SQL：第一次和最后一次出现之间的行数 - 有一个扭曲
SQL: Count of rows between first and last occurrence - with a twist
我想计算值第一次出现和最后一次出现之间的行数。但是，当它们之间有五个或更多个不同值的记录时，停止计数。
所以如果最后一次出现是今天，第一次出现是昨天，结果将是 2（今天加上昨天）。
如果最后一次出现是在今天，第一次出现是在 8 天前，并且两者之间没有出现，则结果将为“1”。但是，如果 3 天前发生另一次事件，结果将是 4（3+2+1 天前加上今天）。
我希望这是有道理的。
这是我的数据
Date City Weather
==============================
2018-08-11 Ankara Sun
2018-08-10 Ankara Sun
2018-08-09 Ankara Sun
2018-08-08 Ankara Sun
2018-08-07 Ankara Sun
2018-08-06 Ankara Sun
2018-08-05 Ankara Rain
2018-08-04 Ankara Clouds
2018-08-03 Ankara Rain
2018-08-02 Ankara Sun
2018-08-01 Ankara Sun
2018-08-11 Cairo Clouds
2018-08-10 Cairo Sun
2018-08-09 Cairo Sun
2018-08-08 Cairo Sun
2018-08-07 Cairo Sun
2018-08-06 Cairo Sun
2018-08-05 Cairo Clouds
2018-08-04 Cairo Sun
2018-08-03 Cairo Sun
2018-08-02 Cairo Sun
2018-08-01 Cairo Sun
我要查询的是 return 给定城市的查询，并记录当天的天气和自该天气首次出现以来的天数。但是，如果有五天或更长时间的间隔，则从 1 重新开始计数。
就像在 11th Aug 上查询 Ankara 它会 return 11 因为自 Sun 第一次出现以来已经 11 天（包括今天） .
但是对于 11th Aug 上的 Cairo 它会 return 1 而不是 7 因为它在 Clouds 之间已经超过 5 天了8 月 5 日和今天 Clouds。
我已经用 first_value()、LEAD、LAG 和 ROW_NUMBER 尝试了很多东西，但没有任何意义，因为它们都惨败。
反正就在这里...
select
city, val,datediff(day, min(datadate), '2018-10-30') + 1 as DaysPresent
from d
where val = last_val
group by city,val;
或...
select
date, city, weather, datediff(day,ca.prior,d.date)+1 as daysPresent
from d
cross apply (
select min(prev.date) as prior
from d as prev
where prev.city = d.city
and prev.date between dateadd(day,-4,d.date) and dateadd(day,0,d.date)
and prev.weather = d.weather
) ca
order by city,date
预期结果
+----+---------------------+--------+---------+----------------+-------------+----------+----------------------------
| | date | city | weather | prior_the_same | prior_types |expected | why?
+----+---------------------+--------+---------+----------------+-------------+----------+----------------------------
| 1 | 11.08.2018 00:00:00 | Ankara | Sun | 5 | 2 | 11 | 11t day since 1st time Sun
| 2 | 10.08.2018 00:00:00 | Ankara | Sun | 4 | 3 | 10 | 10t day since 1st time Sun
| 3 | 09.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | 9 | 9th day since 1st time Sun
| 4 | 08.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | 8 | 8th day since 1st time Sun
| 5 | 07.08.2018 00:00:00 | Ankara | Sun | 6 | 3 | 7 | 7th day since 1st time Sun
| 6 | 06.08.2018 00:00:00 | Ankara | Sun | 5 | 3 | 6 | 6th day since 1st time Sun ( <5 days gap since last Sun keeps counting )
| 7 | 05.08.2018 00:00:00 | Ankara | Rain | 2 | 3 | 3 | 3rd day since 1st time Rain
| 8 | 04.08.2018 00:00:00 | Ankara | Clouds | 0 | 3 | 1 | 1st day Clouds
| 9 | 03.08.2018 00:00:00 | Ankara | Rain | 0 | 2 | 1 | 1st day Rain
| 10 | 02.08.2018 00:00:00 | Ankara | Sun | 1 | 0 | 2 | 2nd day since 1st time Sun
| 11 | 01.08.2018 00:00:00 | Ankara | Sun | 0 | 0 | 1 | 1st day Sun
| 12 | 11.08.2018 00:00:00 | Cairo | Clouds | 6 | 6 | 1 | 1st time Clouds ( >5 days gap since last Clouds resets the count )
| 13 | 10.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 10 | 10t day since 1st time Sun
| 14 | 09.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 9 | 9th day since 1st time Sun
| 15 | 08.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 8 | 8th day since 1st time Sun
| 16 | 07.08.2018 00:00:00 | Cairo | Sun | 6 | 1 | 7 | 7th day since 1st time Sun
| 17 | 06.08.2018 00:00:00 | Cairo | Sun | 5 | 1 | 6 | 6th day since 1st time Sun ( <5 days gap since last Sun keeps counting )
