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027_编写MapReduce的模板类Mapper、Reducer和Driver

模板类编写好后写MapReduce程序，的模板类编写好以后只需要改参数就行了，代码如下：

  1 package org.dragon.hadoop.mr.module;
  2 
  3 import java.io.IOException;
  4 
  5 import org.apache.hadoop.conf.Configuration;
  6 import org.apache.hadoop.conf.Configured;
  7 import org.apache.hadoop.fs.Path;
  8 import org.apache.hadoop.io.LongWritable;
  9 import org.apache.hadoop.io.Text;
 10 import org.apache.hadoop.mapreduce.Job;
 11 import org.apache.hadoop.mapreduce.Mapper;
 12 import org.apache.hadoop.mapreduce.Reducer;
 13 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
 14 import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
 15 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
 16 import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
 17 import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;
 18 import org.apache.hadoop.util.Tool;
 19 import org.apache.hadoop.util.ToolRunner;
 20 
 21 /**
 22  * 
 23  * ########################################### 
 24  * ############     MapReduce 模板类        ########## 
 25  * ###########################################
 26  * 
 27  * @author ZhuXY
 28  * @time 2016-3-13 下午10:21:06
 29  * 
 30  */
 31 public class ModuleMapReduce extends Configured implements Tool {
 32 
 33     /**
 34      * Mapper Class
 35      */
 36     public static class ModuleMapper extends
 37             Mapper<LongWritable, Text, LongWritable, Text> {
 38 
 39         @Override
 40         protected void setup(Context context) throws IOException,
 41                 InterruptedException {
 42             super.setup(context);
 43         }
 44 
 45         @Override
 46         protected void map(LongWritable key, Text value, Context context)
 47                 throws IOException, InterruptedException {
 48             super.map(key, value, context);
 49         }
 50 
 51         @Override
 52         protected void cleanup(Context context) throws IOException,
 53                 InterruptedException {
 54             super.cleanup(context);
 55         }
 56     }
 57 
 58     /**
 59      * Reducer Class
 60      */
 61     public static class ModuleReducer extends
 62             Reducer<LongWritable, Text, LongWritable, Text> {
 63 
 64         @Override
 65         protected void setup(Context context) throws IOException,
 66                 InterruptedException {
 67             // TODO Auto-generated method stub
 68             super.setup(context);
 69         }
 70 
 71         @Override
 72         protected void reduce(LongWritable key, Iterable<Text> values,
 73                 Context context) throws IOException, InterruptedException {
 74             // TODO Auto-generated method stub
 75             super.reduce(key, values, context);
 76         }
 77 
 78         @Override
 79         protected void cleanup(Context context) throws IOException,
 80                 InterruptedException {
 81             // TODO Auto-generated method stub
 82             super.cleanup(context);
 83         }
 84 
 85     }
 86 
 87     /**
 88      * Driver Class
 89      */
 90 
 91     //    专门抽取一个方法出来用于设置
 92     public Job parseInputAndOutput(Tool tool,Configuration conf,String[] args) throws IOException
 93     {
 94         if (args.length!=2) {
 95             System.err.printf("Usage:%s [generic options] <input> <output>
", tool.getClass().getSimpleName());
 96             ToolRunner.printGenericCommandUsage(System.err);
 97             return null;
 98         }
 99         
100         //创建job，并设置配置信息和job名称
101         Job job=new Job(conf, ModuleMapReduce.class.getSimpleName());
102         
103         //设置job的运行类
104         // step 3：set job
105         // 1) set run jar class
106         job.setJarByClass(tool.getClass());
107         
108         // 14) job output path
109         FileOutputFormat.setOutputPath(job, new Path(args[1]));
110         
111         return job;
112     }
113     
114     @Override
115     public int run(String[] args) throws Exception {
116         
117         // step 1：get conf
118         Configuration conf = new Configuration();
119 
120         // step 2：create job
121         Job job = parseInputAndOutput(this, conf, args);
122 
123 
124         // 2) set input format
125         job.setInputFormatClass(TextInputFormat.class); // 可省
126 
127         // 3) set input path
128         FileInputFormat.addInputPath(job, new Path(args[0]));
129 
130         // 4) set mapper class
131         job.setMapperClass(ModuleMapper.class); // 可省
132 
133         // 5)set map input key/value class
134         job.setMapOutputKeyClass(LongWritable.class); // 可省
135         job.setMapOutputValueClass(Text.class); // 可省
136 
137         // 6) set partitioner class
138         job.setPartitionerClass(HashPartitioner.class); // 可省
139 
140         // 7) set reducer number
141         job.setNumReduceTasks(1);// default 1 //可省
142         
143         // 8)set sort comparator class
144         //job.setSortComparatorClass(LongWritable.Comparator.class); // 可省
145 
146         // 9) set group comparator class
147         //job.setGroupingComparatorClass(LongWritable.Comparator.class); // 可省
148 
149         // 10) set combiner class
150         // job.setCombinerClass(null);默认是null，但是此处不能写 //可省
151 
152         // 11) set reducer class
153         job.setReducerClass(ModuleReducer.class); // 可省
154 
155         // 12) set output format
156         job.setOutputFormatClass(TextOutputFormat.class); // 可省
157 
158         // 13) job output key/value class
159         job.setOutputKeyClass(LongWritable.class); // 可省
160         job.setOutputValueClass(Text.class); // 可省
161 
162 
163         // step 4: submit job
164         boolean isSuccess = job.waitForCompletion(true);
165 
166         // step 5: return status
167         return isSuccess ? 0 : 1;
168     }
169 
170     public static void main(String[] args) throws Exception {
171         
172         args = new String[] {
173                 "hdfs://hadoop-master.dragon.org:9000/wc/mininput/",
174                 "hdfs://hadoop-master.dragon.org:9000/wc/minoutput" 
175                 };
176 
177         //run mapreduce
178         int status=ToolRunner.run(new ModuleMapReduce(), args);
179         
180         //exit
181         System.exit(status);
182     }
183 }

