获取特定时间范围内的数据库记录

Question

让我们假设我有下表，称为video_data。我有另外一个videos，但它并不真正相关。我用它来查询特定频道的视频，但这不会改变查询。这只是为了获得一个通道的计算而不是全部。

+----+----------+-------+---------------------+ 
| 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 | 
+----+----------+-------+---------------------+ 

我现在想要做的是获得时间范围内视图的平均值。比方说，我想获得视频在2小时内的平均观看次数。以video_ 1为例

因此，我需要做的是以下几点。我需要得到id: 1和id: 4的平均值。这将是1250，因为它是(1000 + 1500)/2。接下来我需要得到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分数将为2250，因为它是(1250 + 3250)/2，对吗？

现在我不知道，是如何从MySQL获得这个。它甚至可以在普通的MySQL中执行吗？我需要很多很多video_data。就像我有超过100个小时的数据！如果id: 100和id: 105的数据相距不到两个小时，我仍然需要计算这些数据。

我想要做它在某种程度上是这样

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一个结果，因为TIMEDIFF结果总是00:00:00

我这个

创建SQL Fiddle的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'); 

现在当我执行查询

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 | 
+-----------+-------------+-----------+ 

但会在它看起来像likes值的结果时是ALL喜欢在数据库中的平均水平，而不仅仅是那些只有谁是2相隔几小时，对吧？或者它是正确的？

Answer 1

但这只是返回我每次的结果，因为TIMEDIFF的结果总是00:00:00

它这样做becauase你使用相同的列：

TIMEDIFF(`created_at`, `created_at`) 

所以它的几乎不可能使它产生不同的结果。您可能想使用NOW()作为参数之一？

Answer 2

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 

尝试此查询它应该工作