| 18 | 05.08.2018 00:00:00 | Cairo | Clouds | 0 | 4 | 1 | 1st time Clouds
| 19 | 04.08.2018 00:00:00 | Cairo | Sun | 3 | 0 | 4 | 4th day since 1st time Sun
| 20 | 03.08.2018 00:00:00 | Cairo | Sun | 2 | 0 | 3 | 3rd day since 1st time Sun
| 21 | 02.08.2018 00:00:00 | Cairo | Sun | 1 | 0 | 2 | 2nd day since 1st time Sun
| 22 | 01.08.2018 00:00:00 | Cairo | Sun | 0 | 0 | 1 | 1st day Sun
+----+---------------------+--------+---------+----------------+-------------+----------+----------------------------
最新
declare @day_range integer = 5;
select
t.date, t.city, t.weather
, datediff(day,ca1.prior_dt,t.date)+1 as prior_the_same
, twist.prior_types
, twist.prior_mx_dt
from mytable t
cross apply (
select count(prev.weather) as prior_types, max(prev.date) as prior_mx_dt
from mytable as prev
where prev.city = t.city
and prev.date between dateadd(day,-@day_range,t.date) and t.date
and prev.weather <> t.weather
) twist
cross apply (
select min(prev.date) as prior_dt
from mytable as prev
where prev.city = t.city
and (twist.prior_types < @day_range or prev.date >= twist.prior_mx_dt)
and prev.weather = t.weather
) ca1
order by t.city, t.date DESC
结果：
+----+---------------------+--------+---------+----------------+-------------+---------------------+
| | date | city | weather | prior_the_same | prior_types | prior_mx_dt |
+----+---------------------+--------+---------+----------------+-------------+---------------------+
| 1 | 11.08.2018 00:00:00 | Ankara | Sun | 11 | 0 | NULL |
| 2 | 10.08.2018 00:00:00 | Ankara | Sun | 10 | 1 | 05.08.2018 00:00:00 |
| 3 | 09.08.2018 00:00:00 | Ankara | Sun | 9 | 2 | 05.08.2018 00:00:00 |
| 4 | 08.08.2018 00:00:00 | Ankara | Sun | 8 | 3 | 05.08.2018 00:00:00 |
| 5 | 07.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | 05.08.2018 00:00:00 |
| 6 | 06.08.2018 00:00:00 | Ankara | Sun | 6 | 3 | 05.08.2018 00:00:00 |
| 7 | 05.08.2018 00:00:00 | Ankara | Rain | 3 | 3 | 04.08.2018 00:00:00 |
| 8 | 04.08.2018 00:00:00 | Ankara | Clouds | 1 | 3 | 03.08.2018 00:00:00 |
| 9 | 03.08.2018 00:00:00 | Ankara | Rain | 1 | 2 | 02.08.2018 00:00:00 |
| 10 | 02.08.2018 00:00:00 | Ankara | Sun | 2 | 0 | NULL |
| 11 | 01.08.2018 00:00:00 | Ankara | Sun | 1 | 0 | NULL |
| 12 | 11.08.2018 00:00:00 | Cairo | Clouds | 1 | 5 | 10.08.2018 00:00:00 |
| 13 | 10.08.2018 00:00:00 | Cairo | Sun | 10 | 1 | 05.08.2018 00:00:00 |
| 14 | 09.08.2018 00:00:00 | Cairo | Sun | 9 | 1 | 05.08.2018 00:00:00 |
| 15 | 08.08.2018 00:00:00 | Cairo | Sun | 8 | 1 | 05.08.2018 00:00:00 |
| 16 | 07.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 05.08.2018 00:00:00 |
| 17 | 06.08.2018 00:00:00 | Cairo | Sun | 6 | 1 | 05.08.2018 00:00:00 |
| 18 | 05.08.2018 00:00:00 | Cairo | Clouds | 1 | 4 | 04.08.2018 00:00:00 |
| 19 | 04.08.2018 00:00:00 | Cairo | Sun | 4 | 0 | NULL |
| 20 | 03.08.2018 00:00:00 | Cairo | Sun | 3 | 0 | NULL |
| 21 | 02.08.2018 00:00:00 | Cairo | Sun | 2 | 0 | NULL |
| 22 | 01.08.2018 00:00:00 | Cairo | Sun | 1 | 0 | NULL |
在线查看：https://rextester.com/ZSHT63407
原创
样本数据为：
CREATE TABLE mytable(
Date DATE NOT NULL
,City VARCHAR(6) NOT NULL
,Weather VARCHAR(6) NOT NULL
);
