hadoop案例：partition分区

淡淡的烟草味﹌ 2022-11-21 15:14 191阅读 0赞

### 文章目录 ###

*   *  输入数据
     *  期望结果
     *  需求分析
     *   *  自定义PhoneFlowBean
     *  自定义MyPartitioner
     *  Mapper类
     *  Reducer类
     *  Driver类
     *  执行结果

## 输入数据 ##

1	13736230513	192.196.100.1	www.hadoop.com	2481	24681	200
    2	13846544121	192.196.100.2			264	0	200
    3 	13956435636	192.196.100.3			132	1512	200
    4 	13966251146	192.168.100.1			240	0	404
    5 	18271575951	192.168.100.2	www.hadoop.com	1527	2106	200
    6 	84188413	192.168.100.3	www.hadoop.com	4116	1432	200
    7 	13590439668	192.168.100.4			1116	954	200
    8 	15910133277	192.168.100.5	www.hao123.com	3156	2936	200
    9 	13729199489	192.168.100.6			240	0	200
    10 	13630577991	192.168.100.7	www.shouhu.com	6960	690	200
    11 	15043685818	192.168.100.8	www.baidu.com	3659	3538	200
    12 	15959002129	192.168.100.9	www.hadoop.com	1938	180	500
    13 	13560439638	192.168.100.10			918	4938	200
    14 	13470253144	192.168.100.11			180	180	200
    15 	13682846555	192.168.100.12	www.qq.com	1938	2910	200
    16 	13992314666	192.168.100.13	www.gaga.com	3008	3720	200
    17 	13509468723	192.168.100.14	www.qinghua.com	7335	110349	404
    18 	18390173782	192.168.100.15	www.sogou.com	9531	2412	200
    19 	13975057813	192.168.100.16	www.baidu.com	11058	48243	200
    20 	13768778790	192.168.100.17			120	120	200
    21 	13568436656	192.168.100.18	www.alibaba.com	2481	24681	200
    22 	13568436656	192.168.100.19			1116	954	200

## 期望结果 ##

期望输出数据  
手机号136、137、138、139开头都分别放到一个独立的4个文件中，其他开头的放到一个文件中。

## 需求分析 ##

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQzNjc0MzYw_size_16_color_FFFFFF_t_70_pic_center]

### 自定义PhoneFlowBean ###

package com.mr.mypartition;
    
    import org.apache.hadoop.io.Writable;
    
    import java.io.DataInput;
    import java.io.DataOutput;
    import java.io.IOException;
    
    
    public class PhoneFlowBean implements Writable { 
    
        // 上传流量
        private long upFlow;
        // 下载流量
        private long downFlow;
        // 总流量 = 上传流量+下载流量
        private long sumFlow;
    
        public PhoneFlowBean() { 
        }
    
        public PhoneFlowBean(long upFlow, long downFlow) { 
            this.upFlow = upFlow;
            this.downFlow = downFlow;
            this.sumFlow = upFlow + downFlow;
        }
    
    
        public void write(DataOutput out) throws IOException { 
            out.writeLong(upFlow);
            out.writeLong(downFlow);
            out.writeLong(sumFlow);
        }
    
    
        public void readFields(DataInput in) throws IOException { 
            this.upFlow = in.readLong();
            this.downFlow = in.readLong();
            this.sumFlow = in.readLong();
        }
    
        @Override
        public String toString() { 
            return upFlow +
                    "\t" + downFlow +
                    "\t" + sumFlow;
        }
    
        public void setUpFlow(long upFlow) { 
            this.upFlow = upFlow;
        }
    
        public void setDownFlow(long downFlow) { 
            this.downFlow = downFlow;
        }
    
        public void setSumFlow(long sumFlow) { 
            this.sumFlow = sumFlow;
        }
    
        public long getUpFlow() { 
            return upFlow;
        }
    
        public long getDownFlow() { 
            return downFlow;
        }
    
        public long getSumFlow() { 
            return sumFlow;
        }
    }

## 自定义MyPartitioner ##

package com.mr.mypartition;
    
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Partitioner;
    
    
    public class MyPartitioner extends Partitioner<Text, PhoneFlowBean> { 
    
    
        // 根据手机号的前三位返回不同的分区号
        @Override
        public int getPartition(Text text, PhoneFlowBean phoneFlowBean, int numPartitions) { 
            String substring = text.toString().substring(0, 3);
            if ("136".equals(substring)) { 
                return 0;
            } else if ("137".equals(substring)) { 
                return 1;
            } else if ("138".equals(substring)) { 
                return 2;
            } else if ("139".equals(substring)) { 
                return 3;
            } else { 
                return 4;
            }
    
