大数据技术之Hadoop之MapReduce（3）——CombineTextInputFormat

3.1.5 CombineTextInputFormat案例实操

示例：统计单词个数

1. 准备工作
   在hdfs的根目录下创建input文件夹，然后在里面放置4个大小分别为1.5M、35M、5.5M、6.5M的小文件作为输入数据
2. 具体代码

• Mapper类

/**
 * @Author zhangyong
 * @Date 2020/3/4 16:35
 * @Version 1.0
 */
public class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
    private Text mapOutputKey = new Text();
    private IntWritable mapOutputValue = new IntWritable();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String linevalue = value.toString();  //1.将读取的文件变成，偏移量+内容//读取一行数据
        StringTokenizer st = new StringTokenizer(linevalue);//使用空格分隔
        while (st.hasMoreTokens()) {//判断是否还有分隔符，有的话代表还有单词
            String word = st.nextToken();//返回从当前位置到下一个分隔符之间的字符串（单词）
            mapOutputKey.set(word);
            mapOutputValue.set(1);
            context.write(mapOutputKey, mapOutputValue);
        }
    }
}

• Reducer类：

/**
 * @Author zhangyong
 * @Date 2020/3/4 16:35
 * @Version 1.0
 */
public class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
    private IntWritable outputValue = new IntWritable();
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        int sum = 0;    //汇总
        for (IntWritable value : values) {
            sum += value.get();
        }
        outputValue.set(sum);
        context.write(key, outputValue);
    }
}

• Driver类

/**
 * @Author zhangyong
 * @Date 2020/3/4 16:35
 * @Version 1.0
 */
public class WordCountDriver {
    public static void main(String[] args) throws Exception {
       //需要在resources下面提供core-site.xml文件
        args = new String[]{
                "/input/",
                "/output/"
        };

        Configuration cfg = new Configuration();   //获取配置

        Job job = Job.getInstance(cfg, WordCountDriver.class.getSimpleName());
        job.setJarByClass(WordCountDriver.class);

        //如果不设置InputFormat，默认是TextInputFormat
        job.setInputFormatClass(CombineTextInputFormat.class);
		//虚拟存储切片最大值设为20M
        CombineTextInputFormat.setMaxInputSplitSize(job,20*1024*1024);
  
        //设置map与需要设置的内容类 + 输出key与value
        job.setMapperClass(WordCountMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);

        //设置reduce
        job.setReducerClass(WordCountReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        //设置input与output
        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        //将job交给Yarn
        boolean issucess = job.waitForCompletion(true);
        int status=  issucess ? 0 : 1;
        System.exit(status);
    }
}

3. 运行结果