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-11','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-10','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-09','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-08','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-07','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-06','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-05','Ankara','Rain');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-04','Ankara','Clouds');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-03','Ankara','Rain');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-02','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-01','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-11','Cairo','Clouds');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-10','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-09','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-08','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-07','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-06','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-05','Cairo','Clouds');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-04','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-03','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-02','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-01','Cairo','Sun');
使用这个查询：
declare @day_range integer = 7;
declare @ignore_range integer = 5;
select
t.date, t.city, t.weather
, datediff(day,ca1.prior_dt,t.date) as prior_the_same
, ca2.prior_types
from mytable t
cross apply (
select min(prev.date) as prior_dt
from mytable as prev
where prev.city = t.city
and prev.date between dateadd(day,-@day_range,t.date) and t.date
and prev.weather = t.weather
) ca1
cross apply (
select count(prev.weather) as prior_types
from mytable as prev
where prev.city = t.city
and prev.date between dateadd(day,-@day_range,t.date) and t.date
and prev.weather <> t.weather
) ca2
order by t.city, t.date DESC
结果如下：
+----+---------------------+--------+---------+----------------+-------------+----------+
| | date | city | weather | prior_the_same | prior_types |expected? |
+----+---------------------+--------+---------+----------------+-------------+----------+
| 1 | 11.08.2018 00:00:00 | Ankara | Sun | 5 | 2 | |
| 2 | 10.08.2018 00:00:00 | Ankara | Sun | 4 | 3 | |
| 3 | 09.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | |
| 4 | 08.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | |
| 5 | 07.08.2018 00:00:00 | Ankara | Sun | 6 | 3 | |
| 6 | 06.08.2018 00:00:00 | Ankara | Sun | 5 | 3 | |
| 7 | 05.08.2018 00:00:00 | Ankara | Rain | 2 | 3 | |
| 8 | 04.08.2018 00:00:00 | Ankara | Clouds | 0 | 3 | |
| 9 | 03.08.2018 00:00:00 | Ankara | Rain | 0 | 2 | |
| 10 | 02.08.2018 00:00:00 | Ankara | Sun | 1 | 0 | |
| 11 | 01.08.2018 00:00:00 | Ankara | Sun | 0 | 0 | |
| 12 | 11.08.2018 00:00:00 | Cairo | Clouds | 6 | 6 | |
| 13 | 10.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | |
| 14 | 09.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | |
| 15 | 08.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | |
| 16 | 07.08.2018 00:00:00 | Cairo | Sun | 6 | 1 | |
| 17 | 06.08.2018 00:00:00 | Cairo | Sun | 5 | 1 | |
| 18 | 05.08.2018 00:00:00 | Cairo | Clouds | 0 | 4 | |
| 19 | 04.08.2018 00:00:00 | Cairo | Sun | 3 | 0 | |
| 20 | 03.08.2018 00:00:00 | Cairo | Sun | 2 | 0 | |
| 21 | 02.08.2018 00:00:00 | Cairo | Sun | 1 | 0 | |
| 22 | 01.08.2018 00:00:00 | Cairo | Sun | 0 | 0 | |
+----+---------------------+--------+---------+----------------+-------------+----------+
您在不止一个问题上扩展了您的要求。我可以建议您考虑以上内容并决定是否可以使用这 2 个计算来得出想要的最终结果。如果您仍然无法得出结论，请使用文本 table 格式将 "expected result" 作为新列包含在内