View Module Code

模板使用步骤：

1）改名称（MapReduce类的名称、Mapper类的名称、Reducer类的名称）

2）依据实际的业务逻辑修改Mapper类和Reducer类的Key/Value输入输出参数的类型

3）修改驱动Driver部分的Job的参数设置（Mapper类和Reducer类的输出类型）

4）在Mapper类中编写实际的业务逻辑（setup()、map()、cleanup()）

5）在Reducer类中编写实际的业务逻辑（setup()、map()、cleanup()）

6）检查并修改驱动Driver代码（模板类中的run()方法）

7）设置输入输出路径，进行MR测试。

使用ModuleMapReduce编写wordcount程序

  1 package org.dragon.hadoop.mr.module;
  2 
  3 import java.io.IOException;
  4 import java.util.StringTokenizer;
  5 
  6 import org.apache.hadoop.conf.Configuration;
  7 import org.apache.hadoop.conf.Configured;
  8 import org.apache.hadoop.fs.Path;
  9 import org.apache.hadoop.io.LongWritable;
 10 import org.apache.hadoop.io.Text;
 11 import org.apache.hadoop.mapreduce.Job;
 12 import org.apache.hadoop.mapreduce.Mapper;
 13 import org.apache.hadoop.mapreduce.Reducer;
 14 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
 15 import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
 16 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
 17 import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
 18 import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;
 19 import org.apache.hadoop.util.Tool;
 20 import org.apache.hadoop.util.ToolRunner;
 21 
 22 /**
 23  * 
 24  * ########################################### 
 25  * ############        MapReduce 模板类     ########## 
 26  * ###########################################
 27  * 
 28  * @author ZhuXY
 29  * @time 2016-3-13 下午10:21:06
 30  * 
 31  */
 32 public class WordcountByModuleMapReduce extends Configured implements Tool {
 33 
 34     /**
 35      * Mapper Class
 36      */
 37     public static class WordcountMapper extends
 38             Mapper<LongWritable, Text, Text, LongWritable> {
 39 
 40         @Override
 41         protected void setup(Context context) throws IOException,
 42                 InterruptedException {
 43             super.setup(context);
 44         }
 45 
 46         private Text word = new Text();
 47         private final static LongWritable one = new LongWritable(1);
 48 
 49         @Override
 50         protected void map(LongWritable key, Text value, Context context)
 51                 throws IOException, InterruptedException {
 52 
 53             // 获取每行数据的值
 54             String lineValue = value.toString();
 55 
 56             // 进行分割
 57             StringTokenizer stringTokenizer = new StringTokenizer(lineValue);
 58 
 59             // 遍历
 60             while (stringTokenizer.hasMoreElements()) {
 61 
 62                 // 获取每个值
 63                 String worldValue = stringTokenizer.nextToken();
 64 
 65                 // 设置map, 输入的key值
 66                 word.set(worldValue);
 67                 context.write(word, one); // 如果出现就出现一次，存在每行出现几次，这时候键的值一样，多个键值对
 68             }
 69         }
 70 
 71         @Override
 72         protected void cleanup(Context context) throws IOException,
 73                 InterruptedException {
 74             super.cleanup(context);
 75         }
 76     }
 77 
 78     /**
 79      * Reducer Class
 80      */
 81     public static class WordcountReducer extends
 82             Reducer<Text, LongWritable, Text, LongWritable> {
 83         private LongWritable resultLongWritable = new LongWritable();
 84 
 85         @Override
 86         protected void setup(Context context) throws IOException,
 87                 InterruptedException {
 88             // TODO Auto-generated method stub
 89             super.setup(context);
 90         }
 91 
 92         @Override
 93         protected void reduce(Text key, Iterable<LongWritable> values,
 94                 Context context) throws IOException, InterruptedException {
 95             int sum = 0;
 96             // 循环遍历Interable
 97             for (LongWritable value : values) {
 98                 // 累加
 99                 sum += value.get();
