MapReduce2-3.1.1 分布式計(jì)算 實(shí)驗(yàn)示例 (三)二次排序

大家好,我是Iggi。

今天我給大家分享的是MapReduce2-3.1.1版本的SecondarySort實(shí)驗(yàn)。

關(guān)于MapReduce的一段文字簡(jiǎn)介請(qǐng)自行查閱我的實(shí)驗(yàn)示例:MapReduce2-3.1.1 實(shí)驗(yàn)示例 單詞計(jì)數(shù)(一)

好,下面進(jìn)入正題。介紹Java操作MapReduce2組件完成SecondarySort的操作。

首先,使用IDE建立Maven工程,建立工程時(shí)沒(méi)有特殊說(shuō)明,按照向?qū)崾军c(diǎn)擊完成即可。重要的是在pom.xml文件中添加依賴(lài)包,內(nèi)容如下圖:

image.png

待系統(tǒng)下載好依賴(lài)的jar包后便可以編寫(xiě)程序了。

展示實(shí)驗(yàn)代碼:

package linose.mapreduce.secondarysort;

import java.io.IOException;
import java.io.OutputStreamWriter;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocatedFileStatus;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.RemoteIterator;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.log4j.BasicConfigurator;

import linose.mapreduce.secondarysort.SecondarySort.FirstPartitioner;
import linose.mapreduce.secondarysort.SecondarySort.KeyComparator;
import linose.mapreduce.secondarysort.SecondarySort.SortMapper;
import linose.mapreduce.secondarysort.SecondarySort.SortReduce;

public class AppSort 
{

    public static void main( String[] args ) throws IOException, ClassNotFoundException, InterruptedException
    {
        /**
         * 設(shè)定MapReduce示例擁有HDFS的操作權(quán)限
         */
        System.setProperty("HADOOP_USER_NAME", "hdfs"); 
        
        /**
         * 為了清楚的看到輸出結(jié)果,暫將集群調(diào)試信息缺省。
         * 如果想查閱集群調(diào)試信息,取消注釋即可。
         */
        BasicConfigurator.configure();
        
        /**
         * MapReude實(shí)驗(yàn)準(zhǔn)備階段:
         * 定義HDFS文件路徑
         */
        String defaultFS = "hdfs://master2.linose.cloud.beijing.com:8020";
        String inputPath = defaultFS + "/index.dirs/inputsort.txt";
        String outputPath = defaultFS + "/index.dirs/sort";
        
        /**
         * 生產(chǎn)配置,并獲取HDFS對(duì)象
         */
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", defaultFS);
        FileSystem system = FileSystem.get(conf);
        
        /**
         * 定義輸入路徑,輸出路徑
         */
        Path inputHdfsPath = new Path(inputPath);
        Path outputHdfsPath = new Path(outputPath);
        
        /**
         * 如果實(shí)驗(yàn)數(shù)據(jù)文件不存在則創(chuàng)建數(shù)據(jù)文件
         */
        system.delete(inputHdfsPath, false);
        if (!system.exists(inputHdfsPath)) {
            FSDataOutputStream outputStream = system.create(inputHdfsPath);
            OutputStreamWriter file = new OutputStreamWriter(outputStream);
            file.write("5\t35\tlee\n");
            file.write("11\t21\tAndy\n");
            file.write("8\t25\tDa\n");
            file.write("4\t23\tCoCo\n");
            file.write("9\t21\tAnn\n");
            file.write("2\t34\tchap\n");
            file.write("10\t45\tYee\n");
            file.write("6\t25\tViVi\n");
            file.write("1\t33\tIggi\n");
            file.write("3\t27\ttony\n");
            file.write("7\t29\tsummer\n");
            file.close();
            outputStream.close();
        }
        
        /**
         * 如果實(shí)驗(yàn)結(jié)果目錄存在,遍歷文件內(nèi)容全部刪除
         */
        if (system.exists(outputHdfsPath)) {
            RemoteIterator<LocatedFileStatus> fsIterator = system.listFiles(outputHdfsPath, true);
            LocatedFileStatus fileStatus;
            while (fsIterator.hasNext()) {
                fileStatus = fsIterator.next();
                system.delete(fileStatus.getPath(), false);
            }
            system.delete(outputHdfsPath, false);
        }
        
        /**
         * 創(chuàng)建MapReduce任務(wù)并設(shè)定Job名稱(chēng)
         */
        Job job = Job.getInstance(conf, "Secondary Sort");
        job.setJarByClass(SecondarySort.class);
        
        /**
         * 設(shè)置輸入文件、輸出文件
         */
        FileInputFormat.addInputPath(job, inputHdfsPath);
        FileOutputFormat.setOutputPath(job, outputHdfsPath);
        
        /**
         * 指定Reduce類(lèi)輸出類(lèi)型Key類(lèi)型與Value類(lèi)型
         */
        job.setOutputKeyClass(IntPair.class);
        job.setOutputValueClass(NullWritable.class);
        
