Hadoop之——自定义排序算法实现排序功能

Hadoop之——自定义排序算法实现排序功能

要求首先按照第一列升序排列，当第一列相同时，第二列升序排列；不多说直接上代码

1、Mapper类的实现

/** * Mapper类的实现 * @author liuyazhuang * */ static class MyMapper extends Mapper{ protected void map(LongWritable key, Text value, org.apache.hadoop.mapreduce.Mapper.Context context) throws java.io.IOException ,InterruptedException { final String[] splited = value.toString().split("\t"); final NewK2 k2 = new NewK2(Long.parseLong(splited[0]), Long.parseLong(splited[1])); final LongWritable v2 = new LongWritable(Long.parseLong(splited[1])); context.write(k2, v2); }; }

2、Reducer类的实现

/** * Reducer类的实现 * @author liuyazhuang * */ static class MyReducer extends Reducer{ protected void reduce(NewK2 k2, java.lang.Iterable v2s, org.apache.hadoop.mapreduce.Reducer.Context context) throws java.io.IOException ,InterruptedException { context.write(new LongWritable(k2.first), new LongWritable(k2.second)); }; }

3、WritableComparable实现

/** * 问：为什么实现该类？ * 答：因为原来的v2不能参与排序，把原来的k2和v2封装到一个类中，作为新的k2 * @author liuyazhuang */ static class NewK2 implements WritableComparable{ Long first; Long second; public NewK2(){} public NewK2(long first, long second){ this.first = first; this.second = second; } @Override public void readFields(DataInput in) throws IOException { this.first = in.readLong(); this.second = in.readLong(); } @Override public void write(DataOutput out) throws IOException { out.writeLong(first); out.writeLong(second); } /** * 当k2进行排序时，会调用该方法. * 当第一列不同时，升序；当第一列相同时，第二列升序 * @author liuyazhuang */ @Override public int compareTo(NewK2 o) { final long minus = this.first - o.first; if(minus !=0){ return (int)minus; } return (int)(this.second - o.second); } @Override public int hashCode() { return this.first.hashCode()+this.second.hashCode(); } @Override public boolean equals(Object obj) { if(!(obj instanceof NewK2)){ return false; } NewK2 oK2 = (NewK2)obj; return (this.first==oK2.first)&&(this.second==oK2.second); } }

4、程序入口Main

public static void main(String[] args) throws Exception{ final Configuration configuration = new Configuration(); final FileSystem fileSystem = FileSystem.get(new URI(INPUT_PATH), configuration); if(fileSystem.exists(new Path(OUT_PATH))){ fileSystem.delete(new Path(OUT_PATH), true); } final Job job = new Job(configuration, SortApp.class.getSimpleName()); //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); //指定输出的类型 job.setMapOutputKeyClass(NewK2.class); job.setMapOutputValueClass(LongWritable.class); //1.3 指定分区类 job.setPartitionerClass(HashPartitioner.class); job.setNumReduceTasks(1); //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); //指定输出的类型 job.setOutputKeyClass(LongWritable.class); job.setOutputValueClass(LongWritable.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); }

5、完整代码

package com.lyz.hadoop.sort;import java.io.DataInput;import java.io.DataOutput;import java.io.IOException;import java.net.URI;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.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.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;/** * Hadoop实现排序 * 首先按照第一列升序排列，当第一列相同时，第二列升序排列 * @author liuyazhuang * */public class SortApp { static final String INPUT_PATH = "hdfs://liuyazhuang:9000/input"; static final String OUT_PATH = "hdfs://liuyazhuang:9000/out"; public static void main(String[] args) throws Exception{ final Configuration configuration = new Configuration(); final FileSystem fileSystem = FileSystem.get(new URI(INPUT_PATH), configuration); if(fileSystem.exists(new Path(OUT_PATH))){ fileSystem.delete(new Path(OUT_PATH), true); } final Job job = new Job(configuration, SortApp.class.getSimpleName()); //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); //指定输出的类型 job.setMapOutputKeyClass(NewK2.class); job.setMapOutputValueClass(LongWritable.class); //1.3 指定分区类 job.setPartitionerClass(HashPartitioner.class); job.setNumReduceTasks(1); //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); //指定输出的类型 job.setOutputKeyClass(LongWritable.class); job.setOutputValueClass(LongWritable.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); } /** * Mapper类的实现 * @author liuyazhuang * */ static class MyMapper extends Mapper{ protected void map(LongWritable key, Text value, org.apache.hadoop.mapreduce.Mapper.Context context) throws java.io.IOException ,InterruptedException { final String[] splited = value.toString().split("\t"); final NewK2 k2 = new NewK2(Long.parseLong(splited[0]), Long.parseLong(splited[1])); final LongWritable v2 = new LongWritable(Long.parseLong(splited[1])); context.write(k2, v2); }; } /** * Reducer类的实现 * @author liuyazhuang * */ static class MyReducer extends Reducer{ protected void reduce(NewK2 k2, java.lang.Iterable v2s, org.apache.hadoop.mapreduce.Reducer.Context context) throws java.io.IOException ,InterruptedException { context.write(new LongWritable(k2.first), new LongWritable(k2.second)); }; } /** * 问：为什么实现该类？ * 答：因为原来的v2不能参与排序，把原来的k2和v2封装到一个类中，作为新的k2 * @author liuyazhuang */ static class NewK2 implements WritableComparable{ Long first; Long second; public NewK2(){} public NewK2(long first, long second){ this.first = first; this.second = second; } @Override public void readFields(DataInput in) throws IOException { this.first = in.readLong(); this.second = in.readLong(); } @Override public void write(DataOutput out) throws IOException { out.writeLong(first); out.writeLong(second); } /** * 当k2进行排序时，会调用该方法. * 当第一列不同时，升序；当第一列相同时，第二列升序 * @author liuyazhuang */ @Override public int compareTo(NewK2 o) { final long minus = this.first - o.first; if(minus !=0){ return (int)minus; } return (int)(this.second - o.second); } @Override public int hashCode() { return this.first.hashCode()+this.second.hashCode(); } @Override public boolean equals(Object obj) { if(!(obj instanceof NewK2)){ return false; } NewK2 oK2 = (NewK2)obj; return (this.first==oK2.first)&&(this.second==oK2.second); } } }

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