I have a table will the data with exist data below:
Select Date, [Closing Balance] from StockClosing
Date | Closing Quantity
---------------------------
20200828 | 5
20200901 | 10
20200902 | 8
20200904 | 15
20200905 | 18
There are some missing date on the table, example 20200829 to 20200831 and 20200903.
Those closing quantity of the missing date will be follow as per previous day closing quantity.
I would like select the table result in a full range of date (show everyday) with the closing quantity. Expected result,
Date | Closing Quantity
---------------------------
20200828 | 5
20200829 | 5
20200830 | 5
20200831 | 5
20200901 | 10
20200902 | 8
20200903 | 8
20200904 | 15
20200905 | 18
Beside using cursor/for loop to insert the missing date and data 1 by 1, is that any SQL command can do it at once?
You have option to use recursive CTE.
For reference Click Here
;with cte as(
select max(date) date from YourTable
),cte1 as (
select min(date) date from YourTable
union all
select dateadd(day,1,cte1.date) date from cte1 where date<(select date from cte)
)select c.date,isnull(y.[Closing Quantity],
(select top 1 a.[Closing Quantity] from YourTable a where c.date>a.date order by a.date desc) )
as [Closing Quantity]
from cte1 c left join YourTable y on c.date=y.date
The easiest way to do this is to use LAST_VALUE along with the IGNORE NULLS option. Sadly, SQL Server does not support this. There is a workaround using analytic functions, but I would actually offer this simple option, which uses a correlated subquery to fill in the missing values:
WITH dates AS (
SELECT '20200828' AS Date UNION ALL
SELECT '20200829' UNION ALL
SELECT '20200830' UNION ALL
SELECT '20200831' UNION ALL
SELECT '20200901' UNION ALL
SELECT '20200902' UNION ALL
SELECT '20200903' UNION ALL
SELECT '20200904' UNION ALL
SELECT '20200905'
)
SELECT
d.Date,
(SELECT TOP 1 t2.closing FROM StockClosing t2
WHERE t2.Date <= d.Date AND t2.closing IS NOT NULL
ORDER BY t2.Date DESC) AS closing
FROM dates d
LEFT JOIN StockClosing t1
ON d.Date = t1.Date;
Demo
Related
Here is an example:
Id|price|Date
1|2|2022-05-21
1|3|2022-06-15
1|2.5|2022-06-19
Needs to look like this:
Id|Date|price
1|2022-05-21|2
1|2022-05-22|2
1|2022-05-23|2
...
1|2022-06-15|3
1|2022-06-16|3
1|2022-06-17|3
1|2022-06-18|3
1|2022-06-19|2.5
1|2022-06-20|2.5
...
Until today
1|2022-08-30|2.5
I tried using the lag(price) over (partition by id order by date)
But i can't get it right.
I'm not familiar with Azure, but it looks like you need to use a calendar table, or generate missing dates using a recursive CTE.
To get started with a recursive CTE, you can generate line numbers for each id (assuming multiple id values) in the source data ordered by date. These rows with row number equal to 1 (with the minimum date value for the corresponding id) will be used as the starting point for the recursion. Then you can use the DATEADD function to generate the row for the next day. To use the price values from the original data, you can use a subquery to get the price for this new date, and if there is no such value (no row for this date), use the previous price value from CTE (use the COALESCE function for this).
For SQL Server query can look like this
WITH cte AS (
SELECT
id,
date,
price
FROM (
SELECT
*,
ROW_NUMBER() OVER (PARTITION BY id ORDER BY date) AS rn
FROM tbl
) t
WHERE rn = 1
UNION ALL
SELECT
cte.id,
DATEADD(d, 1, cte.date),
COALESCE(
(SELECT tbl.price
FROM tbl
WHERE tbl.id = cte.id AND tbl.date = DATEADD(d, 1, cte.date)),
cte.price
)
FROM cte
WHERE DATEADD(d, 1, cte.date) <= GETDATE()
)
SELECT * FROM cte
ORDER BY id, date
OPTION (MAXRECURSION 0)
Note that I added OPTION (MAXRECURSION 0) to make the recursion run through all the steps, since the default value is 100, this is not enough to complete the recursion.
