统计某年每个月的汽车销售数量的比例实现比例计算

统计某年每个月的汽车销售数量的比例，可以使用Hadoop MapReduce编写一个MapReduce作业来完成。具体步骤如下：

1. Mapper阶段：将数据读取并转换为键值对，其中键是年份和月份，值是销售数量。Mapper代码如下：

public class SalesMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
  private Text yearMonth = new Text();
  private IntWritable sales = new IntWritable();

  public void map(LongWritable key, Text value, Context context)
    throws IOException, InterruptedException {
    // 解析每行记录，获取年份、月份和销售数量
    String[] fields = value.toString().split(",");
    String dateStr = fields[0];
    int qty = Integer.parseInt(fields[1]);

    // 将日期转换为年份和月份
    SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd");
    Date date = dateFormat.parse(dateStr);
    Calendar cal = Calendar.getInstance();
    cal.setTime(date);
    int year = cal.get(Calendar.YEAR);
    int month = cal.get(Calendar.MONTH) + 1;

    // 设置键值对
    yearMonth.set(year + "-" + month);
    sales.set(qty);

    // 输出键值对
    context.write(yearMonth, sales);
  }
}

2. Reducer阶段：对Mapper阶段输出的键值对进行聚合和计算，得到每个月的销售总数量。Reducer代码如下：

public class SalesReducer extends Reducer<Text, IntWritable, Text, DoubleWritable> {
  private DoubleWritable ratio = new DoubleWritable();

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

    // 计算比例
    ratio.set((double)sum / totalSales);

    // 输出结果
    context.write(key, ratio);
  }
}

在Reducer阶段，我们需要计算每个月的销售总数量，并根据年份和月份计算比例。为了计算比例，我们需要在Mapper阶段先统计总销售量。可以在Driver类中定义一个变量来保存总销售量，并在Mapper阶段累加每个月的销售数量。具体代码如下：

public class SalesDriver {
  public static void main(String[] args) throws Exception {
    // 创建Job对象
    Job job = Job.getInstance();

    // 设置Job的各种属性
    job.setJarByClass(SalesDriver.class);
    job.setMapperClass(SalesMapper.class);
    job.setReducerClass(SalesReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);

    // 设置输入输出路径
    FileInputFormat.setInputPaths(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));

    // 计算总销售量
    long totalSales = 0;
    FileSystem fs = FileSystem.get(job.getConfiguration());
    RemoteIterator<LocatedFileStatus> fileStatusIter = fs.listFiles(new Path(args[0]), true);
    while (fileStatusIter.hasNext()) {
      LocatedFileStatus fileStatus = fileStatusIter.next();
      if (!fileStatus.isDirectory()) {
        BufferedReader reader = new BufferedReader(new InputStreamReader(fs.open(fileStatus.getPath())));
        String line = null;
        while ((line = reader.readLine()) != null) {
          String[] fields = line.split(",");
          int qty = Integer.parseInt(fields[1]);
          totalSales += qty;
        }
        reader.close();
      }
    }

    // 设置总销售量到Reducer类中
    job.getConfiguration().setLong("totalSales", totalSales);

    // 提交Job并等待完成
    job.waitForCompletion(true);
  }
}

在Reducer阶段，我们需要从Configuration对象中获取总销售量，并计算每个月的销售比例。具体代码如下：

public class SalesReducer extends Reducer<Text, IntWritable, Text, DoubleWritable> {
  private DoubleWritable ratio = new DoubleWritable();
  private long totalSales;

  public void setup(Context context) {
    totalSales = context.getConfiguration().getLong("totalSales", 0);
  }

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

    // 计算比例
    ratio.set((double)sum / totalSales);

    // 输出结果
    context.write(key, ratio);
  }
}

这样，就可以完成统计某年每个月的汽车销售数量的比例的实现。