Hadoop MapReduce多输出详细介绍

服务器发布日期：2024/12/25 浏览次数：1

正在浏览：Hadoop MapReduce多输出详细介绍

Hadoop MapReduce多输出

FileOutputFormat及其子类产生的文件放在输出目录下。每个reducer一个文件并且文件由分区号命名：part-r-00000，part-r-00001，等等。有时可能要对输出的文件名进行控制或让每个reducer输出多个文件。MapReduce为此提供了MultipleOutputFormat类。

MultipleOutputFormat类可以将数据写到多个文件，这些文件的名称源于输出的键和值或者任意字符串。这允许每个reducer（或者只有map作业的mapper）创建多个文件。采用name-r-nnnnn形式的文件名用于map输出，name-r-nnnnn形式的文件名用于reduce输出，其中name是由程序设定的任意名字，nnnnn是一个指名块号的整数（从0开始）。块号保证从不同块（mapper或者reducer）写的输出在相同名字情况下不会冲突。

1. 重定义输出文件名

我们可以对输出的文件名进行控制。考虑这样一个需求：按男女性别来区分度假订单数据。这需要运行一个作业，作业的输出是男女各一个文件，此文件包含男女性别的所有数据记录。

这个需求可以使用MultipleOutputs来实现：

package com.sjf.open.test;
import java.io.IOException;
import org.apache.commons.lang3.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.compress.CompressionCodec;
import org.apache.hadoop.io.compress.GzipCodec;
import org.apache.hadoop.mapred.JobPriority;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.FileSplit;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.MultipleOutputs;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import com.sjf.open.utils.ConfigUtil;
/**
 * Created by xiaosi on 16-11-7.
 */
public class VacationOrderBySex extends Configured implements Tool {
  public static void main(String[] args) throws Exception {
    int status = ToolRunner.run(new VacationOrderBySex(), args);
    System.exit(status);
  }
  public static class VacationOrderBySexMapper extends Mapper<LongWritable, Text, Text, Text> {
    public String fInputPath = "";
    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
      super.setup(context);
      fInputPath = ((FileSplit) context.getInputSplit()).getPath().toString();
    }
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
      String line = value.toString();
      if(fInputPath.contains("vacation_hot_country_order")){
        String[] params = line.split("\t");
        String sex = params[2];
        if(StringUtils.isBlank(sex)){
          return;
        }
        context.write(new Text(sex.toLowerCase()), value);
      }
    }
  }
  public static class VacationOrderBySexReducer extends Reducer<Text, Text, NullWritable, Text> {
    private MultipleOutputs<NullWritable, Text> multipleOutputs;
    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
      multipleOutputs = new MultipleOutputs<NullWritable, Text>(context);
    }
    @Override
    protected void reduce(Text key, Iterable<Text> values, Context context)
        throws IOException, InterruptedException {
      for (Text value : values) {
        multipleOutputs.write(NullWritable.get(), value, key.toString());
      }
    }
    @Override
    protected void cleanup(Context context) throws IOException, InterruptedException {
      multipleOutputs.close();
    }
  }
  @Override
  public int run(String[] args) throws Exception {
    if (args.length != 2) {
      System.err.println("./run <input> <output>");
      System.exit(1);
    }
    String inputPath = args[0];
    String outputPath = args[1];
    int numReduceTasks = 16;
    Configuration conf = this.getConf();
    conf.setBoolean("mapred.output.compress", true);
    conf.setClass("mapred.output.compression.codec", GzipCodec.class, CompressionCodec.class);
    Job job = Job.getInstance(conf);
    job.setJobName("vacation_order_by_jifeng.si");
    job.setJarByClass(VacationOrderBySex.class);
    job.setMapperClass(VacationOrderBySexMapper.class);
    job.setReducerClass(VacationOrderBySexReducer.class);
    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(Text.class);
    job.setOutputKeyClass(NullWritable.class);
    job.setOutputValueClass(Text.class);
    FileInputFormat.setInputPaths(job, inputPath);
    FileOutputFormat.setOutputPath(job, new Path(outputPath));
    job.setNumReduceTasks(numReduceTasks);
    boolean success = job.waitForCompletion(true);
    return success "htmlcode">

-rw-r--r--  3 wirelessdev wirelessdev     0 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/_SUCCESS
-rw-r--r--  3 wirelessdev wirelessdev   88574 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/f-r-00005.gz
-rw-r--r--  3 wirelessdev wirelessdev   60965 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/m-r-00012.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00000.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00001.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00002.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00003.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00004.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00005.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00006.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00007.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 10:41 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00008.gz




我们可以看到在输出文件中不仅有我们想要的输出文件类型，还有part-r-nnnnn形式的文件，但是文件内没有信息，这是程序默认的输出文件。所以我们在指定输出文件名称时（name-r-nnnnn），不要指定name为part，因为它已经被使用为默认值了。


2. 多目录输出
在MultipleOutputs的write()方法中指定的基本路径相对于输出路径进行解释，因为它可以包含文件路径分隔符（/），创建任意深度的子目录。例如，我们改动上面的需求：按男女性别来区分度假订单数据，不同性别数据位于不同子目录（例如：sex=f/part-r-00000）。


 public static class VacationOrderBySexReducer extends Reducer<Text, Text, NullWritable, Text> {
    private MultipleOutputs<NullWritable, Text> multipleOutputs;
    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
      multipleOutputs = new MultipleOutputs<NullWritable, Text>(context);
    }
    @Override
    protected void reduce(Text key, Iterable<Text> values, Context context)
        throws IOException, InterruptedException {
      for (Text value : values) {
        String basePath = String.format("sex=%s/part", key.toString());
        multipleOutputs.write(NullWritable.get(), value, basePath);
      }
    }
    @Override
    protected void cleanup(Context context) throws IOException, InterruptedException {
      multipleOutputs.close();
    }
  }



后产生的输出名称的形式为sex=f/part-r-nnnnn或者sex=m/part-r-nnnnn：




-rw-r--r--  3 wirelessdev wirelessdev     0 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/_SUCCESS
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00000.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00001.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00002.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00003.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00004.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00005.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00006.gz
-rw-r--r--  3 wirelessdev wirelessdev     20 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/part-r-00007.gz
drwxr-xr-x  - wirelessdev wirelessdev     0 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/sex=f
drwxr-xr-x  - wirelessdev wirelessdev     0 2016-12-06 12:26 tmp/data_group/order/vacation_hot_country_order_by_sex/sex=m



"htmlcode">

Configuration conf = this.getConf();
Job job = Job.getInstance(conf);
LazyOutputFormat.setOutputFormatClass(job, TextOutputFormat.class);



再次检查一下我们的输出文件（第一个例子）：


sudo -uwirelessdev hadoop fs -ls tmp/data_group/order/vacation_hot_country_order_by_sex/
Found 3 items
-rw-r--r--  3 wirelessdev wirelessdev     0 2016-12-06 13:36 tmp/data_group/order/vacation_hot_country_order_by_sex/_SUCCESS
-rw-r--r--  3 wirelessdev wirelessdev   88574 2016-12-06 13:36 tmp/data_group/order/vacation_hot_country_order_by_sex/f-r-00005.gz
-rw-r--r--  3 wirelessdev wirelessdev   60965 2016-12-06 13:36 tmp/data_group/order/vacation_hot_country_order_by_sex/m-r-00012.gz




感谢阅读，希望能帮助到大家，谢谢大家对本站的支持！

上一篇：Docker 教程之获取镜像基础知识详解

下一篇：Docker 教程之CentOS安装 Docker