Mysql
为了说明它是如何工作的,我准备了一个请求,显示计算结果Mysql ,mysql,sql,select,group-by,Mysql,Sql,Select,Group By,为了说明它是如何工作的,我准备了一个请求,显示计算结果 select dt_record, minute(dt_record) as mm, SECOND(dt_record) as ss, UNIX_TIMESTAMP(dt_record) as uxt, UNIX_TIMESTAMP(dt_record) mod 7 as ux7, FROM_UNIXTIME( UNIX_TIMESTAMP(dt_record) - UNIX_TIMESTAMP(dt_record) mod 7)
select dt_record, minute(dt_record) as mm, SECOND(dt_record) as ss,
UNIX_TIMESTAMP(dt_record) as uxt, UNIX_TIMESTAMP(dt_record) mod 7 as ux7,
FROM_UNIXTIME(
UNIX_TIMESTAMP(dt_record) - UNIX_TIMESTAMP(dt_record) mod 7) as dtsub,
column from `yourtable` where dt_record>='2016-11-13 05:00:00'
and dt_record < '2016-11-13 05:02:00';
+---------------------+--------------------+
| dt | avg(column) |
+---------------------+--------------------+
| 2016-11-13 04:59:43 | 25434.85714285714 |
| 2016-11-13 05:00:42 | 5700.728813559322 |
| 2016-11-13 05:01:41 | 950.1016949152543 |
| 2016-11-13 05:02:40 | 4671.220338983051 |
| 2016-11-13 05:03:39 | 25468.728813559323 |
| 2016-11-13 05:04:38 | 43883.52542372881 |
| 2016-11-13 05:05:37 | 24589.338983050846 |
+---------------------+--------------------+
+---------------------+-----+-----+------------+------+---------------------+----------+
| dt_record | mm | ss | uxt | ux7 | dtsub | column |
+---------------------+------+-----+------------+------+---------------------+----------+
| 2016-11-13 05:00:00 | 0 | 0 | 1479002400 | 1 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:01 | 0 | 1 | 1479002401 | 2 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:02 | 0 | 2 | 1479002402 | 3 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:03 | 0 | 3 | 1479002403 | 4 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:04 | 0 | 4 | 1479002404 | 5 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:05 | 0 | 5 | 1479002405 | 6 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:06 | 0 | 6 | 1479002406 | 0 | 2016-11-13 05:00:06 | 33726 |
| 2016-11-13 05:00:07 | 0 | 7 | 1479002407 | 1 | 2016-11-13 05:00:06 | 32581 |
| 2016-11-13 05:00:08 | 0 | 8 | 1479002408 | 2 | 2016-11-13 05:00:06 | 32581 |
| 2016-11-13 05:00:09 | 0 | 9 | 1479002409 | 3 | 2016-11-13 05:00:06 | 31475 |
+---------------------+-----+-----+------------+------+---------------------+----------+
选择dt_记录,分钟(dt_记录)为毫米,秒(dt_记录)为秒,
UNIX_时间戳(dt_记录)为uxt,UNIX_时间戳(dt_记录)mod 7为ux7,
从uUnixtime(
UNIX_时间戳(dt_记录)-UNIX_时间戳(dt_记录)mod 7)作为dtsub,
“yourtable”中的列,其中dt_记录>='2016-11-13 05:00:00'
和dt_记录<'2016-11-13 05:02:00';
+---------------------+--------------------+
|dt |平均值(列)|
+---------------------+--------------------+
| 2016-11-13 04:59:43 | 25434.85714285714 |
| 2016-11-13 05:00:42 | 5700.728813559322 |
| 2016-11-13 05:01:41 | 950.1016949152543 |
| 2016-11-13 05:02:40 | 4671.220338983051 |
| 2016-11-13 05:03:39 | 25468.728813559323 |
| 2016-11-13 05:04:38 | 43883.52542372881 |
| 2016-11-13 05:05:37 | 24589.338983050846 |
+---------------------+--------------------+
+---------------------+-----+-----+------------+------+---------------------+----------+
|dt|U记录| mm | ss | uxt | ux7 | dtsub |列|
+---------------------+------+-----+------------+------+---------------------+----------+
| 2016-11-13 05:00:00 | 0 | 0 | 1479002400 | 1 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:01 | 0 | 1 | 1479002401 | 2 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:02 | 0 | 2 | 1479002402 | 3 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:03 | 0 | 3 | 1479002403 | 4 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:04 | 0 | 4 | 1479002404 | 5 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:05 | 0 | 5 | 1479002405 | 6 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:06 | 0 | 6 | 1479002406 | 0 | 2016-11-13 05:00:06 | 33726 |
| 2016-11-13 05:00:07 | 0 | 7 | 1479002407 | 1 | 2016-11-13 05:00:06 | 32581 |
| 2016-11-13 05:00:08 | 0 | 8 | 1479002408 | 2 | 2016-11-13 05:00:06 | 32581 |