db<>fiddle here
The same approach for MySQL (you need MySQL of version 8.0 to use CTE)
WITH RECURSIVE cte AS (
SELECT
id,
date,
price
FROM (
SELECT
*,
ROW_NUMBER() OVER (PARTITION BY id ORDER BY date) AS rn
FROM tbl
) t
WHERE rn = 1
UNION ALL
SELECT
cte.id,
DATE_ADD(cte.date, interval 1 day),
COALESCE(
(SELECT tbl.price
FROM tbl
WHERE tbl.id = cte.id AND tbl.date = DATE_ADD(cte.date, interval 1 day)),
cte.price
)
FROM cte
WHERE DATE_ADD(cte.date, interval 1 day) <= NOW()
)
SELECT * FROM cte
ORDER BY id, date
db<>fiddle here
Both queries produces the same results, the only difference is the use of the engine's specific date functions.
For MySQL versions below 8.0, you can use a calendar table since you don't have CTE support and can't generate the required date range.
Assuming there is a column in the calendar table to store date values (let's call it date for simplicity) you can use the CROSS JOIN operator to generate date ranges for the id values in your table that will match existing dates. Then you can use a subquery to get the latest price value from the table which is stored for the corresponding date or before it.
So the query would be like this
SELECT
d.id,
d.date,
(SELECT
price
FROM tbl
WHERE tbl.id = d.id AND tbl.date <= d.date
ORDER BY tbl.date DESC
LIMIT 1
) price
FROM (
SELECT
t.id,
c.date
FROM calendar c
CROSS JOIN (SELECT DISTINCT id FROM tbl) t
WHERE c.date BETWEEN (
SELECT
MIN(date) min_date
FROM tbl
WHERE tbl.id = t.id
)
AND NOW()
) d
ORDER BY id, date
Using my pseudo-calendar table with date values ranging from 2022-05-20 to 2022-05-30 and source data in that range, like so
id
price
date
1
2
2022-05-21
1
3
2022-05-25
1
2.5
2022-05-28
2
10
2022-05-25
2
100
2022-05-30
the query produces following results
id
date
price
1
2022-05-21
2
1
2022-05-22
2
1
2022-05-23
2
1
2022-05-24
2
1
2022-05-25
3
1
2022-05-26
3
1
2022-05-27
3
1
2022-05-28
2.5
1
2022-05-29
2.5
1
2022-05-30
2.5
2
2022-05-25
10
2
2022-05-26
10
2
2022-05-27
10
2
2022-05-28
10
2
2022-05-29
10
2
2022-05-30
100
db<>fiddle here
I have records of No. of calls coming to a call center. When a call comes into a call center a ticket is open.
So, let's say ticket 1 (T1) is open on 8/1/19 and it stays open till 8/5/19. So, if a person ran a query everyday then on 8/1 it will show 1 ticket open...same think on day 2 till day 5....I want to get records by day to see how many tickets were open for each day.....
In short, Frequency Distribution by Day.
Ticket Open_date Close_date
T1 8/1/2019 8/5/2019
T2 8/1/2019 8/6/2019
Result:
Result
Date # Tickets_Open
8/1/2019 2
8/2/2019 2
8/3/2019 2
8/4/2019 2
8/5/2019 2
8/6/2019 1
8/7/2019 0
8/8/2019 0
8/9/2019 0
8/10/2019 0
We can handle your requirement via the use of a calendar table, which stores all dates covering the full range in your data set.