100             }
101 
102             // 设置总次数
103             resultLongWritable.set(sum);
104             context.write(key, resultLongWritable);
105         }
106 
107         @Override
108         protected void cleanup(Context context) throws IOException,
109                 InterruptedException {
110             // TODO Auto-generated method stub
111             super.cleanup(context);
112         }
113 
114     }
115 
116     /**
117      * Driver Class
118      */
119 
120     // 专门抽取一个方法出来用于设置
121     public Job parseInputAndOutput(Tool tool, Configuration conf, String[] args)
122             throws IOException {
123         if (args.length != 2) {
124             System.err.printf("Usage:%s [generic options] <input> <output>
",
125                     tool.getClass().getSimpleName());
126             ToolRunner.printGenericCommandUsage(System.err);
127             return null;
128         }
129 
130         // 创建job，并设置配置信息和job名称
131         Job job = new Job(conf,
132                 WordcountByModuleMapReduce.class.getSimpleName());
133 
134         // 设置job的运行类
135         // step 3：set job
136         // 1) set run jar class
137         job.setJarByClass(tool.getClass());
138 
139         // 14) job output path
140         FileOutputFormat.setOutputPath(job, new Path(args[1]));
141 
142         return job;
143     }
144 
145     @Override
146     public int run(String[] args) throws Exception {
147 
148         // step 1：get conf
149         Configuration conf = new Configuration();
150 
151         // step 2：create job
152         Job job = parseInputAndOutput(this, conf, args);
153 
154         // 2) set input format
155         job.setInputFormatClass(TextInputFormat.class); // 可省
156 
157         // 3) set input path
158         FileInputFormat.addInputPath(job, new Path(args[0]));
159 
160         // 4) set mapper class
161         job.setMapperClass(WordcountMapper.class); // 可省
162 
163         // 5)set map input key/value class
164         job.setMapOutputKeyClass(Text.class); // 可省
165         job.setMapOutputValueClass(LongWritable.class); // 可省
166 
167         // 6) set partitioner class
168         job.setPartitionerClass(HashPartitioner.class); // 可省
169 
170         // 7) set reducer number
171         job.setNumReduceTasks(1);// default 1 //可省
172 
173         // 8)set sort comparator class
174         // job.setSortComparatorClass(LongWritable.Comparator.class); // 可省
175 
176         // 9) set group comparator class
177         // job.setGroupingComparatorClass(LongWritable.Comparator.class); // 可省
178 
179         // 10) set combiner class
180         // job.setCombinerClass(null);默认是null，但是此处不能写 //可省
181 
182         // 11) set reducer class
183         job.setReducerClass(WordcountReducer.class); // 可省
184 
185         // 12) set output format
186         job.setOutputFormatClass(TextOutputFormat.class); // 可省
187 
188         // 13) job output key/value class
189         job.setOutputKeyClass(Text.class); // 可省
190         job.setOutputValueClass(LongWritable.class); // 可省
191 
192         // step 4: submit job
193         boolean isSuccess = job.waitForCompletion(true);
194 
195         // step 5: return status
196         return isSuccess ? 0 : 1;
197     }
198 
199     public static void main(String[] args) throws Exception {
200 
201         args = new String[] {
202                 "hdfs://hadoop-master.dragon.org:9000/wc/mininput/",
203                 "hdfs://hadoop-master.dragon.org:9000/wc/minoutput" };
204 
205         // run mapreduce
206         int status = ToolRunner.run(new WordcountByModuleMapReduce(), args);
207 
208         // exit
209         System.exit(status);
210     }
211 }

View WordcountByModuleMapReduce Code

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原文地址：https://www.cnblogs.com/xiangyangzhu/p/5281129.html