MapReduce明星搜索指数统计，找出人气王

package com.buaa;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

/** 
* @ProjectName CountStarSearchIndex
* @PackageName com.buaa
* @ClassName SearchStarIndex
* @Description 统计分别统计出男女明星最大搜索指数
* @Author 刘吉超
* @Date 2016-05-12 16:30:23
*/
public class SearchStarIndex extends Configured implements Tool {
    // 分隔符\t
    private static String TAB_SEPARATOR = "\t";
    // 男
    private static String MALE = "male";
    // 女
    private static String FEMALE = "female";
    
    /*
     * 解析明星数据
     */
    public static class IndexMapper extends Mapper<Object, Text, Text, Text> {
        /*
         * 每次调用map(LongWritable key, Text value, Context context)解析一行数据。
         * 每行数据存储在value参数值中。然后根据‘\t‘分隔符，解析出明星姓名，性别和搜索指数
         */
        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            // 将数据解析为数组
            String[] tokens = value.toString().split(TAB_SEPARATOR);
            
            if(tokens != null && tokens.length >= 3){
                // 性别
                String gender = tokens[1].trim();
                // 名称、关注指数
                String nameHotIndex = tokens[0].trim() + TAB_SEPARATOR + tokens[2].trim();
                
                // 输出key=gender value=name+hotIndex
                context.write(new Text(gender), new Text(nameHotIndex));
            }
        }
    }
    
    /*
     * 根据性别对数据进行分区，将 Mapper的输出结果均匀分布在 reduce上
     */
    public static class IndexPartitioner extends Partitioner<Text, Text> {         
        @Override
        public int getPartition(Text key, Text value, int numReduceTasks) { 
            // 按性别分区
            String sex = key.toString();
            
            // 默认指定分区 0
            if(numReduceTasks == 0)
                return 0;
            
            // 性别为男，选择分区0
            if(MALE.equals(sex)){           
                return 0;
            }else if(FEMALE.equals(sex)){ // 性别为女，选择分区1
                return 1 % numReduceTasks;
            }else // 性别未知，选择分区2
                return 2 % numReduceTasks;
           
        }
    }
    
    /*
     * 定义Combiner，对 map端的输出结果，先进行一次合并，减少数据的网络输出
     */
    public static class IndexCombiner extends Reducer<Text, Text, Text, Text> {
        
        @Override
        public void reduce(Text key, Iterable<Text> values, Context context)throws IOException, InterruptedException {
            int maxHotIndex = Integer.MIN_VALUE;
            String name= "";
            
            for (Text val : values) {
                String[] valTokens = val.toString().split(TAB_SEPARATOR);
                
                int hotIndex = Integer.parseInt(valTokens[1]);
                
                if(hotIndex > maxHotIndex){
                    name = valTokens[0];
                    maxHotIndex = hotIndex;
                }
            }
            
            context.write(key, new Text(name + TAB_SEPARATOR + maxHotIndex));
        }
    }
    
    /*
     * 统计男、女明星最高搜索指数
     */
    public static class IndexReducer extends Reducer<Text, Text, Text, Text> {
        /*
         * 调用reduce(key, Iterable< Text> values, context)方法来处理每个key和values的集合。
         * 我们在values集合中，计算出明星的最大搜索指数
         */
        @Override
        public void reduce(Text key, Iterable<Text> values, Context context)throws IOException, InterruptedException {
            int maxHotIndex = Integer.MIN_VALUE;
            String name = " ";
            
            // 根据key，迭代 values集合，求出最高搜索指数
            for (Text val : values) {
                String[] valTokens = val.toString().split(TAB_SEPARATOR);
                
                int hotIndex = Integer.parseInt(valTokens[1]);
                
                if (hotIndex > maxHotIndex) {
                    name = valTokens[0];
                    maxHotIndex = hotIndex;
                }
            }
            
            context.write(new Text(name), new Text(key + TAB_SEPARATOR + maxHotIndex));
        }
    }
    
    @SuppressWarnings("deprecation")
    @Override
    public int run(String[] args) throws Exception {
        // 读取配置文件
        Configuration conf = new Configuration();
        
        // 如果目标文件夹存在，则删除
        Path mypath = new Path(args[1]);
        FileSystem hdfs = mypath.getFileSystem(conf);
        if (hdfs.isDirectory(mypath)) {
            hdfs.delete(mypath, true);
        }

        // 新建一个任务
        Job job = new Job(conf, "searchStarIndex");
        // 主类
        job.setJarByClass(SearchStarIndex.class);
        
        // reduce的个数设置为2
        job.setNumReduceTasks(2);
        // 设置Partitioner类
        job.setPartitionerClass(IndexPartitioner.class);
        
        // Mapper
        job.setMapperClass(IndexMapper.class);
        // Reducer
        job.setReducerClass(IndexReducer.class);
        
        // map 输出key类型
        job.setMapOutputKeyClass(Text.class);
        // map 输出value类型
        job.setMapOutputValueClass(Text.class);
        
        // 设置Combiner类
        job.setCombinerClass(IndexCombiner.class);
        
        // 输出结果 key类型
        job.setOutputKeyClass(Text.class);
        // 输出结果 value类型
        job.setOutputValueClass(Text.class);
        
        // 输入路径
        FileInputFormat.addInputPath(job, new Path(args[0]));
        // 输出路径
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        
        // 提交任务
        return job.waitForCompletion(true) ? 0 : 1;
    }
    
    public static void main(String[] args) throws Exception {
        String[] args0 = { 
                "hdfs://ljc:9000/buaa/index/index.txt",
                "hdfs://ljc:9000/buaa/index/out/"
        };
        int ec = ToolRunner.run(new Configuration(), new SearchStarIndex(), args0);
        System.exit(ec);
    }
}