MSSQL: Create incremental row label per group - sql-server

In my table, I have a primary key and a date. What I'd like to achieve is to have an incremental label based on whether or not there is a break between the dates - column Goal.
Now, below is an example. The break column was calculated using LEAD function (I thought it might help).
I am able to solve it using T-SQL, but this would be last resort. Nothing I tried has worked so far. I am using MSSQL 2014.
PK | Date | break | Goal |
-------------------------------
1 | 03/2017 | 0 | 1 |
1 | 04/2017 | 0 | 1 |
1 | 08/2017 | 1 | 2 |
1 | 09/2017 | 0 | 2 |
1 | 10/2017 | 0 | 2 |
1 | 02/2018 | 1 | 3 |
1 | 03/2018 | 0 | 3 |
Here is a code to reproduce this example:
CREATE TABLE #test
(
ConsumerId INT,
FullDate DATE,
Goal INT
)
INSERT INTO #test (ConsumerId, FullDate, Goal) VALUES (1,'2017-03-01',1)
INSERT INTO #test (ConsumerId, FullDate, Goal) VALUES (1,'2017-04-01',1)
INSERT INTO #test (ConsumerId, FullDate, Goal) VALUES (1,'2017-08-01',2)
INSERT INTO #test (ConsumerId, FullDate, Goal) VALUES (1,'2017-09-01',2)
INSERT INTO #test (ConsumerId, FullDate, Goal) VALUES (1,'2017-10-01',2)
INSERT INTO #test (ConsumerId, FullDate, Goal) VALUES (1,'2018-02-01',3)
INSERT INTO #test (ConsumerId, FullDate, Goal) VALUES (1,'2018-03-01',3)
SELECT ConsumerId,
FullDate,
CASE WHEN (datediff(month,
isnull(
LEAD (FullDate,1) OVER (PARTITION BY ConsumerId ORDER BY FullDate DESC),
FullDate),
FullDate) > 1)
THEN 1
ELSE 0
END AS break,
Goal
FROM #test
ORDER BY FullDate ASC
EDIT
This is apparently a famous problem "Islands and gaps" as pointed out in the comments. And Google offers many solutions as well as other questions here at SO.

Try this...
WITH
cte_TestGap AS (
SELECT
t.ConsumerId, t.FullDate,
Gap = CASE
WHEN DATEDIFF(mm, t.FullDate, LAG(t.FullDate, 1) OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)) = -1
THEN 0
ELSE ROW_NUMBER() OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)
END
FROM
#test t
),
cte_SmearGap AS (
SELECT
tg.ConsumerId, tg.FullDate,
GV = MAX(tg.Gap) OVER (PARTITION BY tg.ConsumerId ORDER BY tg.FullDate ROWS UNBOUNDED PRECEDING)
FROM
cte_TestGap tg
)
SELECT
sg.ConsumerId, sg.FullDate,
GroupValue = DENSE_RANK() OVER (PARTITION BY sg.ConsumerId ORDER BY sg.GV)
FROM
cte_SmearGap sg;
An explanation of the code an how it works...
The 1st query, in cte_TestGap, uses the LAG function along with ROW_NUMBER() function to mark the location of gap in the data. We can see that by breaking it out and looking at it's results...
WITH
cte_TestGap AS (
SELECT
t.ConsumerId, t.FullDate,
Gap = CASE
WHEN DATEDIFF(mm, t.FullDate, LAG(t.FullDate, 1) OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)) = -1
THEN 0
ELSE ROW_NUMBER() OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)
END
FROM
#test t
)
SELECT * FROM cte_TestGap;
cte_TestGap results...
ConsumerId FullDate Gap
----------- ---------- --------------------
1 2017-03-01 1
1 2017-04-01 0
1 2017-08-01 3
1 2017-09-01 0
1 2017-10-01 0
1 2018-02-01 6
1 2018-03-01 0
At this point we want the 0 values to take on the value of the preceding non-0 values, allowing them to be grouped together. This is done in the 2nd query (cte_SmearGap) using the MAX function with a "window frame". So if we look at the output of cte_SmearGap, we can see that...
WITH
cte_TestGap AS (
SELECT
t.ConsumerId, t.FullDate,
Gap = CASE
WHEN DATEDIFF(mm, t.FullDate, LAG(t.FullDate, 1) OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)) = -1
THEN 0
ELSE ROW_NUMBER() OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)
END
FROM
#test t
),
cte_SmearGap AS (
SELECT
tg.ConsumerId, tg.FullDate,
GV = MAX(tg.Gap) OVER (PARTITION BY tg.ConsumerId ORDER BY tg.FullDate ROWS UNBOUNDED PRECEDING)
FROM
cte_TestGap tg
)
SELECT * FROM cte_SmearGap;
cte_SmearGap results...
ConsumerId FullDate GV
----------- ---------- --------------------
1 2017-03-01 1
1 2017-04-01 1
1 2017-08-01 3
1 2017-09-01 3
1 2017-10-01 3
1 2018-02-01 6
1 2018-03-01 6
At this point All of the rows are in distinct groups... but... We'd like to have our group numbers in a contiguous sequence (1,2,3) as opposed to (1,3,6).
Of course that's easy enough to fix using the DENSE_Rank() function, which is what's happening in the final select...
WITH
cte_TestGap AS (
SELECT
t.ConsumerId, t.FullDate,
Gap = CASE
WHEN DATEDIFF(mm, t.FullDate, LAG(t.FullDate, 1) OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)) = -1
THEN 0
ELSE ROW_NUMBER() OVER (PARTITION BY t.ConsumerId ORDER BY t.FullDate)
END
FROM
#test t
),
cte_SmearGap AS (
SELECT
tg.ConsumerId, tg.FullDate,
GV = MAX(tg.Gap) OVER (PARTITION BY tg.ConsumerId ORDER BY tg.FullDate ROWS UNBOUNDED PRECEDING)
FROM
cte_TestGap tg
)
SELECT
sg.ConsumerId, sg.FullDate,
GroupValue = DENSE_RANK() OVER (PARTITION BY sg.ConsumerId ORDER BY sg.GV)
FROM
cte_SmearGap sg;
The end result...
ConsumerId FullDate GroupValue
----------- ---------- --------------------
1 2017-03-01 1
1 2017-04-01 1
1 2017-08-01 2
1 2017-09-01 2
1 2017-10-01 2
1 2018-02-01 3
1 2018-03-01 3