WITH dates AS (
SELECT '2019-08-01' AS dt UNION ALL
SELECT '2019-08-02' UNION ALL
SELECT '2019-08-03' UNION ALL
SELECT '2019-08-04' UNION ALL
SELECT '2019-08-05' UNION ALL
SELECT '2019-08-06' UNION ALL
SELECT '2019-08-07' UNION ALL
SELECT '2019-08-08' UNION ALL
SELECT '2019-08-09' UNION ALL
SELECT '2019-08-10'
)
SELECT
d.dt,
COUNT(t.Open_date) AS num_tickets_open
FROM dates d
LEFT JOIN tickets t
ON d.dt BETWEEN t.Open_date AND t.Close_date
GROUP BY
d.dt;
Note that in practice if you expect to have this reporting requirement in the long term, you might want to replace the dates CTE above with a bona-fide table of dates.
This solution generates the list of dates from the tickets table using CTE recursion and calculates the count:
WITH Tickets(Ticket, Open_date, Close_date) AS
(
SELECT "T1", "8/1/2019", "8/5/2019"
UNION ALL
SELECT "T2", "8/1/2019", "8/6/2019"
),
Ticket_dates(Ticket, Dates) as
(
SELECT t1.Ticket, CONVERT(DATETIME, t1.Open_date)
FROM Tickets t1
UNION ALL
SELECT t1.Ticket, DATEADD(dd, 1, CONVERT(DATETIME, t1.Dates))
FROM Ticket_dates t1
inner join Tickets t2 on t1.Ticket = t2.Ticket
where DATEADD(dd, 1, CONVERT(DATETIME, t1.Dates)) <= CONVERT(DATETIME, t2.Close_date)
)
SELECT CONVERT(varchar, Dates, 1), count(*)
FROM Ticket_dates
GROUP by Dates
ORDER by Dates
A "general purpose" trick is to generate a series of numbers, which can be done using CTE's but there are many alternatives, and from that create the needed range of dates. Once that exists then you can left join your ticket data to this and then count by date.
CREATE TABLE mytable(
Ticket VARCHAR(8) NOT NULL PRIMARY KEY
,Open_date DATE NOT NULL
,Close_date DATE NOT NULL
);
INSERT INTO mytable(Ticket,Open_date,Close_date) VALUES ('T1','8/1/2019','8/5/2019');
INSERT INTO mytable(Ticket,Open_date,Close_date) VALUES ('T2','8/1/2019','8/6/2019');
Also note I am using a cross apply in this example to "attach" the min and max dates of your tickets to each numbered row. You would need to include your own logic on what data to select here.
;WITH
cteDigits AS (
SELECT 0 AS digit UNION ALL SELECT 1 UNION ALL SELECT 2 UNION ALL SELECT 3 UNION ALL SELECT 4 UNION ALL
SELECT 5 UNION ALL SELECT 6 UNION ALL SELECT 7 UNION ALL SELECT 8 UNION ALL SELECT 9
)
, cteTally AS (
SELECT
[1s].digit
+ [10s].digit * 10
+ [100s].digit * 100 /* add more like this as needed */
AS num
FROM cteDigits [1s]
CROSS JOIN cteDigits [10s]
CROSS JOIN cteDigits [100s] /* add more like this as needed */
)
select
n.num + 1 rownum
, dateadd(day,n.num,ca.min_date) as on_date
, count(t.Ticket) as tickets_open
from cteTally n
cross apply (select min(Open_date), max(Close_date) from mytable) ca (min_date, max_date)
left join mytable t on dateadd(day,n.num,ca.min_date) between t.Open_date and t.Close_date
where dateadd(day,n.num,ca.min_date) <= ca.max_date
group by
n.num + 1
, dateadd(day,n.num,ca.min_date)
order by
rownum
;
result:
+--------+---------------------+--------------+
| rownum | on_date | tickets_open |
+--------+---------------------+--------------+
| 1 | 01.08.2019 00:00:00 | 2 |
| 2 | 02.08.2019 00:00:00 | 2 |
| 3 | 03.08.2019 00:00:00 | 2 |
| 4 | 04.08.2019 00:00:00 | 2 |
| 5 | 05.08.2019 00:00:00 | 2 |
| 6 | 06.08.2019 00:00:00 | 1 |
+--------+---------------------+--------------+
I have the following data set:
I want to create a new column that sums the last 7 days of sales. So the query result should look be the following:
Pls help
Thanks!
