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Hadoop读书笔记(十二)MapReduce自定义排序
Hadoop读书笔记系列文章:http://blog.csdn.net/caicongyang/article/category/2166855
1.说明:
对给出的两列数据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
数据格式:
3 3 3 2 3 1 2 2 2 1 1 1
2.代码
SortApp.java
package 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; /** * * <p> * Title: SortApp.java * Package sort * </p> * <p> * Description: 当第一列不同时,升序;当第一列相同时,第二列升序 * <p> * @author Tom.Cai * @created 2014-12-2 下午10:29:14 * @version V1.0 * */ public class SortApp { private static final String INPUT_PATH = "hdfs://192.168.80.100:9000/sort_input"; private static final String OUT_PATH = "hdfs://192.168.80.100:9000/sort_out"; public static void main(String[] args) throws Exception { Configuration conf = new Configuration(); FileSystem fileSystem = FileSystem.get(new URI(INPUT_PATH), conf); if(fileSystem.exists(new Path(OUT_PATH))){ fileSystem.delete(new Path(OUT_PATH),true); } Job job = new Job(conf,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<k2,v2>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<k3,v3>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); } static class MyMapper extends Mapper<LongWritable,Text, newK2,LongWritable>{ @Override protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String[] splied = value.toString().split("\t"); newK2 k2 = new newK2(Long.parseLong(splied[0]),Long.parseLong(splied[1])); final LongWritable v2 = new LongWritable(Long.parseLong(splied[1])); context.write(k2, v2); } } static class MyReducer extends Reducer<newK2, LongWritable, LongWritable, LongWritable>{ @Override protected void reduce(sort.SortApp.newK2 key, Iterable<LongWritable> value, Context context) throws IOException, InterruptedException { context.write(new LongWritable(key.first), new LongWritable(key.second)); } } static class newK2 implements WritableComparable<newK2>{ Long first; Long second; public newK2(long first, long second) { this.first = first; this.second = second; } public newK2() { } @Override public void readFields(DataInput input) throws IOException { this.first = input.readLong(); this.second = input.readLong(); } @Override public void write(DataOutput out) throws IOException { out.writeLong(first); out.writeLong(second); } /** * * * 当第一列不同时,升序;当第一列相同时,第二列升序 */ @Override public int compareTo(newK2 o) { long temp = this.first -o.first; if(temp!=0){ return (int)temp; } 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 k2 = (newK2)obj; return(this.first == k2.first)&&(this.second == k2.second); } } }
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Hadoop读书笔记(十二)MapReduce自定义排序
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