package mapreduce;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
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;
public class OneSort {
public static class Map extends Mapper<Object , Text , IntWritable,Text >{
private static Text goods=new Text();
private static IntWritable num=new IntWritable();
public void map(Object key,Text value,Context context) throws IOException, InterruptedException{
String line=value.toString();
String arr[]=line.split(" ");
num.set(Integer.parseInt(arr[1]));
goods.set(arr[0]);
context.write(num,goods);
}
}
public static class Reduce extends Reducer< IntWritable, Text, IntWritable, Text>{
private static IntWritable result= new IntWritable();
public void reduce(IntWritable key,Iterable<Text> values,Context context) throws IOException, InterruptedException{
for(Text val:values){
context.write(key,val);
}
}
}
public static class IntWritableDecreasingComparator extends IntWritable.Comparator
{
public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2)
{
return -super.compare(b1, s1, l1, b2, s2, l2);
}
}
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException{
Configuration conf=new Configuration();
Job job =new Job(conf,"OneSort");
job.setJarByClass(OneSort.class);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setOutputKeyClass(IntWritable.class);
job.setOutputValueClass(Text.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
Path in=new Path("hdfs://192.168.43.114:9000/mymapreduce3/in/one");
Path out=new Path("hdfs://192.168.43.114:9000/mymapreduce3/out");
FileInputFormat.addInputPath(job,in);
FileOutputFormat.setOutputPath(job,out);
job.setSortComparatorClass(IntWritableDecreasingComparator.class);
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
利用mapreduce的wordcount程序进行id的计算,相同id合并并计数,之后 将输出的文件根据次数降序,
因为mapreduce的排序是是默认升序排序,所以需要写排序类重写降序类,最后将输出结果存到hive与mysql中。