java - 比较日期列表并找到最接近分钟的日期，然后选择它并将其四舍五入到最接近的分钟

Question

我有一个对象类型列表 - TrackingMessage，其中包含日期。该列表可以包含 5 到数千个条目。

我需要遍历该列表来比较每个日期，以找到最接近分钟的日期。该列表在一分钟内可能包含 3 或 4 个条目，因此需要找到最接近分钟的条目，然后将其四舍五入到最接近的分钟。

即 12:45:22、12:45:35、12:45:15

从上面的小示例中，它将选择 12:45:15 作为最接近分钟的值，然后将其四舍五入到最接近的分钟 - 12:45:00>.

我目前的代码如下:

返回根据时间排序和舍入的消息列表的方法

private List<TrackingMessage> findTrackingMessageDatesToNearestMinute(List<TrackingMessage> filteredTrackingMessages) {
    return filteredTrackingMessages.stream()
            .sorted(orderByClosestToMinute)
            .filter(JourneyServiceUtil.distinctByKey(x -> roundToClosestMinute(x)))
            .sorted(comparing(TrackingMessage::getEventTime))
            .collect(Collectors.toList());
  }

传入流的比较器

  public Comparator<TrackingMessage> orderByClosestToMinute = (tm1, tm2) -> {
    LocalDateTime roundedTrackingMessage1 = roundToClosestMinute(tm1);
    LocalDateTime roundedTrackingMessage2 = roundToClosestMinute(tm2);
    Duration tm1Duration = Duration.between(DateTimeUtils.toLocalDateTime(tm1.getEventTime()), roundedTrackingMessage1).abs();
    Duration tm2Duration = Duration.between(DateTimeUtils.toLocalDateTime(tm2.getEventTime()), roundedTrackingMessage2).abs();
    return tm1Duration.compareTo(tm2Duration);
  };

将时间四舍五入到最接近的分钟的函数

  private LocalDateTime roundToClosestMinute(TrackingMessage trackingMessage) {
    return DateTimeUtils.toLocalDateTime(DateUtils.round(trackingMessage.getEventTime(), Calendar.MINUTE));
  }

去重函数

  public static <T> Predicate<T> distinctByKey(Function<? super T, ?> keyExtractor) {
    Set<Object> seen = ConcurrentHashMap.newKeySet();
    return t -> seen.add(keyExtractor.apply(t));
  }

现在这段代码可以工作了，但是这段代码返回的响应如下:

