我正在研究一個MySQL數據庫系統，該系統可讓我的公司在目前所用時間的一小部分內處理我們的行程時間調查數據。我已經得到了下面的MySQL命令，做計算：按時間間隔對查詢結果進行分組聚合

select anpr_1_unique.date as "Date", 
anpr_1_unique.NETBIOSNAME as "ID for site A", 
anpr_1_unique.time as "Timestamp at site A", 
anpr_3_unique.NETBIOSNAME as "ID for site B", 
anpr_3_unique.time as "Timestamp at site B", 
anpr_1_unique.plate as "Plate", 
if (timediff(anpr_3_unique.time,anpr_1_unique.time) like "%-%", null,timediff(anpr_3_unique.time,anpr_1_unique.time)) as "Journey time in direction 1", 
if (timediff(anpr_1_unique.time,anpr_3_unique.time) like "%-%", null,timediff(anpr_1_unique.time,anpr_3_unique.time)) as "Journey time in direction 1", 
if (timediff(anpr_1_unique.time,anpr_3_unique.time) like "%-%", "A->B","B->A") as "Direction of travel" 
from anpr_1_unique inner join anpr_3_unique on anpr_1_unique.plate=anpr_3_unique.plate 
where anpr_1_unique.date = "2013-02-26" and anpr_3_unique.date="2013-02-26" and anpr_1_unique.time like "%06:%%:%%%" order by anpr_1_unique.time

其產生的表中的格式如下：

+------------+---------------+---------------------+---------------+---------------------+---------+-----------------------------+-----------------------------+---------------------+ 
| Date  | ID for site A | Timestamp at site A | ID for site B | Timestamp at site B | Plate | Journey time in direction 1 | Journey time in direction 1 | Direction of travel | 
+------------+---------------+---------------------+---------------+---------------------+---------+-----------------------------+-----------------------------+---------------------+ 
| 2013-02-26 | Farnham N 1 | 06:50:52   | Farnham S  | 06:54:32   | LS60JAO | 00:03:40     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:51:33   | Farnham S  | 06:53:32   | FH53WGW | 00:01:59     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:51:51   | Farnham S  | 06:54:23   | V987USD | 00:02:32     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:52:17   | Farnham S  | 06:54:28   | BK61RNY | 00:02:11     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:52:30   | Farnham S  | 06:54:35   | WU59SXP | 00:02:05     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:53:02   | Farnham S  | 12:23:33   | NA08UKV | 05:30:31     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:53:44   | Farnham S  | 06:56:09   | KC04CTF | 00:02:25     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:53:46   | Farnham S  | 06:56:11   | LL58YAJ | 00:02:25     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:54:41   | Farnham S  | 06:57:44   | AP57CWE | 00:03:03     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:54:46   | Farnham S  | 14:55:29   | EU55LRF | 08:00:43     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:55:13   | Farnham S  | 06:58:08   | AJ60KVK | 00:02:55     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:55:19   | Farnham S  | 06:58:44   | T96ALO | 00:03:25     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:55:57   | Farnham S  | 06:58:46   | F604WNV | 00:02:49     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:56:22   | Farnham S  | 06:58:50   | S905AAP | 00:02:28     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:56:52   | Farnham S  | 06:59:35   | LO08SKV | 00:02:43     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:56:55   | Farnham S  | 06:59:37   | KT53TNK | 00:02:42     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:57:45   | Farnham S  | 07:00:33   | LC60EOR | 00:02:48     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:58:44   | Farnham S  | 07:06:15   | S278VNA | 00:07:31     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:58:49   | Farnham S  | 07:00:46   | X906GVT | 00:01:57     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:59:15   | Farnham S  | 07:01:35   | YS11AWP | 00:02:20     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:59:44   | Farnham S  | 07:01:46   | LP12NWA | 00:02:02     | NULL      | A->B    | 
| 2013-02-26 | Farnham N 1 | 06:59:59   | Farnham S  | 07:02:29   | RJ11BUA | 00:02:30     | NULL      | A->B    | 
+------------+---------------+---------------------+---------------+---------------------+---------+-----------------------------+-----------------------------+---------------------+ 
22 rows in set (0.09 sec)

這僅僅是一個結果的10分鐘的樣品。我對此感到滿意，以及它是如何發生的，但是我希望能夠將這些結果分組爲5,10或15分鐘的聚合期間。

我已經在本網站和其他網站上尋找其他潛在解決方案，最值得注意的是建議使用GROUP BY UNIX_TIMESTAMP(<time_stamp>) DIV <time>來產生聚合。我已經試過這個，並且它不適用於這個查詢。