我想计算值第一次出现和最后一次出现之间的行数。但是，当它们之间有五个或更多个不同值的记录时，停止计数。
所以如果最后一次出现是今天，第一次出现是昨天，结果将是 2（今天加上昨天）。
如果最后一次出现是在今天，第一次出现是在 8 天前，并且两者之间没有出现，则结果将为“1”。但是，如果 3 天前发生另一次事件，结果将是 4（3+2+1 天前加上今天）。
我希望这是有道理的。
这是我的数据
Date City Weather
==============================
2018-08-11 Ankara Sun
2018-08-10 Ankara Sun
2018-08-09 Ankara Sun
2018-08-08 Ankara Sun
2018-08-07 Ankara Sun
2018-08-06 Ankara Sun
2018-08-05 Ankara Rain
2018-08-04 Ankara Clouds
2018-08-03 Ankara Rain
2018-08-02 Ankara Sun
2018-08-01 Ankara Sun
2018-08-11 Cairo Clouds
2018-08-10 Cairo Sun
2018-08-09 Cairo Sun
2018-08-08 Cairo Sun
2018-08-07 Cairo Sun
2018-08-06 Cairo Sun
2018-08-05 Cairo Clouds
2018-08-04 Cairo Sun
2018-08-03 Cairo Sun
2018-08-02 Cairo Sun
2018-08-01 Cairo Sun
我要查询的是 return 给定城市的查询，并记录当天的天气和自该天气首次出现以来的天数。但是，如果有五天或更长时间的间隔，则从 1 重新开始计数。
就像在 11th Aug 上查询 Ankara 它会 return 11 因为自 Sun 第一次出现以来已经 11 天（包括今天） .
但是对于 11th Aug 上的 Cairo 它会 return 1 而不是 7 因为它在 Clouds 之间已经超过 5 天了8 月 5 日和今天 Clouds。
我已经用 first_value()、LEAD、LAG 和 ROW_NUMBER 尝试了很多东西，但没有任何意义，因为它们都惨败。
反正就在这里...
select
city, val,datediff(day, min(datadate), '2018-10-30') + 1 as DaysPresent
from d
where val = last_val
group by city,val;
或...
select
date, city, weather, datediff(day,ca.prior,d.date)+1 as daysPresent
from d
cross apply (
select min(prev.date) as prior
from d as prev
where prev.city = d.city
and prev.date between dateadd(day,-4,d.date) and dateadd(day,0,d.date)
and prev.weather = d.weather
) ca
order by city,date
预期结果
+----+---------------------+--------+---------+----------------+-------------+----------+----------------------------
| | date | city | weather | prior_the_same | prior_types |expected | why?
+----+---------------------+--------+---------+----------------+-------------+----------+----------------------------
| 1 | 11.08.2018 00:00:00 | Ankara | Sun | 5 | 2 | 11 | 11t day since 1st time Sun
| 2 | 10.08.2018 00:00:00 | Ankara | Sun | 4 | 3 | 10 | 10t day since 1st time Sun
| 3 | 09.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | 9 | 9th day since 1st time Sun
| 4 | 08.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | 8 | 8th day since 1st time Sun
| 5 | 07.08.2018 00:00:00 | Ankara | Sun | 6 | 3 | 7 | 7th day since 1st time Sun
| 6 | 06.08.2018 00:00:00 | Ankara | Sun | 5 | 3 | 6 | 6th day since 1st time Sun ( <5 days gap since last Sun keeps counting )
| 7 | 05.08.2018 00:00:00 | Ankara | Rain | 2 | 3 | 3 | 3rd day since 1st time Rain
| 8 | 04.08.2018 00:00:00 | Ankara | Clouds | 0 | 3 | 1 | 1st day Clouds
| 9 | 03.08.2018 00:00:00 | Ankara | Rain | 0 | 2 | 1 | 1st day Rain
| 10 | 02.08.2018 00:00:00 | Ankara | Sun | 1 | 0 | 2 | 2nd day since 1st time Sun
| 11 | 01.08.2018 00:00:00 | Ankara | Sun | 0 | 0 | 1 | 1st day Sun
| 12 | 11.08.2018 00:00:00 | Cairo | Clouds | 6 | 6 | 1 | 1st time Clouds ( >5 days gap since last Clouds resets the count )
| 13 | 10.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 10 | 10t day since 1st time Sun
| 14 | 09.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 9 | 9th day since 1st time Sun
| 15 | 08.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 8 | 8th day since 1st time Sun
| 16 | 07.08.2018 00:00:00 | Cairo | Sun | 6 | 1 | 7 | 7th day since 1st time Sun
| 17 | 06.08.2018 00:00:00 | Cairo | Sun | 5 | 1 | 6 | 6th day since 1st time Sun ( <5 days gap since last Sun keeps counting )
