ubuntu计算圆周率

要在Ubuntu上计算圆周率，可以使用Hadoop框架。以下是步骤：

1.安装Java和Hadoop
在Ubuntu上安装Java和Hadoop，可以参考引用和引用中的步骤。

2.编写Java程序
编写一个Java程序来计算圆周率。以下是示例代码：

package org.apache.hadoop.examples;

import java.io.IOException;
import java.util.Random;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
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.output.FileOutputFormat;

public class PiEstimator {

  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    Job job = Job.getInstance(conf, "pi estimator");
    job.setJarByClass(PiEstimator.class);
    job.setMapperClass(Map.class);
    job.setReducerClass(Reduce.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }

  public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {

    private static final IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(LongWritable key, Text value, Context context)
        throws IOException, InterruptedException {
      int inside = 0;
      int outside = 0;
      Random r = new Random();
      for (int i = 0; i < 100000; i++) {
        double x = r.nextDouble();
        double y = r.nextDouble();
        if (x * x + y * y <= 1) {
          inside++;
        } else {
          outside++;
        }
      }
      context.write(new Text("pi"), new IntWritable(inside));
      context.write(new Text("not pi"), new IntWritable(outside));
    }
  }

  public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {

    public void reduce(Text key, Iterable<IntWritable> values, Context context)
        throws IOException, InterruptedException {
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();
      }
      context.write(key, new IntWritable(sum));
    }
  }
}

3.将程序打包成JAR文件
使用以下命令将程序打包成JAR文件：

javac -classpath ${HADOOP_HOME}/hadoop-core.jar PiEstimator.java
jar cvf PiEstimator.jar *.class

4.运行程序
使用以下命令在Hadoop上运行程序：

hadoop jar PiEstimator.jar org.apache.hadoop.examples.PiEstimator input output

其中，input是输入文件的路径，output是输出文件的路径。

5.查看结果
使用以下命令查看输出文件的内容：

hadoop fs -cat output/part-r-00000

输出的结果应该类似于：

not pi  78556
pi      21444