MR案例：基站相关01

字段解释： product_no：用户手机号； lac_id：用户所在基站； start_time：用户在此基站的开始时间； staytime：用户在此基站的逗留时间。

product_no lac_id moment start_time user_id county_id staytime city_id

   -- ::19.151754088

   -- ::20.152622488

   -- ::37.149593624

   -- ::51.139539816

   -- ::45.150276800

   -- ::38.140225200

   -- ::19.151754088

   -- ::32.151754088

   -- ::24.139539816

   -- ::30.152622440    

需求描述：  根据 lac_id 和 start_time 知道用户当时的位置，根据 staytime 知道用户各个基站的逗留时长。根据轨迹合并连续基站的 staytime。最终得到每一个用户按时间排序在每一个基站驻留时长。
期望输出：

   -- ::20.152622488

   -- ::37.149593624

   -- ::38.140225200

   -- ::51.139539816

   -- ::45.150276800    

问题分析：针对每个product_no按照start_time进行排序(本例降序)，如果相邻两项的lac_id相同，则将staytime进行相加保存到后一项中，并将前一项移除。

完整代码v1：此版本只启用了Map阶段。map()函数：将每行内容解析成自定义的RecordWritable对象并添加到List集合中，然后对List集合进行排序。clearup()函数：将product_no和lac_id相同的相邻两项中的staytime进行相加。

缺点：将全部数据添加到List集合，对于大数据量无法满足要求。

package demo0902;

import java.io.DataInput;

import java.io.DataOutput;

import java.io.IOException;

import java.util.ArrayList;

import java.util.Collections;

import java.util.Comparator;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.io.WritableComparable;

import org.apache.hadoop.mapreduce.Job;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class Demo090203 {

    final static String INPUT_PATH = "hdfs://10.16.17.182:9000/test/in/0902/";

    final static String OUT_PATH = "hdfs://10.16.17.182:9000/test/out/0902/06";

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

        Configuration configuration = new Configuration();

        Job job = Job.getInstance(configuration);

        job.setJarByClass(Demo090203.class);

        //指定map
        job.setMapperClass(Demo090201Mapper.class);

        job.setMapOutputKeyClass(RecordWritable.class);

        job.setMapOutputValueClass(NullWritable.class);

        job.setOutputKeyClass(RecordWritable.class);

        job.setOutputValueClass(NullWritable.class);

        FileInputFormat.setInputPaths(job, new Path(INPUT_PATH));

        FileOutputFormat.setOutputPath(job, new Path(OUT_PATH));

        job.waitForCompletion(true);

    }

    //map

    public static class Demo090201Mapper extends Mapper<LongWritable, Text, RecordWritable, NullWritable>{

        //存储一条记录

        ArrayList<RecordWritable> list = new ArrayList<RecordWritable>();

        @Override

        protected void map(LongWritable key, Text value, Context context)

                throws IOException, InterruptedException {

            String[] splited = value.toString().split("\t");

            //将一行内容组装成一条记录

            RecordWritable record = new RecordWritable();

            record.product_no=splited[0];

            record.lac_id=splited[1];

            record.moment=Integer.parseInt(splited[2]);

            record.start_time=splited[3];

            record.user_id=splited[4];

            record.county_id=splited[5];

            record.staytime=Integer.parseInt(splited[6]);

            record.city_id=splited[7];

            list.add(record);

            //对List中数据进行排序(自定义比较器)

            Collections.sort(list, new Comparator<RecordWritable>() {

                @Override

                public int compare(RecordWritable r1, RecordWritable r2) {

                    //调用RecordWritable的compareTo()方法

                    return (r1.compareTo(r2));

                }

            });

        }

        @Override

        protected void cleanup(Context context)

                throws IOException, InterruptedException {

            for(RecordWritable r : list){

                System.out.println(r.toString());

            }

            for(int i=0; i<list.size() ;i++){

                if(i != list.size()-1){

                    //取出相邻的两个RecordWritable

                    RecordWritable record_pre = list.get(i);

                    RecordWritable record_next = list.get(i+1);

                    //只有手机号和基站号都相等的情况下,才将 staytime 相加

                    if(record_pre.product_no.equals(record_next.product_no) && record_pre.lac_id.equals(record_next.lac_id)){

                        //将相加后的staytime赋予后一条记录

                        record_next.staytime += record_pre.staytime;

                        //移除前一条记录

                        list.remove(record_pre);

                    }

                }

            }

            for(RecordWritable record : list){

                context.write(record, NullWritable.get());

            }

        }

    }

    //自定义的序列化类

    public static class RecordWritable implements WritableComparable<RecordWritable>{

        String product_no;

        String lac_id;

        int moment;

        String start_time;

        String user_id;

        String county_id;

        int staytime;

        String city_id;

        @Override

        public int compareTo(RecordWritable o) {

            // 先按手机号排序 Asc

            int value = this.product_no.compareTo(o.product_no);

            if(value==0)

                // 再按时间进行排序 Desc

                return o.start_time.compareTo(this.start_time);

            return value;

        }

        @Override

        public void write(DataOutput out) throws IOException {

            out.writeUTF(product_no);

            out.writeUTF(lac_id);

            out.writeInt(moment);

            out.writeUTF(start_time);

            out.writeUTF(user_id);

            out.writeUTF(county_id);

            out.writeInt(staytime);

            out.writeUTF(city_id);