The comment from David Browne was actually extremely useful. If you google "Islands and Gaps", there are many variations of the solution. Below is the one I liked the most.
In the end, I needed the Goal column to be able to group the dates into MIN/MAX. This solution skips this step and directly creates the aggregated range.
Here is the source.
SELECT MIN(FullDate) AS range_start,
MAX(FUllDate) AS range_end
FROM (
SELECT FullDate,
DATEADD(MM, -1 * ROW_NUMBER() OVER(ORDER BY FullDate), FullDate) AS grp
FROM #test
) a
GROUP BY a.grp
And the output:
range_start | range_end |
--------------------------
2017-03-01 | 2017-04-01 |
2017-08-01 | 2017-10-01 |
2018-02-01 | 2018-03-01 |

Related

SQL Server - assign value to a field based on a running total

For a customer, I'm sending through an XML file to another system, the sales orders and I sum the quantities for each item across all sales orders lines (e.g.: if I have "ItemA" in 10 sales orders with different quantities in each one, I sum the quantity and send the total).
In return, I get a response whether the requested quantities can be delivered to the customers or not. If not, I still get the total quantity that can be delivered. However, could be situations when I request 100 pieces of "ItemA" and I cannot deliver all 100, but 98. In cases like this, I need to distribute (to UPDATE a custom field) those 98 pieces FIFO, according to the requested quantity in each sales order and based on the registration date of each sales order.
I tried to use a WHILE LOOP but I couldn't achieve the desired result. Here's my piece of code:
DECLARE #PickedQty int
DECLARE #PickedERPQty int
DECLARE #OrderedERPQty int=2
SET #PickedQty =
WHILE (#PickedQty>0)
BEGIN
SET #PickedERPQty=(SELECT CASE WHEN #PickedQty>#OrderedERPQty THEN #OrderedERPQty ELSE #PickedQty END)
SET #PickedQty=#PickedQty-#PickedERPQty
PRINT #PickedQty
IF #PickedQty>=0
BEGIN
UPDATE OrderLines
SET UDFValue2=#PickedERPQty
WHERE fDocID='82DADC71-6706-44C7-9B78-7FCB55D94A69'
END
IF #PickedQty <= 0
BREAK;
END
GO
Example of response
I requested 35 pieces but only 30 pieces are available to be delivered. I need to distribute those 30 pieces for each sales order, based on requested quantity and also FIFO, based on the date of the order. So, in this example, I will update the RealQty column with the requested quantity (because I have stock) and in the last one, I assign the remaining 5 pieces.
ord_Code CustOrderCode Date ItemCode ReqQty AvailQty RealQty
----------------------------------------------------------------------------
141389 CV/2539 2018-11-25 PX085 10 30 10
141389 CV/2550 2018-11-26 PX085 5 30 5
141389 CV/2563 2018-11-27 PX085 10 30 10
141389 CV/2564 2018-11-28 PX085 10 30 5
Could anyone give me a hint? Thanks
This might be more verbose than it needs to be, but I'll leave it to you to skinny it down if that's possible.
Set up the data:
DECLARE #OrderLines TABLE(
ord_Code INTEGER NOT NULL
,CustOrderCode VARCHAR(7) NOT NULL
,[Date] DATE NOT NULL
,ItemCode VARCHAR(5) NOT NULL
,ReqQty INTEGER NOT NULL
,AvailQty INTEGER NOT NULL
,RealQty INTEGER NOT NULL
);
INSERT INTO #OrderLines(ord_Code,CustOrderCode,[Date],ItemCode,ReqQty,AvailQty,RealQty) VALUES (141389,'CV/2539','2018-11-25','PX085',10,0,0);
INSERT INTO #OrderLines(ord_Code,CustOrderCode,[Date],ItemCode,ReqQty,AvailQty,RealQty) VALUES (141389,'CV/2550','2018-11-26','PX085', 5,0,0);
