Collectors.groupingBy 相关操作

ForestASpring

已于 2023-03-16 16:41:33 修改

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分类专栏： JAVA stream 文章标签： java 开发语言

于 2023-03-16 16:38:49 首次发布

本文链接：https://blog.youkuaiyun.com/weixin_43983286/article/details/129591107

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该代码段展示了如何使用JavaStreamAPI的`groupingBy`方法进行数据分组统计，包括按时间小时分组计数、保持分组顺序、去重统计、类型转换以及按条件分组后的字段求和。

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@Data
@NoArgsConstructor
@AllArgsConstructor
public class TrackRecord {
    private LocalDateTime operationTime;
    private LocalDateTime startUseTime;
    private LocalDateTime lastUserTime;
    private String token;
}

DateTimeFormatter FORMATTER_HOUR = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:00");
DateTimeFormatter FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");

public List<TrackRecord> list() {
    List<TrackRecord> list = new ArrayList<>();

    String uuid1 = UUID.fastUUID().toString();
    String uuid2 = UUID.fastUUID().toString();
    LocalDateTime time1 = LocalDateTimeUtil.parse("2023-03-11 10:12:11", FORMATTER);
    LocalDateTime time2 = LocalDateTimeUtil.parse("2023-03-12 10:12:11", FORMATTER);
    for (int i = 0; i < 20; i++) {
        TrackRecord trackRecord1 = new TrackRecord(
            time1,
            LocalDateTimeUtil.parse("2023-03-11 10:" + (i + 10) + ":11", FORMATTER),
            LocalDateTimeUtil.parse("2023-03-11 10:" + (i + 10 + 1) + ":11", FORMATTER),
            uuid1, 3L
        );
        System.out.println(trackRecord1.toString());
        list.add(trackRecord1);
    }

    for (int i = 0; i < 20; i++) {
        TrackRecord trackRecord1 = new TrackRecord(
            time2,
            LocalDateTimeUtil.parse("2023-03-11 11:" + (i + 10) + ":11", FORMATTER),
            LocalDateTimeUtil.parse("2023-03-11 11:" + (i + 10 + 1) + ":11", FORMATTER),
             uuid2, 4L
        );
        System.out.println(trackRecord1.toString());
        list.add(trackRecord1);
    }
    return list;
}

分组统计记录数

Map<String, Long> collect = list.stream()
                .collect(Collectors.groupingBy(val -> val.getOperationTime().format(FORMATTER_HOUR),
                        Collectors.counting()));
// 输出
key=2023-03-11 10:00 value=20
key=2023-03-12 10:00 value=20

Collectors.groupingBy有序

LinkedHashMap<String, Long> collect = list.stream()
                .collect(Collectors.groupingBy(val -> val.getOperationTime().format(FORMATTER_HOUR),
                        LinkedHashMap::new, Collectors.counting()));
// 输出
key=2023-03-11 10:00 value=20
key=2023-03-12 10:00 value=20

Collectors.groupingBy value去重统计

LinkedHashMap<String, BigDecimal> collect = list.stream()
                .collect(Collectors.groupingBy(val -> val.getOperationTime().format(FORMATTER_HOUR),
                        LinkedHashMap::new,
                        Collectors.mapping(TrackRecord::getToken,
                                Collectors.collectingAndThen(Collectors.toSet(), set -> BigDecimal.valueOf(set.size()))))
                );
// 输出
key=2023-03-11 10:00 value=1
key=2023-03-12 10:00 value=1

Collectors.groupingBy value类型转换

LinkedHashMap<String, BigDecimal> collect = list.stream()
                .collect(Collectors.groupingBy(val -> val.getOperationTime().format(FORMATTER_HOUR),
                        LinkedHashMap::new, Collectors.collectingAndThen(Collectors.counting(), BigDecimal::valueOf)));
// 输出
key=2023-03-11 10:00 value=20
key=2023-03-12 10:00 value=20

Collectors.groupingBy 按条件分组后对指定的字段求和

 LinkedHashMap<String, BigDecimal> collect = list.stream()
                .collect(Collectors.groupingBy(val -> val.getOperationTime().format(FORMATTER_HOUR),
                        LinkedHashMap::new, Collectors.collectingAndThen(
                                Collectors.summingLong(TrackRecord::getNum), bd -> new BigDecimal(bd.toString())
                        )));
// 输出
key=2023-03-11 10:00 value=60
key=2023-03-12 10:00 value=80