大数据技术之Hadoop之MapReduce（3）——自定义InputFormat案例实操

3.1.9 自定义InputFormat案例实操

• 无论HDFS还是MapReduce，在处理小文件时效率都非常低，但又难免面临处理大量小文件的场景，此时，就需要有相应解决方案。可以自定义InputFormat实现小文件的合并。

1．需求

• 将多个小文件合并成一个SequenceFile文件（SequenceFile文件是Hadoop用来存储二进制形式的key-value对的文件格式），SequenceFile里面存储着多个文件，存储的形式为文件路径+名称为key，文件内容为value。

（1）输入数据

• one.txt

yongpeng weidong weinan
sanfeng luozong xiaoming

• two.txt

longlong fanfan
mazong kailun yuhang yixin
longlong fanfan
mazong kailun yuhang yixi

• three.txt

shuaige changmo zhenqiang
dongli lingu xuanxuan

（2）期望输出文件格式

2．程序实现

（1）自定义InputFromat

/**
 * @Author zhangyong
 * @Date 2020/3/6 22:24
 * @Version 1.0
 * 定义类继承FileInputFormat
 */
public class WholeFileInputformat extends FileInputFormat<Text, BytesWritable>{
	@Override
	protected boolean isSplitable(JobContext context, Path filename) {
		return false;
	}
	@Override
	public RecordReader<Text, BytesWritable> createRecordReader(InputSplit split, TaskAttemptContext context)	throws IOException, InterruptedException {
		WholeRecordReader recordReader = new WholeRecordReader();
		recordReader.initialize(split, context);
		return recordReader;
	}
}

（2）自定义RecordReader类

/**
 * @Author zhangyong
 * @Date 2020/3/6 22:24
 * @Version 1.0
 */
public class WholeRecordReader extends RecordReader<Text, BytesWritable> {
    private Configuration configuration;
    private FileSplit split;
    private boolean isProgress = true;
    private BytesWritable value = new BytesWritable ();
    private Text k = new Text ();
    @Override
    public void initialize(InputSplit split, TaskAttemptContext context) throws IOException, InterruptedException {
        this.split = (FileSplit) split;
        configuration = context.getConfiguration ();
    }
    @Override
    public boolean nextKeyValue() throws IOException, InterruptedException {
        if (isProgress) {
            // 1 定义缓存区
            byte[] contents = new byte[(int) split.getLength ()];
            FileSystem fs = null;
            FSDataInputStream fis = null;
            try {
                // 2 获取文件系统
                Path path = split.getPath ();
                fs = path.getFileSystem (configuration);
                // 3 读取数据
                fis = fs.open (path);
                // 4 读取文件内容
                IOUtils.readFully (fis, contents, 0, contents.length);
                // 5 输出文件内容
                value.set (contents, 0, contents.length);
                // 6 获取文件路径及名称
                String name = split.getPath ().toString ();
           		// 7 设置输出的key值
                k.set (name);
            } catch (Exception e) {
            } finally {
                IOUtils.closeStream (fis);
            }
            isProgress = false;
            return true;
        }
        return false;
    }
    @Override
    public Text getCurrentKey() throws IOException, InterruptedException {
        return k;
    }
    @Override
    public BytesWritable getCurrentValue() throws IOException, InterruptedException {
        return value;
    }
    @Override
    public float getProgress() throws IOException, InterruptedException {
        return 0;
    }
    @Override
    public void close() throws IOException {
    }
}

（3）编写SequenceFileMapper类处理流程

/**
 * @Author zhangyong
 * @Date 2020/3/6 22:24
 * @Version 1.0
 * 定义类继承FileInputFormat
 */
public class SequenceFileMapper extends Mapper<Text, BytesWritable, Text, BytesWritable> {
    @Override
    protected void map(Text key, BytesWritable value, Context context) throws IOException, InterruptedException {
        context.write (key, value);
    }
}

（4）编写SequenceFileReducer类处理流程

/**
 * @Author zhangyong
 * @Date 2020/3/6 22:24
 * @Version 1.0
 */
public class SequenceFileReducer extends Reducer<Text, BytesWritable, Text, BytesWritable> {

    @Override
    protected void reduce(Text key, Iterable<BytesWritable> values, Context context) throws IOException, InterruptedException {

        context.write (key, values.iterator ().next ());
    }
}

（5）编写SequenceFileDriver类处理流程

/**
 * @Author zhangyong
 * @Date 2020/3/6 22:24
 * @Version 1.0
 */
public class SequenceFileDriver {

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {

        // 数据输入路径和输出路径
        args = new String[2];
        args[0] = "src/main/resources/format/input";
        args[1] = "src/main/resources/format/output";

        // 读取配置文件
        Configuration cfg = new Configuration();
        cfg.set("mapreduce.framework.name", "local");
        cfg.set("fs.defaultFS", "file:///");

        final FileSystem filesystem = FileSystem.get(cfg);
        if (filesystem.exists(new Path(args[0]))) {
            filesystem.delete(new Path(args[1]), true);
        }

        Job job = Job.getInstance (cfg);

        // 2 设置jar包存储位置、关联自定义的mapper和reducer
        job.setJarByClass (SequenceFileDriver.class);
        job.setMapperClass (SequenceFileMapper.class);
        job.setReducerClass (SequenceFileReducer.class);

        // 7设置输入的inputFormat
        job.setInputFormatClass (WholeFileInputformat.class);

        // 8设置输出的outputFormat
        job.setOutputFormatClass (SequenceFileOutputFormat.class);

        // 3 设置map输出端的kv类型
        job.setMapOutputKeyClass (Text.class);
        job.setMapOutputValueClass (BytesWritable.class);

        // 4 设置最终输出端的kv类型
        job.setOutputKeyClass (Text.class);
        job.setOutputValueClass (BytesWritable.class);

        // 5 设置输入输出路径
        FileInputFormat.setInputPaths (job, new Path (args[0]));
        FileOutputFormat.setOutputPath (job, new Path (args[1]));

        // 6 提交job
        boolean result = job.waitForCompletion (true);
        System.exit (result ? 0 : 1);
    }
}

3．输出结果