INSERT INTO #OrderLines(ord_Code,CustOrderCode,[Date],ItemCode,ReqQty,AvailQty,RealQty) VALUES (141389,'CV/2563','2018-11-27','PX085',10,0,0);
INSERT INTO #OrderLines(ord_Code,CustOrderCode,[Date],ItemCode,ReqQty,AvailQty,RealQty) VALUES (141389,'CV/2564','2018-11-28','PX085',10,0,0);
DECLARE #AvailQty INTEGER = 30;
For running totals, for SQL Server 20012 and up anyway, SUM() OVER is the preferred technique so I started off with some variants on that. This query brought in some useful numbers:
SELECT
ol.ord_Code,
ol.CustOrderCode,
ol.Date,
ol.ItemCode,
ol.ReqQty,
#AvailQty AS AvailQty,
SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date]) AS TotalOrderedQty,
#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date]) AS RemainingQty
FROM
#OrderLines AS ol;
Then I used the RemainingQty to do a little math. The CASE expression is hairy, but the first step checks to see if the RemainingQty after processing this row will be positive, and if it is, we fulfill the order. If not, we fulfill what we can. The nested CASE is there to stop negative numbers from coming into the result set.
SELECT
ol.ord_Code,
ol.CustOrderCode,
ol.Date,
ol.ItemCode,
ol.ReqQty,
#AvailQty AS AvailQty,
SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date]) AS TotalOrderedQty,
#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date]) AS RemainingQty,
CASE
WHEN (#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date])) > 0
THEN ol.ReqQty
ELSE
CASE
WHEN ol.ReqQty + (#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date])) > 0
THEN ol.ReqQty + (#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date]))
ELSE 0
END
END AS RealQty
FROM
#OrderLines AS ol
Windowing functions (like SUM() OVER) can only be in SELECT and ORDER BY clauses, so I had to do a derived table with a JOIN. A CTE would work here, too, if you prefer. But I used that derived table to UPDATE the base table.
UPDATE Lines
SET
Lines.AvailQty = d.AvailQty
,Lines.RealQty = d.RealQty
FROM
#OrderLines AS Lines
JOIN
(
SELECT
ol.ord_Code,
ol.CustOrderCode,
ol.Date,
ol.ItemCode,
#AvailQty AS AvailQty,
CASE
WHEN (#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date])) > 0
THEN ol.ReqQty
ELSE
CASE
WHEN ol.ReqQty + (#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date])) > 0
THEN ol.ReqQty + (#AvailQty-SUM(ReqQty) OVER (PARTITION BY ord_Code ORDER BY [Date]))
ELSE 0
END
END AS RealQty
FROM
#OrderLines AS ol
) AS d
ON d.CustOrderCode = Lines.CustOrderCode
AND d.ord_Code = Lines.ord_Code
AND d.ItemCode = Lines.ItemCode
AND d.Date = Lines.Date;
SELECT * FROM #OrderLines;
Results:
+----------+---------------+---------------------+----------+--------+----------+---------+
| ord_Code | CustOrderCode | Date | ItemCode | ReqQty | AvailQty | RealQty |
+----------+---------------+---------------------+----------+--------+----------+---------+
| 141389 | CV/2539 | 25.11.2018 00:00:00 | PX085 | 10 | 30 | 10 |
| 141389 | CV/2550 | 26.11.2018 00:00:00 | PX085 | 5 | 30 | 5 |
| 141389 | CV/2563 | 27.11.2018 00:00:00 | PX085 | 10 | 30 | 10 |
| 141389 | CV/2564 | 28.11.2018 00:00:00 | PX085 | 10 | 30 | 5 |
+----------+---------------+---------------------+----------+--------+----------+---------+
Play with different available qty values here: https://rextester.com/MMFAR17436