In standard SQL, you would use a window function -- assuming you have data for each day:
select t.*,
sum(sales) over (partition by itemid order by date rows between 6 preceding and current row) as sales_7
from t;
use sum() aggregate function and group by
select country,itemid,year,monthnumber,week sum(sales) as sales_last_7days from your_table
where date>=DATEADD(day, -7, getdate()) and date< getdate()
group by country,itemid,year,monthnumber,week
with window:
select (list other columns here), sum(sum(sales)) over
(partition by week
order by day
rows between 6 preceding and current row)
from table
group by date, week;
note that week doesen't change group by beacause a date is reffered to one week only, but it is needed in window.
Seems you are working with SQL Server if so, then you can use apply :
select t.*, t1.[last7day]
from table t outer apply
(select sum(t1.sales) as [last7day]
from table t1
where t.itemid = t1.itemid and
t1.date <= dateadd(day, -6, t.dt)
) t1;
If you don't have exactly one day for each row, for example if you have a list of transactions...
The below example completely confused me the first time I saw it, so I've tried to comment as much as I can to explain what's happening.
Suppose we have a table tbl with date column dt and amount column amt, and for each date in tbl we want to return a rolling sum of the amount from the current day and the past 6 days.
select distinct -- see note after code on what this distinct is doing.
dt
, ( -- Has to be in brackets to denote we're returning 1 value per row.
-- for each row of T1:
select sum(b.amt) -- the sum of amounts in T2. The where clause will restrict which rows in T2 will be summed.
from tbl T2
where T2.dt between T1.dt - 6 and T1.dt -- for each row in T1, give me all rows in T2 where the date is between 6 days before this T1 row's date and T1 row's date, giving us our rolling sum
-- WARNING: CHECK YOUR VERSION OF SQL FOR HOW TO SUBTRACT DAYS FROM A DATE, I'VE MADE IT (T1.dt - 6) FOR SIMPLICITY
-- we don't need a group by, because we're returning one value for each row in T1
)
from tbl T1
We have a main version of tbl, aliased T1. We then have a secondary table, aliased T2. For each row in T1, we're going to ask for a set of rows in T2 that we're going to sum before giving it to our main query.
To understand what's happening, run the code without the distinct. You'll notice that we have the same number of rows as in tbl, because the T2 statement is happening for every row in T1.
Notes:
If you have any days for which no rows exist in your table you will not get a calculation for this day. To be certain this doesn't happen, join your table to a table containing a distinct list of consecutive dates, and use this as your date column.
If you have nulls in your amount column the calculation will still work, but if the rolling average contains only nulls you will have null instead of 0 as your result. If that troubles you convert all your nulls to zero's before (or after) you use the query.
The beginning of the period will have a 'ramp up'. But this would be the same whatever method you use to do a rolling sum. If it bothers you, don't return the first 6 days.
