使用mapreduce程序清理数据

i2loujxw  于 2021-05-30  发布在  Hadoop
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我有30行的数据。我正在尝试使用mapreduce程序清理数据。数据正在正确清理,但30行中只有一行显示。我猜读唱片的人不是在逐行阅读。请检查一下我的密码,告诉我问题出在哪里。我是hadoop新手。
数据:-

1  Vlan154.DEL-ISP-COR-SWH-002.mantraonline.com (61.95.250.140)  0.460 ms  0.374 ms  0.351 ms
 2  202.56.223.213 (202.56.223.213)  39.718 ms  39.511 ms  39.559 ms
 3  202.56.223.17 (202.56.223.17)  39.714 ms  39.724 ms  39.628 ms
 4  125.21.167.153 (125.21.167.153)  41.114 ms  40.001 ms  39.457 ms
 5  203.208.190.65 (203.208.190.65)  120.340 ms  71.384 ms  71.346 ms
 6  ge-0-1-0-0.sngtp-dr1.ix.singtel.com (203.208.149.158)  71.493 ms ge-0-1-2-0.sngtp-dr1.ix.singtel.com (203.208.149.210)  71.183 ms ge-0-1-0-0.sngtp-dr1.ix.singtel.com (203.208.149.158)  71.739 ms
 7  ge-0-0-0-0.sngtp-ar3.ix.singtel.com (203.208.182.2)  80.917 ms ge-2-0-0-0.sngtp-ar3.ix.singtel.com (203.208.183.20)  71.550 ms ge-1-0-0-0.sngtp-ar3.ix.singtel.com (203.208.182.6)  71.534 ms
 8  203.208.151.26 (203.208.151.26)  141.716 ms 203.208.145.190 (203.208.145.190)  134.740 ms 203.208.151.26 (203.208.151.26)  142.453 ms
 9  219.158.3.225 (219.158.3.225)  138.774 ms  157.205 ms  157.123 ms
10  219.158.4.69 (219.158.4.69)  156.865 ms  157.044 ms  156.845 ms
11  202.96.12.62 (202.96.12.62)  157.109 ms  160.294 ms  159.805 ms
12  61.148.3.58 (61.148.3.58)  159.521 ms  178.088 ms  160.004 ms
     MPLS Label=33 CoS=5 TTL=1 S=0
13  202.106.48.18 (202.106.48.18)  199.730 ms  181.263 ms  181.300 ms
14  * * *
15  * * *
16  * * *
17  * * *
18  * * *
19  * * *
20  * * *
21  * * *
22  * * *
23  * * *

MapReduceprogram:-
公共类跟踪数据清理{

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

    Configuration conf = new Configuration();
    String userArgs[] = new GenericOptionsParser(conf, args).getRemainingArgs();
    if (userArgs.length < 2) {
        System.out.println("Usage: hadoop jar jarfilename mainclass input output");
        System.exit(1);
    }       
    Job job = new Job(conf, "cleaning trace route data");
    job.setJarByClass(TraceRouteDataCleaning.class);        
    job.setMapperClass(TraceRouteMapper.class);
    job.setReducerClass(TraceRouteReducer.class);       
    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(Text.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(Text.class);
    job.setInputFormatClass(TextInputFormat.class);
    job.setOutputFormatClass(TextOutputFormat.class);
    FileInputFormat.addInputPath(job, new Path(userArgs[0]));
    FileOutputFormat.setOutputPath(job, new Path(userArgs[1]));     
    System.exit(job.waitForCompletion(true) ? 0 : 1);
}   
public static class TraceRouteMapper extends Mapper<LongWritable, Text, Text, Text>{        
    StringBuilder emitValue = null;
    StringBuilder emitKey = null;
    Text kword = new Text();
    Text vword = new Text();

    public void map(LongWritable key, Text value, Context context) throws InterruptedException, IOException
     {
         // String[] cleanData;
         String lines = value.toString();   
         //deleting ms in RTT time data  
         lines = lines.replace(" ms", "");               
         String[] data = lines.split(" ");          
         emitValue = new StringBuilder(1024);
         emitKey = new StringBuilder(1024);

            if (data.length == 6) {                     
                emitKey.append(data[0]);
                emitValue.append(data[1]).append("\t").append(data[2]).append("\t").append(data[3]).append("\t").append(data[4]).append("\t").append(data[5]);
                kword.set(emitKey.toString());
                vword.set(emitValue.toString());                            
                context.write(kword, vword);                    
            }               
     }              
}   

public static class TraceRouteReducer extends Reducer<Text, Text, Text, Text>{
    Text vword = new Text();
    public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException{

        context.write(key,vword);           
    }
}

}

z18hc3ub

z18hc3ub1#

第一件事你的减速机类应该根据你的要求如下。如果你的关键是没有发射多个文本,然后选择第一个减速机或选择第二个。

public static class TraceRouteReducer extends Reducer<Text, Text, Text, Text>{
Text vword = new Text();
public void reduce(Text key, Text values, Context context) throws IOException, InterruptedException{

    vword=values;

    /*
 for (Iterator iterator = values.iterator(); iterator.hasNext();) {

    vword.set(iterator.next().toString());
    System.out.println("printing " +vword.toString());

}*/

    context.write(key,vword);           

}
 }

   ----------or------------

public static class TraceRouteReducer extends Reducer<Text, Text, Text, Text>{
Text vword = new Text();
  public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException{

   for (Iterator iterator = values.iterator(); iterator.hasNext();) {

    vword.set(iterator.next().toString());
    context.write(key,vword);  

}          

}
}

second in your mapper you are splitting based on space.but not feasible as of my knowledge. split based on   "\\s+"  regular expression.

   String[] data = lines.split("\\s+");

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