帮我写一个基于mapreduce和eclipse和Hadoop的天气数据分析系统的代码

很抱歉，由于篇幅限制，无法提供完整的代码。以下是一个简单的MapReduce作业，用于计算天气数据中每个城市的平均气温。您可以参考这个作业的代码，根据自己的需求进行修改和扩展。

Mapper类：

public class WeatherMapper extends Mapper<LongWritable, Text, Text, DoubleWritable> {
    private Text city = new Text();
    private DoubleWritable temperature = new DoubleWritable();

    public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String[] fields = value.toString().split(",");
        city.set(fields[0]);
        temperature.set(Double.parseDouble(fields[1]));
        context.write(city, temperature);
    }
}

Reducer类：

public class WeatherReducer extends Reducer<Text, DoubleWritable, Text, DoubleWritable> {
    private DoubleWritable result = new DoubleWritable();

    public void reduce(Text key, Iterable<DoubleWritable> values, Context context) throws IOException, InterruptedException {
        double sum = 0;
        int count = 0;
        for (DoubleWritable val : values) {
            sum += val.get();
            count++;
        }
        result.set(sum/count);
        context.write(key, result);
    }
}

主程序：

public class WeatherAnalysis {
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf, "Weather Analysis");
        job.setJarByClass(WeatherAnalysis.class);
        job.setMapperClass(WeatherMapper.class);
        job.setReducerClass(WeatherReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(DoubleWritable.class);
        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

这个作业的功能是将输入文件中的每行数据解析为城市和温度两个字段，然后计算每个城市的平均温度，并输出到文件中。您可以根据自己的需求进行修改和扩展。