我能做些什麼來有效地聚合這些數據？可以用我製作的查詢來完成，還是需要重寫？

更新

我設法計算做大致我想用下面的SQL代碼：

select 
anpr_1_unique.date as "Date", 
str_to_date(concat(date_format(anpr_1_unique.time, '%H'),':',(floor(date_format(anpr_1_unique.time, '%i')/30)*30), ':00'), '%H:%i:%s') as starttime, 
anpr_1_unique.NETBIOSNAME as "ID for site A", 
anpr_3_unique.NETBIOSNAME as "ID for site B", 
if (avg(timediff(anpr_3_unique.time,anpr_1_unique.time) like "%-%"), null,time(avg(timediff(anpr_3_unique.time,anpr_1_unique.time)))) as "Journey time in direction A->B" 
from anpr_1_unique 
inner join anpr_3_unique on anpr_1_unique.plate=anpr_3_unique.plate 
where anpr_1_unique.date = "2013-02-26" and anpr_3_unique.date="2013-02-26" 
and timediff(anpr_3_unique.time,anpr_1_unique.time) between "00:00:00" and "00:30:00" 
GROUP BY starttime; 
show warnings;

產生的數據是這樣的：但是

+------------+-----------+---------------+---------------+---------------------------------+ 
| Date  | starttime | ID for site A | ID for site B | Journey time in direction A->B | 
+------------+-----------+---------------+---------------+---------------------------------+ 
| 2013-02-26 | 06:30:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 07:00:00 | Farnham N 1 | Farnham S  | 00:03:46.3276 | 
| 2013-02-26 | 07:30:00 | Farnham N 1 | Farnham S  | 00:04:51.5588 | 
| 2013-02-26 | 08:00:00 | Farnham N 1 | Farnham S  | 00:11:10.8462 | 
| 2013-02-26 | 08:30:00 | Farnham N 1 | Farnham S  | 00:11:36.6410 | 
| 2013-02-26 | 09:00:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 09:30:00 | Farnham N 1 | Farnham S  | 00:05:39.0714 | 
| 2013-02-26 | 10:00:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 10:30:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 11:00:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 11:30:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 12:00:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 12:30:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 13:00:00 | Farnham N 1 | Farnham S  | 00:05:17.1250 | 
| 2013-02-26 | 13:30:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 14:00:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 14:30:00 | Farnham N 1 | Farnham S  | 00:05:06.8864 | 
| 2013-02-26 | 15:00:00 | Farnham N 1 | Farnham S  | 00:09:07.2308 | 
| 2013-02-26 | 15:30:00 | Farnham N 1 | Farnham S  | 00:13:02.2558 | 
| 2013-02-26 | 16:00:00 | Farnham N 1 | Farnham S  | NULL   | 
| 2013-02-26 | 16:30:00 | Farnham N 1 | Farnham S  | 00:26:45.7143 | 
| 2013-02-26 | 17:30:00 | Farnham N 1 | Farnham S  | 00:28:04.0000 | 
| 2013-02-26 | 18:00:00 | Farnham N 1 | Farnham S  | 00:22:56.0667 | 
| 2013-02-26 | 18:30:00 | Farnham N 1 | Farnham S  | NULL   | 
+------------+-----------+---------------+---------------+---------------------------------+

，如如圖所示，這會在應該有數據的地方生成一些NULL結果。警告顯示相同數量的「| Warning | 1292 | Truncated incorrect time value: '(number)' |」消息。在計算時，我遇到了類似的問題，我通過使用timediff()命令而不是手動計算來解決這個問題。我不確定我現在可以用這個辦法來「解除」這些結果。

有什麼建議我現在可以在這裏做什麼？

來源

2013-10-10 almg

顯示您嘗試的查詢。 – Barmar

你需要圍繞你的除法結果。做到這一點與地板，細胞或圓形

GROUP BY floor(UNIX_TIMESTAMP(<time_stamp>)/(seconds*minutes)) 

GROUP BY floor(UNIX_TIMESTAMP(<time_stamp>)/(60*15)) - group into 15 minute intervals

具體;

GROUP BY floor(UNIX_TIMESTAMP(CONCAT(anpr_1_unique.date, ' ', npr_1_unique.time))/(60*15))

來源

2013-10-10 15:58:33 AdrianBR

道歉，如果我是鈍的。我應該在那個命令中使用？我試着在上面的查詢結尾處使用'group by'命令，並使用anpr_1_unique.time以及實際計算（'timediff（anpr_3_unique.time，anpr_1_unique.time）'）。這兩個都沒有工作 – almg

CONCAT（anpr_1_unique.date，''，anpr_1_unique.time）獲取時間戳 – AdrianBR

按時間間隔對查詢結果進行分組聚合

更新

回答

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