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SQL：第一次出現和最后一次出現之間的行數-略有不同

[英]SQL: Count of rows between first and last occurrence - with a twist

 原文  2018-10-29 02:29:43  0   1    sql/ sql-server/ lag/ row-number/ lead

問題描述

我想查找值的第一次出現和最后一次出現之間的行數。 但是，當它們之間有五個或更多具有不同值的記錄時，請停止計數。

因此，如果最后一次出現是今天，而第一次出現是昨天，則結果將是2 （今天加上昨天）。

如果最后一次出現是今天，而第一次出現是8天前，並且兩者之間沒有發生，則結果將為'1'。 但是，如果3天前會再次發生，結果將是4 （3 + 2 + 1天前加上今天）。

我希望這是有道理的。

這是我的資料 

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

我需要的是一個查詢，該查詢返回給定城市的日期，並注明該天的天氣以及該天氣首次發生以來的天數。 但是，如果間隔為五天或更長時間，則計數從1重新開始。

就像在11th Aug查詢Ankara時一樣，它將返回11因為距Sun首次出現已經11天（包括今天）。

然而，對於Cairo在11th Aug ，它將返回1 ，而不是7 ，因為它已經5+之間的天Clouds在8月5日和Clouds今天。

我已經嘗試過使用first_value（），LEAD，LAG和ROW_NUMBER進行很多操作，但是對於所有這些都不幸失敗了，沒有任何意義。

無論如何，這里... 

select 
 city, val,datediff(day, min(datadate), '2018-10-30') + 1 as DaysPresent
from d
where val = last_val
group by city,val;

要么... 

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

預期結果 

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

1 個解決方案

解決方案1
 3 已采納  2018-10-29 04:10:08

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

結果： 

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

在線查看： https ： //rextester.com/ZSHT63407

原版的

帶有以下示例數據： 

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');

使用此查詢： 

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

結果如下： 

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

在一個以上的問題上，您已經擴展了自己的要求。 我可以建議您考慮以上內容，然后決定是否可以使用這兩種計算得出所需的最終結果。 如果仍然無法得出結論，請使用文本表格式將“預期結果”作為新列添加

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