hadoop-分区

hadoop分区的实现

分区的作用：
1. 根据业务需要，产生多个文件输出
2. 多个reduce任务在运行，提高整体job的运行速度。

实现方法：
在驱动类里写个分区内部类，它必须继承HashPartitioner接口，同时实现getPartition方法。

job指定分区类
job.setPartitionerClass(KpiPartitioner.class);
job.setNumReduceTasks(分区数);

分区后需要打包运行而不能在eclipse中运行。

package partition;import java.io.DataInput;import java.io.DataOutput;import java.io.IOException;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.io.Writable;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.input.TextInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;/** * 分区的例子必须打成jar运行 * 用处：  1.根据业务需要，产生多个输出文件 *      2.多个reduce任务在运行，提高整体job的运行效率 */public class KpiApp {    static final String INPUT_PATH = "hdfs://chaoren:9000/wlan";    static final String OUT_PATH = "hdfs://chaoren:9000/out";    public static void main(String[] args) throws Exception{        final Job job = new Job(new Configuration(), KpiApp.class.getSimpleName());        job.setJarByClass(KpiApp.class);        //1.1 指定输入文件路径        FileInputFormat.setInputPaths(job, INPUT_PATH);        //指定哪个类用来格式化输入文件        job.setInputFormatClass(TextInputFormat.class);        //1.2指定自定义的Mapper类        job.setMapperClass(MyMapper.class);        //指定输出<k2,v2>的类型        job.setMapOutputKeyClass(Text.class);        job.setMapOutputValueClass(KpiWritable.class);        //1.3 指定分区类        job.setPartitionerClass(KpiPartitioner.class);        job.setNumReduceTasks(2);        //1.4 TODO 排序、分区        //1.5  TODO （可选）合并        //2.2 指定自定义的reduce类        job.setReducerClass(MyReducer.class);        //指定输出<k3,v3>的类型        job.setOutputKeyClass(Text.class);        job.setOutputValueClass(KpiWritable.class);        //2.3 指定输出到哪里        FileOutputFormat.setOutputPath(job, new Path(OUT_PATH));        //设定输出文件的格式化类        job.setOutputFormatClass(TextOutputFormat.class);        //把代码提交给JobTracker执行        job.waitForCompletion(true);    }    static class MyMapper extends Mapper<LongWritable, Text, Text, KpiWritable>{        protected void map(LongWritable key, Text value, org.apache.hadoop.mapreduce.Mapper<LongWritable,Text,Text,KpiWritable>.Context context) throws IOException ,InterruptedException {            final String[] splited = value.toString().split("\t");            final String msisdn = splited[1];            final Text k2 = new Text(msisdn);            final KpiWritable v2 = new KpiWritable(splited[6],splited[7],splited[8],splited[9]);            context.write(k2, v2);        };    }    static class MyReducer extends Reducer<Text, KpiWritable, Text, KpiWritable>{        /**         * @param   k2  表示整个文件中不同的手机号码           * @param   v2s 表示该手机号在不同时段的流量的集合         */        protected void reduce(Text k2, java.lang.Iterable<KpiWritable> v2s, org.apache.hadoop.mapreduce.Reducer<Text,KpiWritable,Text,KpiWritable>.Context context) throws IOException ,InterruptedException {            long upPackNum = 0L;            long downPackNum = 0L;            long upPayLoad = 0L;            long downPayLoad = 0L;            for (KpiWritable kpiWritable : v2s) {                upPackNum += kpiWritable.upPackNum;                downPackNum += kpiWritable.downPackNum;                upPayLoad += kpiWritable.upPayLoad;                downPayLoad += kpiWritable.downPayLoad;            }            final KpiWritable v3 = new KpiWritable(upPackNum+"", downPackNum+"", upPayLoad+"", downPayLoad+"");            context.write(k2, v3);        };    }    static class KpiPartitioner extends HashPartitioner<Text, KpiWritable>{        @Override        public int getPartition(Text key, KpiWritable value, int numReduceTasks) {            return (key.toString().length()==11)?0:1;        }    }}class KpiWritable implements Writable{    long upPackNum;    long downPackNum;    long upPayLoad;    long downPayLoad;    public KpiWritable(){}    public KpiWritable(String upPackNum, String downPackNum, String upPayLoad, String downPayLoad){        this.upPackNum = Long.parseLong(upPackNum);        this.downPackNum = Long.parseLong(downPackNum);        this.upPayLoad = Long.parseLong(upPayLoad);        this.downPayLoad = Long.parseLong(downPayLoad);    }    @Override    public void readFields(DataInput in) throws IOException {        this.upPackNum = in.readLong();        this.downPackNum = in.readLong();        this.upPayLoad = in.readLong();        this.downPayLoad = in.readLong();    }    @Override    public void write(DataOutput out) throws IOException {        out.writeLong(upPackNum);        out.writeLong(downPackNum);        out.writeLong(upPayLoad);        out.writeLong(downPayLoad);    }    @Override    public String toString() {        return upPackNum + "\t" + downPackNum + "\t" + upPayLoad + "\t" + downPayLoad;    }}