map and reduce 数学,mapreduce求和

MapReduce关系代数运算——投影

关系沿用上一个选择运算的关系R，StudentR类也是一致的，本博文中就不赘述了。

MapReduce程序设计 Projection import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.NullWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.Mapper;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 java.io.IOException;public class Projection { public static class ProjectionMap extends Mapper<LongWritable, Text, Text, NullWritable> { private int col; @Override protected void setup(Context context) throws IOException, InterruptedException { col = context.getConfiguration().getInt("col", 0); } @Override protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { StudentR record = new StudentR(value.toString()); context.write(new Text(record.getCol(col)), NullWritable.get()); } } public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException { Configuration conf = new Configuration(); conf.setInt("col", Integer.parseInt(args[2])); Job projectionJob = Job.getInstance(conf, "ProgectionJob"); projectionJob.setJarByClass(Projection.class); projectionJob.setMapperClass(ProjectionMap.class); projectionJob.setMapOutputKeyClass(Text.class); projectionJob.setMapOutputValueClass(NullWritable.class); projectionJob.setNumReduceTasks(0); projectionJob.setInputFormatClass(TextInputFormat.class); projectionJob.setOutputFormatClass(TextOutputFormat.class); FileInputFormat.addInputPath(projectionJob, new Path(args[0])); FileOutputFormat.setOutputPath(projectionJob, new Path(args[1])); projectionJob.waitForCompletion(true); System.out.println("finished!"); }} 运行

像之前的WordCount一样将代码打包出来，生成Projection.jar文件，但是在终端运行的时候，需要注意的是不只是输入两个路径，而应该输入选择的条件。如本例中，我们要输出学生成绩信息，则应该选定第四列grade
字段：

hadoop jar Projection.jar /input /output 4

查看输出结果：

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