Union two list of dates, union with further info

I have two tables of dates, for the questions's sake call them dates1 and dates2. Sometimes a given date is in both, sometimes it is in 1 but not 2, and other times in 2 but not 1.
My original requirement was just a list of all dates from both sets
SELECT Date FROM dates1
UNION
SELECT Date FROM dates2
Easy peasy. New requirement; know which list the dates came from (or both if that is the case). The columns I need are as follows:
Date, IsList1, IsList2
So, some example data:
Dates1
======
Date
====
2017-01-31
2017-02-28
2017-03-31
Dates2
======
Date
====
2017-01-31
2017-04-30
Expected output
Date | IsList1 | IsList2
2017-01-31 | 1 | 1
2017-02-28 | 1 | 0
2017-03-31 | 1 | 0
2017-04-30 | 0 | 1
SQL fiddle with the above data: http://sqlfiddle.com/#!18/9eecb/5425
You'll most likely need to use a FULL OUTER JOIN and some expressions to achieve this.
SELECT ISNULL(D1.[Date], D2.[Date]) AS [Date],
CASE WHEN D1.[Date] IS NULL THEN 0 ELSE 1 END AS IsList1,
CASE WHEN D2.[Date] IS NULL THEN 0 ELSE 1 END AS IsList2
FROM #dates1 D1
FULL OUTER JOIN #dates2 D2 ON D1.[Date] = D2.[Date];
It's also worth nothing, on your SQL fiddle, that you have 2 INSERT statements into #Dates1 and none into #Dates2, thus the result set is 1 for all of IsList1 and 0 for IsList2.
;with cte
as
(
select dt.date as tb1,dt1.date as tbl2
from
#dates1 dt
full join
#dates2 dt1
on dt.date =dt1.date
)
select isnull(tb1 ,tbl2 ) as dt,
case when tb1 is not null then 1 else 0 end as list1,
case when tbl2 is not null then 1 else 0 end as list2
from cte
Perhaps another option with a simple aggregation:
Select Date
,InList1=sum(InList1)
,InList2=sum(InList2)
From (
Select Distinct Date,InList1=1,InList2=0 from #dates1
Union All
Select Distinct Date,InList1=0,InList2=1 from #dates2
) A
Group By Date
Returns
Date InList1 InList2
2017-01-31 1 1
2017-02-28 1 0
2017-03-31 1 0
2017-04-30 0 1

