hadoop项目之求出每年二月的最高气温(Combiner优化)

hadoop项目之求出每年二月的最高气温(Combiner优化)

一、项目结构

hadoop项目之求出每年二月的最高气温(Combiner优化)插图

hadoop项目之求出每年二月的最高气温(Combiner优化)插图1

一、java实现随机生成日期和气温

package com.shujia.weather;

import java.io.BufferedWriter;
import java.io.FileWriter;
import java.io.IOException;
import java.text.DateFormat;
import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.Date;

public class RandomWeather {
    public static void main(String[] args) throws ParseException, IOException {
        //创建日期格式
        DateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
        long start = sdf.parse("2000-01-01 00:00:00").getTime();
        long end = sdf.parse("2022-12-31 00:00:00").getTime();
        long difference=end - start;

        BufferedWriter bw = new BufferedWriter(new FileWriter("F:\software\IdeaProjects\bigdata19-project\biddata19-mapreduce\src\data\weather.txt"));
        for (int i=0;i

二、将这个weather.txt文件上传到虚拟机后再上传到hadoop

1、通过xftp上传文件
2、通过命令上传到hadoop
hadoop fs -put weather.txt /路径

三、项目实现

package com.shujia.weather;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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;

import java.io.IOException;

class WeatherMapper extends Mapper{
    /*
    2022-06-12 02:40:26 21
    2002-01-03 03:49:27 -13
    2001-04-21 19:19:22 -16
    2005-01-18 01:52:15 10
    求出每年二月份的最高气温
     */

    @Override
    protected void map(LongWritable key, Text value, Mapper.Context context) throws IOException, InterruptedException {
        String line = value.toString();
        String[] str = line.split("t");
        String temperature = str[1];
        String[] strings = str[0].split("-");
        String Month = strings[1];
        if ("02".equals(Month)){
            context.write(new Text(strings[0]+"-"+Month),new LongWritable(Long.parseLong(temperature)));
        }

    }
}

class WeatherReducer extends Reducer{
    @Override
    protected void reduce(Text key, Iterable values, Reducer.Context context) throws IOException, InterruptedException {
        long max=0L;
        for (LongWritable value : values) {
            long l = value.get();
            if (l>max){
                max=l;
            }
        }
        context.write(key,new LongWritable(max));
    }
}

public class WeatherDemo {
    public static void main(String[] args) throws IOException, InterruptedException, ClassNotFoundException {
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);

        job.setCombinerClass(WeatherReducer.class);//Combiner优化
        job.setJarByClass(WeatherDemo.class);
        job.setMapperClass(WeatherMapper.class);
        job.setReducerClass(WeatherReducer.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(LongWritable.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);

        FileInputFormat.setInputPaths(job,new Path(args[0]));
        FileOutputFormat.setOutputPath(job,new Path(args[1]));

        job.waitForCompletion(true);
    }
}

优化前

hadoop项目之求出每年二月的最高气温(Combiner优化)插图2

优化后

hadoop项目之求出每年二月的最高气温(Combiner优化)插图3

减少了reduce 从map拉取数据的过程,提高计算效率。

hadoop 的计算特点:将计算任务向数据靠拢,而不是将数据向计算靠拢。

注意:将reduce端的聚合操作,放到map 进行执行。适合求和,计数,等一些等幂操作。不适合求平均值,次幂等类似操作

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