        }

        @Override

        public void readFields(DataInput in) throws IOException {

            product_no=in.readUTF();

            lac_id=in.readUTF();

            moment=in.readInt();

            start_time=in.readUTF();

            user_id=in.readUTF();

            county_id=in.readUTF();

            staytime=in.readInt();

            city_id=in.readUTF();

        }

        @Override

        public String toString() {

            return this.product_no+" "+this.lac_id+" "+this.moment+" "+this.start_time+" "+user_id+" "+county_id+" "+ staytime+" "+city_id;

        }

    }

}

完整代码v2：此版本Map阶段以product_no为key，每行内容为value进行输出。Reduce阶段和上一个版本的Map阶段功能类似。

优点：相比于v1，此版本优化在于每次只处理一个product_no相关的数据，减缓数据量带来的压力。

package demo0902;

import java.io.DataInput;

import java.io.DataOutput;

import java.io.IOException;

import java.util.ArrayList;

import java.util.Collections;

import java.util.Comparator;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.io.WritableComparable;

import org.apache.hadoop.mapreduce.Job;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.hadoop.mapreduce.Reducer;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class Demo090204 {

    final static String INPUT_PATH = "hdfs://10.16.17.182:9000/test/in/0902/";

    final static String OUT_PATH = "hdfs://10.16.17.182:9000/test/out/0902/02";

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

        Configuration configuration = new Configuration();

        Job job = Job.getInstance(configuration);

        job.setJarByClass(Demo090203.class);

        job.setMapperClass(Demo090201Mapper.class);

        job.setReducerClass(Demo090201Reducer.class);

        job.setMapOutputKeyClass(Text.class);

        job.setMapOutputValueClass(Text.class);

        job.setOutputKeyClass(RecordWritable.class);

        job.setOutputValueClass(NullWritable.class);

        FileInputFormat.setInputPaths(job, new Path(INPUT_PATH));

        FileOutputFormat.setOutputPath(job, new Path(OUT_PATH));

        job.waitForCompletion(true);

    }

    //map

    public static class Demo090201Mapper extends Mapper<LongWritable, Text, Text, Text>{

        @Override

        protected void map(LongWritable key, Text value, Context context)

                throws IOException, InterruptedException {

            String[] splited = value.toString().split("\t");

            context.write(new Text(splited[0]), new Text(value));

        }

    }

    //reduce

    public static class Demo090201Reducer extends Reducer<Text, Text, RecordWritable, NullWritable>{

        @Override

        protected void reduce(Text key, Iterable<Text> v2s, Context context)

                throws IOException, InterruptedException {

            ArrayList<RecordWritable> list = new ArrayList<RecordWritable>();

            for(Text text : v2s){

                String[] splited = text.toString().split("\t");

                RecordWritable record = new RecordWritable();

                record.product_no=splited[0];

                record.lac_id=splited[1];

                record.moment=Integer.parseInt(splited[2]);

                record.start_time=splited[3];

                record.user_id=splited[4];

                record.county_id=splited[5];

                record.staytime=Integer.parseInt(splited[6]);

                record.city_id=splited[7];

                list.add(record);

            }

            //对List中数据进行排序(自定义比较器)

            Collections.sort(list, new Comparator<RecordWritable>() {

                @Override

                public int compare(RecordWritable r1, RecordWritable r2) {

                    //调用RecordWritable的compareTo()方法

                    return (r1.compareTo(r2));

                }

            });

            for(int i=0; i<list.size() ;i++){

                //滤过最后一条记录

                if(i != list.size()-1){

                    //取出相邻的两个RecordWritable

                    RecordWritable record_pre = list.get(i);

                    RecordWritable record_next = list.get(i+1);

                    if(record_pre.lac_id.equals(record_next.lac_id)){

                        //将相加后的staytime赋予后一条记录

                        record_next.staytime += record_pre.staytime;

                        //移除前一条记录

                        list.remove(record_pre);

                    }

                }

            }

            for(RecordWritable record : list){

                context.write(record, NullWritable.get());

            }

        }

    }

    //自定义的序列化类

    public static class RecordWritable implements WritableComparable<RecordWritable>{

        String product_no;

        String lac_id;

        int moment;

        String start_time;

        String user_id;

        String county_id;

        int staytime;

        String city_id;

        @Override

        public int compareTo(RecordWritable o) {

            // 先按手机号排序 Asc

            int value = this.product_no.compareTo(o.product_no);

            if(value==0)

                // 再按时间进行排序 Desc

                return o.start_time.compareTo(this.start_time);

            return value;

        }

        @Override

        public void write(DataOutput out) throws IOException {

            out.writeUTF(product_no);

            out.writeUTF(lac_id);

            out.writeInt(moment);

            out.writeUTF(start_time);

            out.writeUTF(user_id);

            out.writeUTF(county_id);

            out.writeInt(staytime);

            out.writeUTF(city_id);

        }

        @Override

        public void readFields(DataInput in) throws IOException {

            product_no=in.readUTF();

            lac_id=in.readUTF();

            moment=in.readInt();

            start_time=in.readUTF();

            user_id=in.readUTF();

            county_id=in.readUTF();

            staytime=in.readInt();

            city_id=in.readUTF();

        }

        @Override

        public String toString() {

            return this.product_no+" "+this.lac_id+" "+this.moment+" "+this.start_time+" "+user_id+" "+county_id+" "+ staytime+" "+city_id;

        }

    }

}