| 18 | 05.08.2018 00:00:00 | Cairo | Clouds | 0 | 4 | 1 | 1st time Clouds
| 19 | 04.08.2018 00:00:00 | Cairo | Sun | 3 | 0 | 4 | 4th day since 1st time Sun
| 20 | 03.08.2018 00:00:00 | Cairo | Sun | 2 | 0 | 3 | 3rd day since 1st time Sun
| 21 | 02.08.2018 00:00:00 | Cairo | Sun | 1 | 0 | 2 | 2nd day since 1st time Sun
| 22 | 01.08.2018 00:00:00 | Cairo | Sun | 0 | 0 | 1 | 1st day Sun
+----+---------------------+--------+---------+----------------+-------------+----------+----------------------------
最新
declare @day_range integer = 5;
select
t.date, t.city, t.weather
, datediff(day,ca1.prior_dt,t.date)+1 as prior_the_same
, twist.prior_types
, twist.prior_mx_dt
from mytable t
cross apply (
select count(prev.weather) as prior_types, max(prev.date) as prior_mx_dt
from mytable as prev
where prev.city = t.city
and prev.date between dateadd(day,-@day_range,t.date) and t.date
and prev.weather <> t.weather
) twist
cross apply (
select min(prev.date) as prior_dt
from mytable as prev
where prev.city = t.city
and (twist.prior_types < @day_range or prev.date >= twist.prior_mx_dt)
and prev.weather = t.weather
) ca1
order by t.city, t.date DESC
结果：
+----+---------------------+--------+---------+----------------+-------------+---------------------+
| | date | city | weather | prior_the_same | prior_types | prior_mx_dt |
+----+---------------------+--------+---------+----------------+-------------+---------------------+
| 1 | 11.08.2018 00:00:00 | Ankara | Sun | 11 | 0 | NULL |
| 2 | 10.08.2018 00:00:00 | Ankara | Sun | 10 | 1 | 05.08.2018 00:00:00 |
| 3 | 09.08.2018 00:00:00 | Ankara | Sun | 9 | 2 | 05.08.2018 00:00:00 |
| 4 | 08.08.2018 00:00:00 | Ankara | Sun | 8 | 3 | 05.08.2018 00:00:00 |
| 5 | 07.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | 05.08.2018 00:00:00 |
| 6 | 06.08.2018 00:00:00 | Ankara | Sun | 6 | 3 | 05.08.2018 00:00:00 |
| 7 | 05.08.2018 00:00:00 | Ankara | Rain | 3 | 3 | 04.08.2018 00:00:00 |
| 8 | 04.08.2018 00:00:00 | Ankara | Clouds | 1 | 3 | 03.08.2018 00:00:00 |
| 9 | 03.08.2018 00:00:00 | Ankara | Rain | 1 | 2 | 02.08.2018 00:00:00 |
| 10 | 02.08.2018 00:00:00 | Ankara | Sun | 2 | 0 | NULL |
| 11 | 01.08.2018 00:00:00 | Ankara | Sun | 1 | 0 | NULL |
| 12 | 11.08.2018 00:00:00 | Cairo | Clouds | 1 | 5 | 10.08.2018 00:00:00 |
| 13 | 10.08.2018 00:00:00 | Cairo | Sun | 10 | 1 | 05.08.2018 00:00:00 |
| 14 | 09.08.2018 00:00:00 | Cairo | Sun | 9 | 1 | 05.08.2018 00:00:00 |
| 15 | 08.08.2018 00:00:00 | Cairo | Sun | 8 | 1 | 05.08.2018 00:00:00 |
| 16 | 07.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | 05.08.2018 00:00:00 |
| 17 | 06.08.2018 00:00:00 | Cairo | Sun | 6 | 1 | 05.08.2018 00:00:00 |
| 18 | 05.08.2018 00:00:00 | Cairo | Clouds | 1 | 4 | 04.08.2018 00:00:00 |
| 19 | 04.08.2018 00:00:00 | Cairo | Sun | 4 | 0 | NULL |
| 20 | 03.08.2018 00:00:00 | Cairo | Sun | 3 | 0 | NULL |
| 21 | 02.08.2018 00:00:00 | Cairo | Sun | 2 | 0 | NULL |
| 22 | 01.08.2018 00:00:00 | Cairo | Sun | 1 | 0 | NULL |
在线查看：https://rextester.com/ZSHT63407
原创
样本数据为：
CREATE TABLE mytable(
Date DATE NOT NULL
,City VARCHAR(6) NOT NULL
,Weather VARCHAR(6) NOT NULL
);