| 2016-11-13 05:00:09 | 0 | 9 | 1479002409 | 3 | 2016-11-13 05:00:06 | 31475 |
+---------------------+-----+-----+------------+------+---------------------+----------+
有人能提出更快的建议吗?太好了!这正是我所需要的!非常感谢!请完成查询。我无法使用此解决方案存档OP结果。感谢您提出此解决方案,帮了我很多忙!好东西!我现在所需要的只是一种方法,当时间桶中没有样本时,它可以记录一个“零”行…@DanielRhodes有没有想过这个? +---------------------+-----------------+ | 2010-06-15 23:35:00 | 1 | # This is the sum for the 00 - 30 seconds range | 2010-06-15 23:35:30 | 7544 | # This is the sum for the 30 - 60 seconds range | 2010-06-17 10:39:35 | 450 | # This is the sum for the 30 - 60 seconds range +---------------------+-----------------+
select
min(ts),
user_name,
sum(measure) / 27
from metric_table
where
ts between date_sub('2015-03-17 00:00:00', INTERVAL 2160 MINUTE) and '2015-03-17 00:00:00'
group by unix_timestamp(ts) div 1620, user_name
order by ts, user_name
;
select
from_unixtime(unix_timestamp(ts) - unix_timestamp(ts) mod 1620) as ts1,
user_name,
sum(measure) / 27
from metric_table
where
ts between date_sub('2015-03-17 00:00:00', INTERVAL 2160 MINUTE) and '2015-03-17 00:00:00'
group by ts1, user_name
order by ts1, user_name
;
select convert(
(min(dt_record) div 50)*50 - 20*((convert(min(dt_record),
datetime) div 50) mod 2), datetime) as dt,
avg(1das4hrz)
from `meteor-m2_msgi`
where dt_record>='2016-11-13 05:00:00'
and dt_record < '2016-11-14 00:00:00'
group by convert(dt_record, datetime) div 50;
select (
convert(
min(dt_record), datetime) div 50)*50 - 20*(
(convert(min(dt_record), datetime) div 50) mod 2
) as dt,
avg(column) from `your_table`
where dt_record>='2016-11-13 05:00:00'
and dt_record < '2016-11-14 00:00:00'
group by convert(dt_record, datetime) div 50;
select FROM_UNIXTIME(
UNIX_TIMESTAMP(dt_record) - UNIX_TIMESTAMP(dt_record) mod 7
) as dt, avg(1das4hrz) from `meteor-m2_msgi`
where dt_record>='2016-11-13 05:00:00'
and dt_record < '2016-11-13 05:02:00'
group by FROM_UNIXTIME(
UNIX_TIMESTAMP(dt_record) - UNIX_TIMESTAMP(dt_record) mod 7);
select dt_record, minute(dt_record) as mm, SECOND(dt_record) as ss,
UNIX_TIMESTAMP(dt_record) as uxt, UNIX_TIMESTAMP(dt_record) mod 7 as ux7,
FROM_UNIXTIME(
UNIX_TIMESTAMP(dt_record) - UNIX_TIMESTAMP(dt_record) mod 7) as dtsub,
column from `yourtable` where dt_record>='2016-11-13 05:00:00'
and dt_record < '2016-11-13 05:02:00';
+---------------------+--------------------+
| dt | avg(column) |
+---------------------+--------------------+
| 2016-11-13 04:59:43 | 25434.85714285714 |
| 2016-11-13 05:00:42 | 5700.728813559322 |
| 2016-11-13 05:01:41 | 950.1016949152543 |
| 2016-11-13 05:02:40 | 4671.220338983051 |
| 2016-11-13 05:03:39 | 25468.728813559323 |
| 2016-11-13 05:04:38 | 43883.52542372881 |
| 2016-11-13 05:05:37 | 24589.338983050846 |
+---------------------+--------------------+
+---------------------+-----+-----+------------+------+---------------------+----------+
| dt_record | mm | ss | uxt | ux7 | dtsub | column |
+---------------------+------+-----+------------+------+---------------------+----------+
| 2016-11-13 05:00:00 | 0 | 0 | 1479002400 | 1 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:01 | 0 | 1 | 1479002401 | 2 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:02 | 0 | 2 | 1479002402 | 3 | 2016-11-13 04:59:59 | 36137 |
| 2016-11-13 05:00:03 | 0 | 3 | 1479002403 | 4 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:04 | 0 | 4 | 1479002404 | 5 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:05 | 0 | 5 | 1479002405 | 6 | 2016-11-13 04:59:59 | 34911 |
| 2016-11-13 05:00:06 | 0 | 6 | 1479002406 | 0 | 2016-11-13 05:00:06 | 33726 |
| 2016-11-13 05:00:07 | 0 | 7 | 1479002407 | 1 | 2016-11-13 05:00:06 | 32581 |
| 2016-11-13 05:00:08 | 0 | 8 | 1479002408 | 2 | 2016-11-13 05:00:06 | 32581 |
| 2016-11-13 05:00:09 | 0 | 9 | 1479002409 | 3 | 2016-11-13 05:00:06 | 31475 |
+---------------------+-----+-----+------------+------+---------------------+----------+