Finally a worked example if you're playing along at home using SQL Server:
with tbl as (
-- a list of transactions from 1.10.2019 to 14.10.2019
select cast('2019-10-01' as date) dt, 1 amt
union select cast('2019-10-02' as date), 4
union select cast('2019-10-01' as date), 10
union select cast('2019-10-03' as date), 3
union select cast('2019-10-04' as date), 20
union select cast('2019-10-04' as date), 2
union select cast('2019-10-04' as date), 12
union select cast('2019-10-04' as date), 17
union select cast('2019-10-05' as date), null -- a whole week of null values because we all had the week off... I hope this data wasn't important
union select cast('2019-10-06' as date), null
union select cast('2019-10-07' as date), null
union select cast('2019-10-08' as date), null
union select cast('2019-10-09' as date), null
union select cast('2019-10-10' as date), null
union select cast('2019-10-10' as date), null
union select cast('2019-10-10' as date), null
union select cast('2019-10-11' as date), null
union select cast('2019-10-12' as date), 1
union select cast('2019-10-12' as date), 1
union select cast('2019-10-12' as date), 1
union select cast('2019-10-12' as date), 1
union select cast('2019-10-12' as date), 1
union select cast('2019-10-12' as date), 1
union select cast('2019-10-13' as date), 2
union select cast('2019-10-14' as date), 1000
)
select distinct
a.dt
, (
select sum(b.amt)
from tbl b
where b.dt between dateadd(dd, -6, a.dt) and a.dt
) past_7_days_amt
from tbl a
Returns:
+------------+-----------------+
| dt | past_7_days_amt |
+------------+-----------------+
| 2019-10-01 | 11 |
| 2019-10-02 | 15 |
| 2019-10-03 | 18 |
| 2019-10-04 | 69 |
| 2019-10-05 | 69 |
| 2019-10-06 | 69 |
| 2019-10-07 | 69 |
| 2019-10-08 | 58 |
| 2019-10-09 | 54 |
| 2019-10-10 | 51 |
| 2019-10-11 | NULL |
| 2019-10-12 | 1 |
| 2019-10-13 | 3 |
| 2019-10-14 | 1003 |
+------------+-----------------+
I've a table containing a date column.
ID | Date
----|-----------
1 | 2000-01-01
2 | 2000-02-01
3 | 2000-02-01
4 | 2000-03-01
I need a select that returns for each row, the ID, the Date and the smallest date (of all dates in the table) that is larger than the current date.
ID | Date | Next date
----+------------+------------
1 | 2000-01-01 | 2000-02-01
2 | 2000-02-01 | 2000-03-01
3 | 2000-02-01 | 2000-03-01
4 | 2000-03-01 | (NULL)
My first approach was
SELECT id, date, LEAD (date, 1) OVER (ORDER BY date NULLS LAST) AS next_date
FROM t
But this only works, if the values in column DATE are unique.
Any ideas?
You could use an analytic function with a windowing clause. lead() doesn't support a windowing clause, so you need use one that does like min() or first_value():
FIRST_VALUE ("Date")
OVER (ORDER BY "Date" RANGE BETWEEN 1 FOLLOWING AND UNBOUNDED FOLLOWING)
The default windowing clause is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW, which would give all your rows the same value of 2000-01-01 and using a ROWS window would run into the same problem you're having with lead() with duplicate dates (ID 2 would still get 2000-02-01; and ID 4 would get 2000-03-01 instead of null if you you used ROWS BETWEEN CURRENT ROW... rather than 1 FOLLOWING).
Demo using this range:
with t (ID, "Date") as (
select 1, date '2000-01-01' from dual
union all select 2, date '2000-02-01' from dual
union all select 3, date '2000-02-01' from dual
union all select 4, date '2000-03-01' from dual
)
select id, "Date", FIRST_VALUE ("Date") OVER (ORDER BY "Date"
RANGE BETWEEN 1 FOLLOWING AND UNBOUNDED FOLLOWING) AS next_date
FROM t;
ID Date NEXT_DATE
---------- ---------- ----------
1 2000-01-01 2000-02-01
2 2000-02-01 2000-03-01
3 2000-02-01 2000-03-01
4 2000-03-01
Only rows where the date value is higher than the current row are considered. And this still only has to hit the table once.
(I've put "Date" in double-quotes because date is a reserved word; from your sample data it looks like a quoted identifier, but it isn't quoted in your query, so it's probably just got a more sensible name really...)
select * , (select min(t2.date) from table t2 where t2.date > t1.date)
from Table t1
Above code is in sql server
To answer my own question. ;-) (Just to show another option to people stumbling across this post)
Another solution would be using a subselect:
SELECT t.id,
t.date,
(SELECT MIN (t.date)
FROM t t2
WHERE t2.date > t.date)
AS next_date
FROM t;
One approach would be to create a CTE containing the distinct dates and their immediate lead values. Then, join this CTE to your original table on the date to get the final result.