        /**
         * 指定自定義Map類(lèi),Reduce類(lèi),Partitioner類(lèi)、SortComparator類(lèi)。
         */
        job.setMapperClass(SortMapper.class);
        job.setReducerClass(SortReduce.class);
        job.setPartitionerClass(FirstPartitioner.class);
        job.setSortComparatorClass(KeyComparator.class);
        
        /**
         * 設(shè)定Reduce數(shù)量并執(zhí)行
         */
        job.setNumReduceTasks(1);
        job.waitForCompletion(true);
        
        /**
         * 然后輪詢(xún)進(jìn)度,直到作業(yè)完成。
         */
        float progress = 0.0f;
        do {
            progress = job.setupProgress();
            System.out.println("Secondary Sort: 的當(dāng)前進(jìn)度:" + progress * 100);
            Thread.sleep(1000);
        } while (progress != 1.0f && !job.isComplete());
        
        /**
         * 如果成功,查看輸出文件內(nèi)容
         */
        if (job.isSuccessful()) {
            RemoteIterator<LocatedFileStatus> fsIterator = system.listFiles(outputHdfsPath, true);
            LocatedFileStatus fileStatus;
            while (fsIterator.hasNext()) {
                fileStatus = fsIterator.next();
                FSDataInputStream outputStream = system.open(fileStatus.getPath());
                IOUtils.copyBytes(outputStream, System.out, conf, false);
                outputStream.close();
                System.out.println("--------------------------------------------");
            }
        }
    }
}

展示MapReduce2-3.1.1組件編寫(xiě)IntPair測(cè)試類(lèi):

package linose.mapreduce.secondarysort;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.WritableComparable;

public class IntPair implements WritableComparable<IntPair>{

    private IntWritable first;
    private IntWritable second;
    
    public void set(IntWritable first, IntWritable second) {
        this.first = first;
        this.second = second;
    }
    
    public IntPair() {
        set(new IntWritable(), new IntWritable());
    }
    
    public IntPair(int first, int second) {
        set(new IntWritable(first), new IntWritable(second));
    }
    
    public void setFirst(IntWritable first) {
        this.first = first;
    }
    
    public IntWritable getFirst() {
        return first;
    }
    
    public void setSecond(IntWritable second) {
        this.second = second;
    }
    
    public IntWritable getSecond() {
        return second;
    }
    
    public void readFields(DataInput in) throws IOException {
        first.readFields(in);
        second.readFields(in);
    }

    public void write(DataOutput out) throws IOException {
        first.write(out);
        second.write(out);
    }

    public int compareTo(IntPair o) {
        int compare = first.compareTo(o.first);
        if (0 != compare) {
            return compare;
        }
        return second.compareTo(o.second);
    }
    
    public int hashCode() {
        return first.hashCode()*163+second.hashCode();
    }
    
    public boolean equals(Object o) {
        if (o instanceof IntPair) {
            IntPair pair = (IntPair)o;
            return first.equals(pair.first) && second.equals(pair.second);
        }
        return false;
    }

    public String toString() {
        return first + "\t" + second;
    }
}

展示MapReduce2-3.1.1組件編寫(xiě)Secondary Sort測(cè)試類(lèi):

package linose.mapreduce.secondarysort;

import java.io.IOException;

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.io.WritableComparator;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;

public class SecondarySort {

    public static class SortMapper extends Mapper<LongWritable, Text, IntPair, NullWritable> {
        
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            String[] fields = value.toString().split("\t");
            int field1 = Integer.parseInt(fields[0]);
            int field2 = Integer.parseInt(fields[1]);
            context.write(new IntPair(field1, field2), NullWritable.get());
        }
    }
    
    public static class SortReduce extends Reducer<IntPair, NullWritable, IntPair, NullWritable> {
        
        protected void reduce(IntPair key, Iterable<NullWritable> values, Context context) throws IOException, InterruptedException {
            context.write(key, NullWritable.get());
        }
    }
    
    public static class FirstPartitioner extends Partitioner<IntPair, NullWritable> {
        
        public int getPartition(IntPair key, NullWritable value, int partitions) {
            return Math.abs(key.getFirst().get()) % partitions;
        }
    }
    
    public static class KeyComparator extends WritableComparator {
        
        protected KeyComparator() {
            super(IntPair.class, true);
        }
        
        public int compare(@SuppressWarnings("rawtypes") WritableComparable value1, @SuppressWarnings("rawtypes") WritableComparable value2) {
            IntPair pair1 = (IntPair)value1;
            IntPair pair2 = (IntPair)value2;
            
            int compare = pair1.getFirst().compareTo(pair2.getFirst());
            if (0 != compare) {
                return compare;
            }
            
            return -pair1.getSecond().compareTo(pair2.getSecond());
        }
    }
}

下圖為測(cè)試結(jié)果:


image.png

至此,MapReduce2-3.1.1 Secondary Sort 實(shí)驗(yàn)示例演示完畢。

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