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-11','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-10','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-09','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-08','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-07','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-06','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-05','Ankara','Rain');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-04','Ankara','Clouds');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-03','Ankara','Rain');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-02','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-01','Ankara','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-11','Cairo','Clouds');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-10','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-09','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-08','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-07','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-06','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-05','Cairo','Clouds');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-04','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-03','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-02','Cairo','Sun');
INSERT INTO mytable(Date,City,Weather) VALUES ('2018-08-01','Cairo','Sun');
使用这个查询：
declare @day_range integer = 7;
declare @ignore_range integer = 5;
select
t.date, t.city, t.weather
, datediff(day,ca1.prior_dt,t.date) as prior_the_same
, ca2.prior_types
from mytable t
cross apply (
select min(prev.date) as prior_dt
from mytable as prev
where prev.city = t.city
and prev.date between dateadd(day,-@day_range,t.date) and t.date
and prev.weather = t.weather
) ca1
cross apply (
select count(prev.weather) as prior_types
from mytable as prev
where prev.city = t.city
and prev.date between dateadd(day,-@day_range,t.date) and t.date
and prev.weather <> t.weather
) ca2
order by t.city, t.date DESC
结果如下：
+----+---------------------+--------+---------+----------------+-------------+----------+
| | date | city | weather | prior_the_same | prior_types |expected? |
+----+---------------------+--------+---------+----------------+-------------+----------+
| 1 | 11.08.2018 00:00:00 | Ankara | Sun | 5 | 2 | |
| 2 | 10.08.2018 00:00:00 | Ankara | Sun | 4 | 3 | |
| 3 | 09.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | |
| 4 | 08.08.2018 00:00:00 | Ankara | Sun | 7 | 3 | |
| 5 | 07.08.2018 00:00:00 | Ankara | Sun | 6 | 3 | |
| 6 | 06.08.2018 00:00:00 | Ankara | Sun | 5 | 3 | |
| 7 | 05.08.2018 00:00:00 | Ankara | Rain | 2 | 3 | |
| 8 | 04.08.2018 00:00:00 | Ankara | Clouds | 0 | 3 | |
| 9 | 03.08.2018 00:00:00 | Ankara | Rain | 0 | 2 | |
| 10 | 02.08.2018 00:00:00 | Ankara | Sun | 1 | 0 | |
| 11 | 01.08.2018 00:00:00 | Ankara | Sun | 0 | 0 | |
| 12 | 11.08.2018 00:00:00 | Cairo | Clouds | 6 | 6 | |
| 13 | 10.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | |
| 14 | 09.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | |
| 15 | 08.08.2018 00:00:00 | Cairo | Sun | 7 | 1 | |
| 16 | 07.08.2018 00:00:00 | Cairo | Sun | 6 | 1 | |
| 17 | 06.08.2018 00:00:00 | Cairo | Sun | 5 | 1 | |
| 18 | 05.08.2018 00:00:00 | Cairo | Clouds | 0 | 4 | |
| 19 | 04.08.2018 00:00:00 | Cairo | Sun | 3 | 0 | |
| 20 | 03.08.2018 00:00:00 | Cairo | Sun | 2 | 0 | |
| 21 | 02.08.2018 00:00:00 | Cairo | Sun | 1 | 0 | |
| 22 | 01.08.2018 00:00:00 | Cairo | Sun | 0 | 0 | |
+----+---------------------+--------+---------+----------------+-------------+----------+
您在不止一个问题上扩展了您的要求。我可以建议您考虑以上内容并决定是否可以使用这 2 个计算来得出想要的最终结果。如果您仍然无法得出结论，请使用文本 table 格式将 "expected result" 作为新列包含在内