假设我有下表，名为 video_data。我还有另外一个 videos，但它并不真正相关。我用它来查询特定 channel 的视频，但这不会改变查询。这只是为了获取一个 channel 而不是所有 channel 的计算结果。

+----+----------+-------+---------------------+
| id | video_id | views |     created_at      |
+----+----------+-------+---------------------+
|  1 |        1 |  1000 | 2016-04-26 00:00:00 |
|  2 |        2 |   500 | 2016-04-26 00:00:01 |
|  3 |        3 |  2500 | 2016-04-26 00:00:02 |

|  4 |        1 |  1500 | 2016-04-26 02:00:00 |
|  5 |        2 |  1000 | 2016-04-26 02:00:01 |
|  6 |        3 |  3000 | 2016-04-26 02:00:02 |

|  7 |        1 |  5000 | 2016-04-26 04:00:00 |
|  8 |        2 | 10000 | 2016-04-26 04:00:01 |
|  9 |        3 | 30000 | 2016-04-26 04:00:02 |
+----+----------+-------+---------------------+

我现在要做的是获取一个时间范围内的浏览量的平均值。比方说，我想获得视频在 2 小时内的平均观看次数。让我们以带有 video_1 的视频为例

所以我需要做的是以下内容。我需要获取 id: 1 和 id: 4 的平均值。这将是 1250，因为它是 (1000 + 1500)/2。接下来，我需要获取 id: 4 和 id: 7 的平均值。这将是 3250，因为它是 (1500 + 5000)/2。现在，视频在两个小时内的平均值为 2250，因为它是 (1250 + 3250)/2，对吗？

现在我不知道如何从 MySQL 中获取它。甚至可以在普通的 MySQL 中做吗？我需要这个用于很多很多视频数据。就像我有超过 100 小时的数据!如果 id: 100 和 id: 105 的数据彼此相隔不到两个小时，我仍然需要计算这些数据以进行计算。

我想像这样做

select *
from `video_data`
where `video_id` in (select `id` from `videos` where `channel_id` = 1)
  and TIMEDIFF(`created_at`, `created_at`) < '02:00:00'

但这只是返回我的每个结果，因为 TIMEDIFF 的结果总是 00:00:00

我创建了一个 SQL Fiddle为此

MySQL 5.6 架构设置:

CREATE TABLE `video_data` (
  `id` int(10) unsigned NOT NULL AUTO_INCREMENT,
  `video_id` int(10) unsigned NOT NULL,
  `shares` int(11) DEFAULT NULL,
  `likes` int(11) DEFAULT NULL,
  `comments` int(11) DEFAULT NULL,
  `total_count` int(11) DEFAULT NULL,
  `created_at` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
  `updated_at` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci;

INSERT INTO `video_data` (`id`, `video_id`, `shares`, `likes`, `comments`, `total_count`, `created_at`, `updated_at`)
VALUES
    (1889612, 245721, 777, 69922, 1314, 72013, '2015-10-04 20:00:04', '2015-10-04 20:00:04'),
    (1896986, 245721, 970, 90611, 1570, 93151, '2015-10-04 21:00:04', '2015-10-04 21:00:04'),
    (1904145, 245721, 1121, 104636, 1725, 107482, '2015-10-04 22:00:05', '2015-10-04 22:00:05'),
    (1911872, 245721, 1199, 115389, 1838, 118426, '2015-10-04 23:00:04', '2015-10-04 23:00:04'),
    (1882621, 245007, 1651, 102569, 2659, 106879, '2015-10-04 19:00:06', '2015-10-04 19:00:06'),
    (1889613, 245007, 1769, 113910, 2775, 118454, '2015-10-04 20:00:05', '2015-10-04 20:00:05'),
    (1896988, 245007, 1829, 121646, 2851, 126326, '2015-10-04 21:00:05', '2015-10-04 21:00:05'),
    (1904150, 245007, 1889, 127677, 2917, 132483, '2015-10-04 22:00:06', '2015-10-04 22:00:06'),
    (1911877, 245007, 1914, 132764, 2957, 137635, '2015-10-04 23:00:05', '2015-10-04 23:00:05'),
    (1845984, 239950, 675, 75030, 1373, 77078, '2015-10-04 12:00:04', '2015-10-04 12:00:04'),
    (1849749, 239950, 857, 97028, 1617, 99502, '2015-10-04 13:00:05', '2015-10-04 13:00:05'),
    (1853996, 239950, 1021, 113648, 1801, 116470, '2015-10-04 14:00:04', '2015-10-04 14:00:04'),
    (1858726, 239950, 1148, 126624, 1919, 129691, '2015-10-04 15:00:04', '2015-10-04 15:00:04'),
    (1863954, 239950, 1297, 137950, 2019, 141266, '2015-10-04 16:00:04', '2015-10-04 16:00:04'),
    (1869723, 239950, 1427, 148069, 2102, 151598, '2015-10-04 17:00:04', '2015-10-04 17:00:04'),
    (1875982, 239950, 1549, 156391, 2194, 160134, '2015-10-04 18:00:05', '2015-10-04 18:00:05'),
    (1882622, 239950, 1618, 161312, 2232, 165162, '2015-10-04 19:00:07', '2015-10-04 19:00:07'),
    (1889616, 239950, 1683, 164783, 2261, 168727, '2015-10-04 20:00:06', '2015-10-04 20:00:06'),
    (1896990, 239950, 1722, 167718, 2278, 171718, '2015-10-04 21:00:06', '2015-10-04 21:00:06'),
    (1904151, 239950, 1743, 170240, 2290, 174273, '2015-10-04 22:00:07', '2015-10-04 22:00:07'),
    (1911880, 239950, 1761, 172363, 2300, 176424, '2015-10-04 23:00:06', '2015-10-04 23:00:06');

当我现在执行查询时

select avg(pd.shares) AS shares, avg(pd.likes) AS likes, avg(pd.comments) AS comments FROM video_data pd JOIN video_data pd1 ON pd1.video_id = pd.`video_id` AND TIMEDIFF(pd.created_at, pd1.created_at) <= '02:00:00';

+-----------+-------------+-----------+
|  shares   |    likes    | comments  |
+-----------+-------------+-----------+
| 1298.2077 | 123542.5769 | 2032.2769 |
+-----------+-------------+-----------+

但是当查看结果时，likes 值似乎是数据库中ALL 喜欢的平均值，而不仅仅是相隔仅 2 小时的那些从彼此，对不对？还是正确的？

最佳答案

select t.*,avg(t1.views) from videos t join videos t1 on
t1.video_id=t.video_id 
and timediff(t.created_at,t1.created_at)< '02:00:00' 
group by t.video_id

尝试这个查询它应该工作

关于php - 获取特定时间范围内的数据库记录，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/36862018/