WITH cte AS (
SELECT t.date,
LEAD(t.date, 1) OVER (ORDER BY t.date NULLS LAST) AS next_date
FROM (SELECT DISTINCT date FROM yourTable) t
)
SELECT
t1.ID,
t1.date,
t2.next_date
FROM yourTable t1
INNER JOIN cte t2
ON t1.date = t2.date
Here is another approach, without "distinct":
select
ted.id,
ted.date_col,
(select
min(ted2.date_col)
from
test_date_v ted2
where
ted2.id != ted.id and
ted2.date_col > ted.date_col) next_date_col
from
test_date_v ted;
I would like to know how to make intersections or concatenations of adjacent date ranges in sql.
I have a list of customer start and end dates, for example (in dd/mm/yyyy format, where 31/12/9999 means the customer is still a current customer).
CustID | StartDate | Enddate |
1 | 01/08/2011|19/06/2012|
1 | 20/06/2012|07/03/2012|
1 | 03/05/2012|31/12/9999|
2 | 09/03/2009|16/08/2009|
2 | 16/01/2010|10/10/2010|
2 | 11/10/2010|31/12/9999|
3 | 01/08/2010|19/08/2010|
3 | 20/08/2010|26/12/2011|
Although the dates in different rows don't overlap, I would consider some of the ranges as a contigous period of time, e.g when the start date comes one day after an end date (for a given customer). Hence I would like to return a query that returns just the intersection of the dates,
CustID | StartDate | Enddate |
1 | 01/08/2011|07/03/2012|
1 | 03/05/2012|31/12/9999|
2 | 09/03/2009|16/08/2009|
2 | 16/01/2010|31/12/9999|
3 | 01/08/2010|26/12/2011|
I've looked at CTE tables, but I can't figure out how to return just one row for one contigous block of dates.
This should work in 2005 forward:
;WITH cte2 AS (SELECT 0 AS Number
UNION ALL
SELECT Number + 1
FROM cte2
WHERE Number < 10000)
SELECT CustID, Min(GroupStart) StartDate, MAX(EndDate) EndDate
FROM (SELECT *
, DATEADD(DAY,b.number,a.StartDate) GroupStart
, DATEADD(DAY,1- DENSE_RANK() OVER (PARTITION BY CustID ORDER BY DATEADD(DAY,b.number,a.StartDate)),DATEADD(DAY,b.number,a.StartDate)) GroupDate
FROM Table1 a
JOIN cte2 b
ON b.number <= DATEDIFF(d, startdate, EndDate)
) X
GROUP BY CustID, GroupDate
ORDER BY CustID, StartDate
OPTION (MAXRECURSION 0)
Demo: SQL Fiddle
You can build a quick table of numbers 0-something large enough to cover the spread of dates in your ranges to replace the cte so it doesn't run each time, indexed properly it will run quickly.
you can do this with recursive common table expression:
with cte as (
select t.CustID, t.StartDate, t.EndDate, t2.StartDate as NextStartDate
from Table1 as t
left outer join Table1 as t2 on t2.CustID = t.CustID and t2.StartDate = case when t.EndDate < '99991231' then dateadd(dd, 1, t.EndDate) end
), cte2 as (
select c.CustID, c.StartDate, c.EndDate, c.NextStartDate
from cte as c
where c.NextStartDate is null
union all
select c.CustID, c.StartDate, c2.EndDate, c2.NextStartDate
from cte2 as c2
inner join cte as c on c.CustID = c2.CustID and c.NextStartDate = c2.StartDate
)
select CustID, min(StartDate) as StartDate, EndDate
from cte2
group by CustID, EndDate
order by CustID, StartDate
option (maxrecursion 0);
sql fiddle demo
Quick performance tests:
Results on 750 rows, small periods of 2 days length:
sql fiddle demo
My query: 300 ms
Goat CO query with CTE: 10804 ms
Goat CO query with table of fixed numbers: 7 ms
Results on 5 rows, large periods:
sql fiddle demo
My query: 1 ms
Goat CO query with CTE: 700 ms
Goat CO query with table of fixed numbers: 36 ms