MR案例之自定义分区

FlowSumArea.java

package com.matrix.areapartition;

import java.io.IOException;

import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
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;

import com.matrix.flowsum.FlowBean;

/**
 * 对流量原始日志进行分析，将不同省份的用户统计分析到不同文件
 *
 *
 *
 * FlowSumArea<BR>
 * 创建人:Matrix <BR>
 * 时间：2016年3月11日-上午8:10:02 <BR>
 *
 * @version 1.0.0
 *
 */
public class FlowSumArea {

    // 需要自定义改造两个机制：

    // 1、改造分区逻辑partitioner，自定义一个partitioner
    // 2、自定义reducer task的并发任务数

    // Mapper
    public static class FlowMapper extends Mapper<LongWritable, Text, Text, FlowBean> {

        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {

            String line = value.toString();

            String[] fields = StringUtils.split(line, "\t");

            String phoneNB = fields[1];
            Long up_flow = Long.parseLong(fields[7]);
            Long d_flow = Long.parseLong(fields[8]);

            context.write(new Text(phoneNB), new FlowBean(phoneNB, up_flow, d_flow));

        }

    }

    // Reducer
    public static class FlowSumReducer extends Reducer<Text, FlowBean, Text, FlowBean> {

        @Override
        protected void reduce(Text key, Iterable<FlowBean> values, Context context)
                throws IOException, InterruptedException {

            // 定义上行流量计数器
            long up_flow_counter = 0;

            // 定义上行流量计数器
            long d_flow_counter = 0;

            for (FlowBean value : values) {
                // 叠加相同手机号的上行流量
                up_flow_counter += value.getUp_flow();
                // 叠加相同手机号的下行流量
                d_flow_counter += value.getD_flow();
            }

            context.write(key, new FlowBean(key.toString(), up_flow_counter, d_flow_counter));
        }

    }

    public static void main(String[] args) throws Exception {

        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://node1:8020");

        FileSystem fs = FileSystem.get(conf);

        Job job = Job.getInstance(conf);
        job.setJarByClass(FlowSumArea.class);

        job.setMapperClass(FlowMapper.class);
        job.setReducerClass(FlowSumReducer.class);

        // 设定自定义的分组
        job.setPartitionerClass(AreaPartitioner.class);

        // job.setMapOutputKeyClass(Text.class);
        // job.setMapOutputValueClass(FlowBean.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(FlowBean.class);

        // 设定reduce的任务并发数，跟分组的数量保持一致，只能分多不能分少
        /**
         * 设置reduce task数量要跟AreaPartitioner返回的partition个数匹配 reduce task或map
         * task指的是，reducer和mapper在集群中运行的实例，在进程中都叫yarn-child
         */
        job.setNumReduceTasks(7);

        // job.setInputFormatClass(TextInputFormat.class);
        // job.setOutputFormatClass(TextOutputFormat.class);

        FileInputFormat.addInputPaths(job, "/usr/matrix/input/flowsum.dat");

        Path outer = new Path("/usr/matrix/output/flowsumarea");

        if (fs.exists(outer)) {
            fs.delete(outer, true);
        }

        FileOutputFormat.setOutputPath(job, outer);

        boolean f = job.waitForCompletion(true);

        if (f) {
            System.out.println("程序运行成功！");
        }

    }
}

AreaPartitioner.java

package com.matrix.areapartition;

import java.util.HashMap;

import org.apache.hadoop.mapreduce.Partitioner;

/**
 * 自定义分区类
 *
 * AreaPartitioner<BR>
 * 创建人:Matrix <BR>
 * 时间：2016年3月12日-下午4:43:29 <BR>
 *
 * @version 1.0.0
 *
 */
public class AreaPartitioner<Key, Value> extends Partitioner<Key, Value> {

    private static HashMap<String, Integer> areaMap = new HashMap();

    // 数据字典
    static {
        areaMap.put("134", 0);
        areaMap.put("135", 1);
        areaMap.put("136", 2);
        areaMap.put("137", 3);
        areaMap.put("138", 4);
        areaMap.put("139", 5);

    }

    @Override
    public int getPartition(Key key, Value value, int numPartitioner) {

        // 从key中拿手机号，查询手机归属字典，不同省份返回不同的组号
        int areaCoder = areaMap.get(key.toString().substring(0, 3)) == null ? 6
                : areaMap.get(key.toString().substring(0, 3));

        return areaCoder;
    }

}

运行结果：