{
    "status": "success",
    "serviceId": "d8f2092b-01de-424f-9068-32c4efdcfd45",
    "driverId": "e1275ef6-f885-4724-9255-2e03868df5ee",
    "eventList": [
        {
            "eventTime": "2019-07-18T13:09:01",
            "eventId": 15,
            "lat": 50.4130166,
            "lon": -5.0739198
        },
        {
            "eventTime": "2019-07-18T13:10:04",
            "eventId": 21,
            "lat": 50.412991299999995,
            "lon": -5.073924
        },
        {
            "eventTime": "2019-07-18T13:11:04",
            "eventId": 21,
            "lat": 50.413074599999995,
            "lon": -5.074010299999999
        },
        {
            "eventTime": "2019-07-18T13:12:04",
            "eventId": 21,
            "lat": 50.4131295,
            "lon": -5.0739676
        },
        {
            "eventTime": "2019-07-18T13:13:04",
            "eventId": 21,
            "lat": 50.4133475,
            "lon": -5.073917499999999
        },
        {
            "eventTime": "2019-07-18T13:14:04",
            "eventId": 21,
            "lat": 50.4133618,
            "lon": -5.0739218
        },
        {
            "eventTime": "2019-07-18T13:15:04",
            "eventId": 21,
            "lat": 50.4133333,
            "lon": -5.073961
        },
        {
            "eventTime": "2019-07-18T13:16:04",
            "eventId": 21,
            "lat": 50.4132803,
            "lon": -5.0739765
        },
        {
            "eventTime": "2019-07-18T13:17:04",
            "eventId": 21,
            "lat": 50.4133433,
            "lon": -5.0739588
        },
        {
            "eventTime": "2019-07-18T13:18:04",
            "eventId": 21,
            "lat": 50.413306999999996,
            "lon": -5.0739355999999995
        },
        {
            "eventTime": "2019-07-18T13:19:04",
            "eventId": 21,
            "lat": 50.4133013,
            "lon": -5.073953599999999
        },
        {
            "eventTime": "2019-07-18T13:20:04",
            "eventId": 21,
            "lat": 50.413309299999995,
            "lon": -5.073988099999999
        },
        {
            "eventTime": "2019-07-18T13:21:04",
            "eventId": 21,
            "lat": 50.4133146,
            "lon": -5.0739618
        },
        {
            "eventTime": "2019-07-18T13:22:04",
            "eventId": 21,
            "lat": 50.413287999999994,
            "lon": -5.0739141
        },
        {
            "eventTime": "2019-07-18T13:23:04",
            "eventId": 21,
            "lat": 50.4132981,
            "lon": -5.0739008
        },
        {
            "eventTime": "2019-07-18T13:24:04",
            "eventId": 21,
            "lat": 50.413283,
            "lon": -5.07386
        },
        {
            "eventTime": "2019-07-18T13:25:03",
            "eventId": 52,
            "lat": 50.413303,
            "lon": -5.0738673
        },
        {
            "eventTime": "2019-07-18T13:26:01",
            "eventId": 60,
            "lat": 50.4135111,
            "lon": -5.0737745
        },
        {
            "eventTime": "2019-07-18T13:27:02",
            "eventId": 130,
            "lat": 50.415140099999995,
            "lon": -5.073355299999999
        },
        {
            "eventTime": "2019-07-18T13:28:00",
            "eventId": 125,
            "lat": 50.4139743,
            "lon": -5.0697981
        },
        {
            "eventTime": "2019-07-18T13:29:01",
            "eventId": 21,
            "lat": 50.4186421,
            "lon": -5.0698473
        },
        {
            "eventTime": "2019-07-18T13:30:09",
            "eventId": 153,
            "lat": 50.418105999999995,
            "lon": -5.0624391
        },
        {
            "eventTime": "2019-07-18T13:30:50",
            "eventId": 21,
            "lat": 50.4185011,
            "lon": -5.0581641
        },
        {
            "eventTime": "2019-07-18T13:31:59",
            "eventId": 21,
            "lat": 50.417915099999995,
            "lon": -5.0517363
        },
        {
            "eventTime": "2019-07-18T13:33:02",
            "eventId": 131,
            "lat": 50.4194111,
            "lon": -5.0496058
        },
        {
            "eventTime": "2019-07-18T13:35:34",
            "eventId": 51,
            "lat": 50.4194153,
            "lon": -5.049543
        }
    ]
}

正如您所看到的(向底部)，我们在 13:30 内有两次 {2019-07-18T13:30:50、2019-07-18T13:30:09}

从技术上讲，我希望选择 2019-07-18T13:30:09，因为它最接近分钟(相差 9 秒，而另一个相差 10 秒)

此外，如果您查看响应，时间会以秒为单位，并且不会向下舍入。

如果不清楚，请随时提出任何进一步的问题。

Answer 1

您似乎想要计算自一分钟开始以来经过的秒数。因此，在您的示例中，13:30:09 表示该分钟后 9 秒，13:30:50 表示该分钟后 50 秒。

要计算您可以使用此方法:

public static int distanceToMinute(LocalDateTime t) {
  LocalDateTime minute = t.truncatedTo(ChronoUnit.MINUTES);
  return (int) ChronoUnit.SECONDS.between(minute, t);
}

对于您给出的两个示例，它将按预期返回 9 和 50。

下一步是按分钟对时间进行分组，例如:

List<LocalDateTime> times = ...
Map<LocalDateTime, List<LocalDateTime>> timesByMinute = times.stream()
                    .collect(Collectors.groupingBy(t -> t.truncatedTo(ChronoUnit.MINUTES)));

然后将每个列表减少到最接近分钟的元素:

public static LocalDateTime bestTime(List<LocalDateTime> times) {
  return times.stream()
           .sorted((t1, t2) -> Integer.compare(distanceToMinute(t1), distanceToMinute(t2)))
           .findFirst().get();
}