MapReduce的常见输入格式之NlineInputFormat

有两个文件：

NlineInputFormat

• 切片策略： 读取配置文件中的参数mapreduce.input.lineinputformat.linespermap，默认为1，以文件为单位，切片每此参数行作为1片！
• 既然有参数，那就可以修改，设置为每N行切为一片：

Configuration conf = new Configuration();
conf.set("mapreduce.input.lineinputformat.linespermap", "2")

RecordReader：LineRecordReader，一次处理一行，将一行内容的偏移量作为key，一行内容作为value
它们的数据类型：

LongWritable key
Text value

所以上面两个文件总共八行，若一行切一片，则有八片；两行切一片，则有四片。

WCMapper.java

public class WCMapper extends Mapper<LongWritable, Text, Text, IntWritable>{

    private Text out_key=new Text();
    private IntWritable out_value=new IntWritable(1);

    @Override
    protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, IntWritable>.Context context)
            throws IOException, InterruptedException {

        System.out.println("keyin:"+key+"----keyout:"+value);

        String[] words = value.toString().split("\t");

        for (String word : words) {
            out_key.set(word);
            //写出数据(单词,1)
            context.write(out_key, out_value);
        }

    }
}

WCReducer.java

public class WCReducer extends Reducer<Text, IntWritable, Text, IntWritable>{

    private IntWritable out_value=new IntWritable();

    // reduce一次处理一组数据，key相同的视为一组
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values,
            Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {

        int sum=0;

        for (IntWritable intWritable : values) {
            sum+=intWritable.get(); 
        }

        out_value.set(sum);

        //将累加的值写出
        context.write(key, out_value);

    }
}

WCDriver.java

public class WCDriver {

    public static void main(String[] args) throws Exception {

        Path inputPath=new Path("e:/mrinput/nline");
        Path outputPath=new Path("e:/mroutput/nline");

        //作为整个Job的配置
        Configuration conf = new Configuration();

        conf.set("mapreduce.input.lineinputformat.linespermap", "2");//设置为每两行切一片

        //保证输出目录不存在
        FileSystem fs=FileSystem.get(conf);

        if (fs.exists(outputPath)) {
            fs.delete(outputPath, true);
        }

        // ①创建Job
        Job job = Job.getInstance(conf);

        job.setJarByClass(WCDriver.class);

        // ②设置Job
        // 设置Job运行的Mapper，Reducer类型，Mapper,Reducer输出的key-value类型
        job.setMapperClass(WCMapper.class);
        job.setReducerClass(WCReducer.class);

        // Job需要根据Mapper和Reducer输出的Key-value类型准备序列化器，通过序列化器对输出的key-value进行序列化和反序列化
        // 如果Mapper和Reducer输出的Key-value类型一致，直接设置Job最终的输出类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        // 声明使用NLineInputFormat
        job.setInputFormatClass(NLineInputFormat.class);

        // 设置输入目录和输出目录
        FileInputFormat.setInputPaths(job, inputPath);
        FileOutputFormat.setOutputPath(job, outputPath);

        // ③运行Job
        job.waitForCompletion(true);

    }
}

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