大数据-经典案例上行流量倒序排序（递减排序）

需求二: 上行流量倒序排序（递减排序）

分析，以需求一的输出数据作为排序的输入数据，自定义FlowBean,以FlowBean为map输 出的key，以手机号作为Map输出的value，因为MapReduce程序会对Map阶段输出的key 进行排序

Step 1: 定义FlowBean实现WritableComparable实现比较排序

Java 的 compareTo 方法说明:

• compareTo 方法用于将当前对象与方法的参数进行比较。
• 如果指定的数与参数相等返回 0。
• 如果指定的数小于参数返回 -1。
• 如果指定的数大于参数返回 1。

例如： o1.compareTo(o2); 返回正数的话，当前对象（调用 compareTo 方法的对象 o1） 要排在比较对象（compareTo 传参对象 o2）后面，返回负数的话，放在前面

public class FlowBean implements WritableComparable {
    private Integer upFlow;
    private Integer downFlow;
    private Integer upCountFlow;
    private Integer downCountFlow;

    public FlowBean() {
    }

    public FlowBean(Integer upFlow, Integer downFlow, Integer upCountFlow, Integer downCountFlow) {
        this.upFlow = upFlow;
        this.downFlow = downFlow;
        this.upCountFlow = upCountFlow;
        this.downCountFlow = downCountFlow;
    }

    @Override
    public void write(DataOutput out) throws IOException {
        out.writeInt(upFlow);
        out.writeInt(downFlow);
        out.writeInt(upCountFlow);
        out.writeInt(downCountFlow);
    }

    @Override
    public void readFields(DataInput in) throws IOException {
        upFlow = in.readInt();
        downFlow = in.readInt();
        upCountFlow = in.readInt();
        downCountFlow = in.readInt();
    }

    public Integer getUpFlow() {
        return upFlow;
    }

    public void setUpFlow(Integer upFlow) {
        this.upFlow = upFlow;
    }

    public Integer getDownFlow() {
        return downFlow;
    }

    public void setDownFlow(Integer downFlow) {
        this.downFlow = downFlow;
    }

    public Integer getUpCountFlow() {
        return upCountFlow;
    }

    public void setUpCountFlow(Integer upCountFlow) {
        this.upCountFlow = upCountFlow;
    }

    public Integer getDownCountFlow() {
        return downCountFlow;
    }

    public void setDownCountFlow(Integer downCountFlow) {
        this.downCountFlow = downCountFlow;
    }

    @Override
    public String toString() {
        return upFlow + "\t" + downFlow + "\t" + upCountFlow + "\t" + downCountFlow;
    }

    @Override
    public int compareTo(FlowBean o) {
        return this.upCountFlow > o.upCountFlow ?-1:1;
    }
}

Step 2: 定义FlowMapper

public class FlowCountSortMapper extends Mapper<LongWritable, Text, FlowBean, Text> {
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        FlowBean flowBean = new FlowBean();
        String[] split = value.toString().split("\t");
        //获取手机号，作为V2 .
        String phoneNum = split[0];
        //获取其他流量字段,封装flowBean，作为K2 
        flowBean.setUpFlow(Integer.parseInt(split[1]));
        flowBean.setDownFlow(Integer.parseInt(split[2]));
        flowBean.setUpCountFlow(Integer.parseInt(split[3]));
        flowBean.setDownCountFlow(Integer.parseInt(split[4]));
        //将K2和V2写入上下文中 
        context.write(flowBean, new Text(phoneNum));
    }
}

Step 3: 定义FlowReducer

public class FlowCountSortReducer extends Reducer<FlowBean, Text, Text, FlowBean> {
    @Override
    protected void reduce(FlowBean key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
        for (Text value : values) {
            context.write(value, key);
        }
    }
}

Step 4: 程序main函数入口

public class JobMain extends Configured implements Tool {
    @Override
    public int run(String[] strings) throws Exception {
        //创建一个任务对象
        Job job = Job.getInstance(super.getConf(), "mapreduce_flowcountsort");
        //打包放在集群运行时，需要做一个配置
        job.setJarByClass(JobMain.class);
        //第一步:设置读取文件的类: K1 和V1
        job.setInputFormatClass(TextInputFormat.class);
        TextInputFormat.addInputPath(job, new Path("hdfs://node01:8020/out/flowcount_out"));
        //第二步：设置Mapper类
        job.setMapperClass(FlowCountSortMapper.class);
        //设置Map阶段的输出类型: k2 和V2的类型
        job.setMapOutputKeyClass(FlowBean.class);
        job.setMapOutputValueClass(Text.class);
        //第三,四，五，六步采用默认方式(分区，排序，规约，分组)
        // 第七步 ：设置文的Reducer类
        job.setReducerClass(FlowCountSortReducer.class);
        //设置Reduce阶段的输出类型
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(FlowBean.class);
        //设置Reduce的个数
        // 第八步:设置输出类
        job.setOutputFormatClass(TextOutputFormat.class);
        //设置输出的路径
        TextOutputFormat.setOutputPath(job, new Path("hdfs://node01:8020/out/flowcountsort_out"));
        boolean b = job.waitForCompletion(true);
        return b ? 0 : 1;
    }

    public static void main(String[] args) throws Exception {
        Configuration configuration = new Configuration();
        //启动一个任务 
        int run = ToolRunner.run(configuration, new JobMain(), args);
        System.exit(run);
    }
}