Using multipleoutputs to output multiple files in MapReduce

The user is using Mapreduce By default part-＊ name ,MultipleOutputs You can output different key value pairs to different user-defined files .

The implementation process is calling output.write(key, new IntWritable(total), key.toString());

The third parameter of the method is   public void write(KEYOUT key, VALUEOUT value, String baseOutputPath) Specifies the naming prefix of the output file , Then we can pass on different key Use different baseOutputPath Make a difference key Corresponding value Output to different files , For example, output the data of the same day to a file named after that date

Hadoop Technology insider ： In depth analysis of MapReduce Architecture design and implementation principle PDF High definition scanning version http://www.linuxidc.com/Linux/2014-06/103576.htm

Test data ：ip-to-hosts.txt

18.217.167.70 United States 206.96.54.107 United States 196.109.151.139 Mauritius 174.52.58.113 United States 142.111.216.8 Canada 162.100.49.185 United States 146.38.26.54 United States 36.35.107.36 China 95.214.95.13 Spain 2.96.191.111 United Kingdom 62.177.119.177 Czech Republic 21.165.189.3 United States 46.190.32.115 Greece 113.173.113.29 Vietnam 42.65.172.142 Taiwan 197.91.198.199 South Africa 68.165.71.27 United States 110.119.165.104 China 171.50.76.89 India 171.207.52.113 Singapore 40.174.30.170 United States 191.170.95.175 United States 17.81.129.101 United States 91.212.157.202 France 173.83.82.99 United States 129.75.56.220 United States 149.25.104.198 United States 103.110.22.19 Indonesia 204.188.117.122 United States 138.23.10.72 United States 172.50.15.32 United States 85.88.38.58 Belgium 49.15.14.6 India 19.84.175.5 United States 50.158.140.215 United States 161.114.120.34 United States 118.211.174.52 Australia 220.98.113.71 Japan 182.101.16.171 China 25.45.75.194 United Kingdom 168.16.162.99 United States 155.60.219.154 Australia 26.216.17.198 United States 68.34.157.157 United States 89.176.196.28 Czech Republic 173.11.51.134 United States 116.207.191.159 China 164.210.124.152 United States 168.17.158.38 United States 174.24.173.11 United States 143.64.173.176 United States 160.164.158.125 Italy 15.111.128.4 United States 22.71.176.163 United States 105.57.100.182 Morocco 111.147.83.42 China 137.157.65.89 Australia

Each row of data in this file has two fields Namely ip Address and address ip Country corresponding to the address , With \t Separate

Code up

 public static class IPCountryReducer             extends Reducer<Text, IntWritable, Text, IntWritable> {

        private MultipleOutputs output;

        @Override         protected void setup(Context context         ) throws IOException, InterruptedException {             output = new MultipleOutputs(context);         }

        @Override         protected void reduce(Text key, Iterable<IntWritable> values, Context context         ) throws IOException, InterruptedException {             int total = 0;             for(IntWritable value: values) {                 total += value.get();             }           <span style="color:#FF0000;"> output.write(new Text("Output by MultipleOutputs"), NullWritable.get(), key.toString());             output.write(key, new IntWritable(total), key.toString());</span>

        }

        @Override         protected void cleanup(Context context         ) throws IOException, InterruptedException {             output.close();         }     }

stay reduce Of setup In the method

 output = new MultipleOutputs(context);

And then in reduce Through the output Output content to different files

  private Configuration conf;     public static final String NAME = "named_output";

    public static void main(String[] args) throws Exception {         args =new String[] {"hdfs://caozw:9100/user/hadoop/hadooprealword","hdfs://caozw:9100/user/hadoop/hadooprealword/output"};         ToolRunner.run(new Configuration(), new NamedCountryOutputJob(), args);     }

    public int run(String[] args) throws Exception {         if(args.length != 2) {             System.err.println("Usage: named_output <input> <output>");             System.exit(1);         }

        Job job = new Job(conf, "IP count by country to named files");         job.setInputFormatClass(TextInputFormat.class);

        job.setMapperClass(IPCountryMapper.class);         job.setReducerClass(IPCountryReducer.class);

        job.setMapOutputKeyClass(Text.class);         job.setMapOutputValueClass(IntWritable.class);         job.setJarByClass(NamedCountryOutputJob.class);

        FileInputFormat.addInputPath(job, new Path(args[0]));         FileOutputFormat.setOutputPath(job, new Path(args[1]));

        return job.waitForCompletion(true) ? 1 : 0;

    }

    public void setConf(Configuration conf) {         this.conf = conf;     }

    public Configuration getConf() {         return conf;     }

    public static class IPCountryMapper             extends Mapper<LongWritable, Text, Text, IntWritable> {

        private static final int country_pos = 1;         private static final Pattern pattern = Pattern.compile("\\t");

        @Override         protected void map(LongWritable key, Text value,                           Context context) throws IOException, InterruptedException {             String country = pattern.split(value.toString())[country_pos];             context.write(new Text(country), new IntWritable(1));         }     }

test result ：