Mapreduce-实现webcount代码

参考博文：https://blog.csdn.net/qq_41035588/article/details/90514824

首先安装一个Hadoop-Eclipse-Plugin 方便来对于hdfs进行管理

参考地址：http://dblab.xmu.edu.cn/blog/hadoop-build-project-using-eclipse/

配置好Hadoop-Ecllipse-Plugin之后

建立一个txt文档，里面的内容如下：

 1 买家id 商品id 收藏日期
 2 10181 1000481 2010-04-04 16:54:31
 3 20001 1001597 2010-04-07 15:07:52
 4 20001 1001560 2010-04-07 15:08:27
 5 20042 1001368 2010-04-08 08:20:30
 6 20067 1002061 2010-04-08 16:45:33
 7 20056 1003289 2010-04-12 10:50:55
 8 20056 1003290 2010-04-12 11:57:35
 9 20056 1003292 2010-04-12 12:05:29
10 20054 1002420 2010-04-14 15:24:12
11 20055 1001679 2010-04-14 19:46:04
12 20054 1010675 2010-04-14 15:23:53
13 20054 1002429 2010-04-14 17:52:45
14 20076 1002427 2010-04-14 19:35:39
15 20054 1003326 2010-04-20 12:54:44
16 20056 1002420 2010-04-15 11:24:49
17 20064 1002422 2010-04-15 11:35:54
18 20056 1003066 2010-04-15 11:43:01
19 20056 1003055 2010-04-15 11:43:06
20 20056 1010183 2010-04-15 11:45:24
21 20056 1002422 2010-04-15 11:45:49
22 20056 1003100 2010-04-15 11:45:54
23 20056 1003094 2010-04-15 11:45:57
24 20056 1003064 2010-04-15 11:46:04
25 20056 1010178 2010-04-15 16:15:20
26 20076 1003101 2010-04-15 16:37:27
27 20076 1003103 2010-04-15 16:37:05
28 20076 1003100 2010-04-15 16:37:18
29 20076 1003066 2010-04-15 16:37:31
30 20054 1003103 2010-04-15 16:40:14
31 20054 1003100 2010-04-15 16:40:16

然后建立一个java项目

然后把所有的包都导进去，重点是mapreduce,common,yarn,hdfs的包

然后再输入代码：

 1 package mapreduce;
 2 
 3 import java.io.IOException;
 4 import java.util.StringTokenizer;
 5 import org.apache.hadoop.fs.Path;
 6 import org.apache.hadoop.io.IntWritable;
 7 import org.apache.hadoop.io.Text;
 8 import org.apache.hadoop.mapreduce.Job;
 9 import org.apache.hadoop.mapreduce.Mapper;
10 import org.apache.hadoop.mapreduce.Reducer;
11 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
12 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
13 
14 
15 public class WordCount {
16 
17 public static class doMapper extends Mapper<Object, Text, Text, IntWritable>{
18     //第一个object表示输入key的类型，第二个text表示输入value的类型；第三个text表示输出建的类型；
19     //第四个INtWritable表示输出值的类型
20     
21 public static final IntWritable one = new IntWritable(1);
22 public static Text word = new Text();
23 @Override
24 protected void map(Object key, Text value, Context context)
25 //key value是输入的key value context是记录输入的key,value
26 throws IOException, InterruptedException {
27 StringTokenizer tokenizer = new StringTokenizer(value.toString(), "\t");
28 //StringTokenizer是Java的工具包中的一个类，用于将字符串进行拆分
29 word.set(tokenizer.nextToken());
30 //返回当前位置到下一个分隔符之间的字符串
31 context.write(word, one);
32 //讲word存到容器中计一个数
33 }
34 }
35 public static class doReducer extends Reducer<Text, IntWritable, Text, IntWritable>{
36     //输入键类型，输入值类型 输出建类型，输出值类型
37 private IntWritable result = new IntWritable();
38 @Override
39 protected void reduce(Text key, Iterable<IntWritable> values, Context context)
40 throws IOException, InterruptedException {
41 int sum = 0;
42 for (IntWritable value : values) {
43 sum += value.get();
44 }
45 result.set(sum);
46 context.write(key, result);
47 }
48 }
49 public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
50 Job job = Job.getInstance();
51 job.setJobName("WordCount");
52 job.setJarByClass(WordCount.class);
53 job.setMapperClass(doMapper.class);
54 job.setReducerClass(doReducer.class);
55 job.setOutputKeyClass(Text.class);
56 job.setOutputValueClass(IntWritable.class);
57 Path in = new Path("hdfs://localhost:9000/mymapreduce1/in/buyer_favorite1");
58 Path out = new Path("hdfs://localhost:9000/mymapreduce1/out");
59 FileInputFormat.addInputPath(job, in);
60 FileOutputFormat.setOutputPath(job, out);
61 System.exit(job.waitForCompletion(true) ? 0 : 1);    
62 }
63 }

然后运行之后查看左边的菜单：

双击part-r-00000就有返回的值了

最重要的问题就是分隔的问题

StringTokenizer tokenizer = new StringTokenizer(value.toString(),"\t");

这个是根据tab键来进行分割，但是我们复制粘贴后就是空格所以要换成空格

Mapreduce-实现webcount代码

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