        }
    }

## Mapper类 ##

package com.mr.mypartition;
    
    import org.apache.hadoop.io.LongWritable;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Mapper;
    
    import java.io.IOException;
    
    
    public class PhoneFlowMapper extends Mapper<LongWritable, Text, Text, PhoneFlowBean> { 
    
    // 4. 定义对象，防止每次执行map方法重复创建对象
        Text phoneNumberText = new Text();
        PhoneFlowBean phoneFlowBean = new PhoneFlowBean();
    
        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { 
            // 1. 读取每行文本数据，按照分隔符进行切割
            String string = value.toString();
            String[] split = string.split("\t");
    
            // 2. 抽取手机号，上行和下行流量
            String phoneNumber = split[1];
            String upFlow = split[split.length - 3];
            String downFlow = split[split.length - 2];
    
    // 3. 组装 flowBean对象
            phoneFlowBean.setUpFlow(Long.parseLong(upFlow));
            phoneFlowBean.setDownFlow(Long.parseLong(downFlow));
    // flowBean.setSumFlow(Long.parseLong(upFlow)+Long.parseLong(downFlow));
    
            phoneNumberText.set(phoneNumber);
    // FlowBean flowBean = new FlowBean(Long.parseLong(upFlow), Long.parseLong(downFlow));
    // 5. 往reducer写出手机号，flowBean对象
            context.write(phoneNumberText, phoneFlowBean);
    
        }
    }

## Reducer类 ##

package com.mr.mypartition;
    
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Reducer;
    
    import java.io.IOException;
    
    
    public class PhoneFlowReducer extends Reducer<Text, PhoneFlowBean, Text, PhoneFlowBean> { 
    
    // 4. 将创建FlowBean对象的方法提取出来
        PhoneFlowBean phoneFlowBean = new PhoneFlowBean();
    
        @Override
        protected void reduce(Text key, Iterable<PhoneFlowBean> values, Context context) throws IOException, InterruptedException { 
    // 1. 定义上行总流量和下行总流量
            long upTotal = 0;
            long downTotal = 0;
    
    // 2. 迭代 values（封装的是一个个FlowBean对象，根据手机号来分组）
            for (PhoneFlowBean value : values) { 
                upTotal += value.getUpFlow();
                downTotal += value.getDownFlow();
    
            }
    // 3. 继续封装FlowBean 对象
            phoneFlowBean.setUpFlow(upTotal);
            phoneFlowBean.setDownFlow(downTotal);
            phoneFlowBean.setSumFlow(upTotal + downTotal);
    // 5. 输出结果
            context.write(key, phoneFlowBean);
    
    
        }
    }

## Driver类 ##

package com.mr.mypartition;
    
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.mapreduce.Job;
    import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
    import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
    
    import java.io.IOException;
    
    
    public class PhoneFlowDriver { 
        public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException { 
            // 0 指定路径
            args = new String[]{ "E:\\Hadoop\\src\\main\\resources\\input\\iphone", "E:\\Hadoop\\src\\main\\resources\\mypart"};
    
    // 1 获取配置信息configuration以及封装任务job
            Configuration configuration = new Configuration();
            Job job = Job.getInstance(configuration);
    
    // 2 设置Driver加载路径 setJarByClass
            job.setJarByClass(PhoneFlowDriver.class);
    
    // 3 设置map和reduce类 setMaper setReducer
            job.setMapperClass(PhoneFlowMapper.class);
            job.setReducerClass(PhoneFlowReducer.class);
    
    // 4 设置map输出 setmapoutputkey setmapoutputvalue
            job.setMapOutputKeyClass(Text.class);
            job.setMapOutputValueClass(PhoneFlowBean.class);
    
    // 5 设置最终输出kv类型 (reducer的输出kv类型) setoutoutkey setoutputvalue
            job.setOutputKeyClass(Text.class);
            job.setOutputValueClass(PhoneFlowBean.class);
    
    // 设置自定义的分区器
            job.setPartitionerClass(MyPartitioner.class);
    // 设置reduceTask 的个数，影响最终的文件个数
            job.setNumReduceTasks(5);
    
    // 6 设置本地的输入和输出路径 fileinputformat.setinputpath
            FileInputFormat.setInputPaths(job, new Path(args[0]));
            FileOutputFormat.setOutputPath(job, new Path(args[1]));
    // 7 提交
            boolean completion = job.waitForCompletion(true);
            System.exit(completion ? 0 : 1);
    
        }
    }

## 执行结果 ##

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQzNjc0MzYw_size_16_color_FFFFFF_t_70_pic_center 1]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQzNjc0MzYw_size_16_color_FFFFFF_t_70_pic_center]: /images/20221120/f598f489aeb048d8a0a888646d497960.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQzNjc0MzYw_size_16_color_FFFFFF_t_70_pic_center 1]: /images/20221120/eca0137edf614b4b9ddbf0c2b646534f.png