使用Java 8 Stream从Guava Table按星期几提取统计数据

没问题，我来帮你搞定这个Guava Table按星期几分组统计的需求，用Java 8实现的话可以这么做：

1. 准备基础类 #

首先确保你有实体类和初始化好的Guava Table数据：

WeatherInformation实体类 #

class WeatherInformation {
    private final int temperature;
    private final int snow;
    private final int rain;

    public WeatherInformation(int temperature, int snow, int rain) {
        this.temperature = temperature;
        this.snow = snow;
        this.rain = rain;
    }

    // Getter方法
    public int getTemperature() { return temperature; }
    public int getSnow() { return snow; }
    public int getRain() { return rain; }
}

初始化Guava Table示例数据 #

import com.google.common.collect.HashBasedTable;
import com.google.common.collect.Table;

// 初始化题目中给定的天气数据
Table<Integer, String, WeatherInformation> weatherTable = HashBasedTable.create();
weatherTable.put(1, "Sunday", new WeatherInformation(25, 0, 0));
weatherTable.put(2, "Monday", new WeatherInformation(25, 0, 1));
weatherTable.put(3, "Tuesday", new WeatherInformation(25, 0, 2));
weatherTable.put(4, "Sunday", new WeatherInformation(25, 0, 3));
weatherTable.put(5, "Monday", new WeatherInformation(25, 0, 4));
weatherTable.put(6, "Friday", new WeatherInformation(25, 0, 5));
weatherTable.put(7, "Saturday", new WeatherInformation(25, 0, 6));
weatherTable.put(8, "Sunday", new WeatherInformation(25, 0, 7));
weatherTable.put(9, "Monday", new WeatherInformation(25, 0, 8));

2. 核心统计逻辑（Java 8兼容版） #

因为Java 8没有Collectors.teeing（Java 12才引入），所以我们用自定义收集器来实现分组统计：

import java.util.Map;
import java.util.stream.Collectors;

public class WeatherStatisticsProcessor {
    public static void main(String[] args) {
        // 按星期几分组计算统计数据
        Map<String, WeatherStats> statsMap = weatherTable.cellSet().stream()
                .collect(Collectors.groupingBy(
                        // 分组依据：星期几（Table的列键）
                        cell -> cell.getColumnKey(),
                        // 自定义收集器：累加计数和各字段总和，最后计算平均值
                        Collector.of(
                                Accumulator::new,
                                (accumulator, cell) -> {
                                    WeatherInformation info = cell.getValue();
                                    accumulator.count++;
                                    accumulator.totalTemp += info.getTemperature();
                                    accumulator.totalSnow += info.getSnow();
                                    accumulator.totalRain += info.getRain();
                                },
                                (acc1, acc2) -> {
                                    // 并行流场景下合并两个累加器的数据
                                    acc1.count += acc2.count;
                                    acc1.totalTemp += acc2.totalTemp;
                                    acc1.totalSnow += acc2.totalSnow;
                                    acc1.totalRain += acc2.totalRain;
                                    return acc1;
                                },
                                accumulator -> new WeatherStats(
                                        accumulator.count,
                                        accumulator.totalTemp / accumulator.count,
                                        accumulator.totalSnow / accumulator.count,
                                        accumulator.totalRain / accumulator.count
                                )
                        )
                ));

        // 按要求格式化输出结果
        statsMap.forEach((day, stats) -> {
            // 处理降雨平均值格式：记录数为1时输出整数，否则保留两位小数
            String rainAvgStr = stats.count == 1 
                    ? String.format("%.0f", stats.avgRain) 
                    : String.format("%.2f", stats.avgRain);
            
            System.out.printf("%s = Count:%d, Avg[Temp:%.0f; Snow:%.0f; Rain:%s]%n",
                    day, stats.count, stats.avgTemp, stats.avgSnow, rainAvgStr);
        });
    }

    // 临时累加器：存储每组的计数和各字段总和
    private static class Accumulator {
        long count = 0;
        double totalTemp = 0;
        double totalSnow = 0;
        double totalRain = 0;
    }

    // 最终统计结果类：存储每组的计数和平均值
    private static class WeatherStats {
        final long count;
        final double avgTemp;
        final double avgSnow;
        final double avgRain;

        WeatherStats(long count, double avgTemp, double avgSnow, double avgRain) {
            this.count = count;
            this.avgTemp = avgTemp;
            this.avgSnow = avgSnow;
            this.avgRain = avgRain;
        }
    }
}

3. 代码说明 #

• 分组逻辑：通过Collectors.groupingBy提取Table的列键（星期几）作为分组依据；
• 自定义收集器：用Collector.of实现了一个收集器，负责累加每组的记录数和各气象字段的总和，最后通过「总和/计数」得到平均值；
• 格式化输出：根据记录数的不同调整降雨平均值的显示格式，完全匹配你要求的输出样式。

运行结果 #

运行后会输出（注：你提供的示例中Tuesday的Rain值应为2，属于笔误，以下是正确计算结果）：

Sunday = Count:3, Avg[Temp:25; Snow:0; Rain:3.33]
Monday = Count:3, Avg[Temp:25; Snow:0; Rain:4.33]
Tuesday = Count:1, Avg[Temp:25; Snow:0; Rain:2]
Friday = Count:1, Avg[Temp:25; Snow:0; Rain:5]
Saturday = Count:1, Avg[Temp:25; Snow:0; Rain:6]

内容的提问来源于stack exchange，提问作者NewBee