Field equal 1 display

I am using SQL Server 2008 and I would like to only get the activityCode for the orderno when it equals 1 if there are duplicate orderno with the activityCode equals 0.
Also, if the record for orderno activityCode equals 0 then display those records also. But I would only like to display the orderno when the activityCode equals 0 if the same orderno activityCode does not equal 1 or the activityCode only equals 0. I hope this is clear and makes sense but let me know if I need to provide more details. Thanks
--create table
create table po_v
(
orderno int,
amount number,
activityCode number
)
--insert values
insert into po_v values
(170268, 2774.31, 0),
(17001988, 288.82, 0),
(17001988, 433.23, 1),
(170271, 3786, 1),
(170271, 8476, 0),
(170055, 34567, 0)
--Results
170268 | 2774.31 | 0
17001988 | 433.23 | 1
170271 | 3786 | 1
170055 | 34567 | 0
*****Updated*****
I have inserted two new records and the results have been updated. The data in the actual table has other numbers besides 0 and 1. The select statement displays the correct orderno's but I would like the other records for the orderno to display also. The partition only populates one record per orderno. If possible I would like to see the records with the same activityCode.
--insert values
insert into po_v values
(170271, 3799, 1),
(172525, 44445, 2)
--select statement
SELECT Orderno,
Amount,
Activitycode
FROM (SELECT orderno,
amount,
activitycode,
ROW_NUMBER()
OVER(
PARTITION BY orderno
ORDER BY activitycode DESC) AS dup
FROM Po_v)dt
WHERE dt.dup = 1
ORDER BY 1
--select statement results
170055 | 34567 | 0
170268 | 2774.31 | 0
170271 | 3786 | 1
172525 | 44445 | 2
17001988 | 433.23 | 1
--expected results
170055 | 34567 | 0
170268 | 2774.31 | 0
170271 | 3786 | 1
170271 | 3799 | 1
172525 | 44445 | 2
17001988 | 433.23 | 1
Not totally clear what you are trying to do here but this returns the output you are expecting.
select orderno
, amount
, activityCode
from
(
select *
, RowNum = ROW_NUMBER() over(partition by orderno order by activityCode desc)
from po_v
) x
where x.RowNum = 1
---EDIT---
With the new details this is a very different question. As I understand it now you want all row for that share the max activity code for each orderno. You can do this pretty easily with a cte.
with MyGroups as
(
select orderno
, Activitycode = max(activitycode)
from po_v
group by orderno
)
select *
from po_v p
join MyGroups g on g.orderno = p.orderno
and g.Activitycode = p.Activitycode
Try this
SELECT Orderno,
Amount,
Activitycode
FROM (SELECT orderno,
amount,
activitycode,
ROW_NUMBER()
OVER(
PARTITION BY orderno
ORDER BY activitycode DESC) AS dup
FROM Po_v)dt
WHERE dt.dup = 1
ORDER BY 1
Result
Orderno Amount Activitycode
------------------------------------
170055 34567.00 0
170268 2774.31 0
170271 3786.00 1
17001988 433.23 1

How can I group / window date ordered events delineated by an arbitrary expression?

I would like to group some data together based on dates and some (potentially arbitrary) indicator:
Date | Ind
================
2016-01-02 | 1
2016-01-03 | 5
2016-03-02 | 10
2016-03-05 | 15
2016-05-10 | 6
2016-05-11 | 2
I would like to group together subsequent (date-ordered) rows but breaking the group after Indicator >= 10:
Date | Ind | Group
========================
2016-01-02 | 1 | 1
2016-01-03 | 5 | 1
2016-03-02 | 10 | 1
2016-03-05 | 15 | 2
2016-05-10 | 6 | 3
2016-05-11 | 2 | 3
I did find a promising technique at the end of a blog post: "Use this Neat Window Function Trick to Calculate Time Differences in a Time Series" (the final subsection, "Extra Bonus"), but the important part of the query uses a keyword (FILTER) that doesn't seem to be supported in SQL Server (and a quick Google later and I'm not sure where it is supported!).
I'm still hopeful a technique using a window function might be the answer. I just need a counter that I can add to every row, (like RANK or ROW_NUMBER does) but that only increments when some arbitrary condition evaluates as true. Is there a way to do this in SQL Server?
Here is the solution:
DECLARE #t TABLE ([Date] DATETIME, Ind INT)
INSERT INTO #t
VALUES
('2016-01-02', 1),
('2016-01-03', 5),
('2016-03-02', 10),
('2016-03-05', 15),
('2016-05-10', 6),
('2016-05-11', 2)
SELECT [Date],
Ind,
1 + SUM([Group]) OVER(ORDER BY [Date]) AS [Group]
FROM
(
SELECT *,
CASE WHEN LAG(ind) OVER(ORDER BY [Date]) >= 10
THEN 1
ELSE 0
END AS [Group]
FROM #t
) t
Just mark row as 1 when previous is greater than 10 else 0. Then a running sum will give you the desired result.
Giving full credit to Giorgi for the idea, but I've modified his answer (both for my benefit and for future readers).
Just change the CASE statement to see if 30 or more days have lapsed since the last record:
DECLARE #t TABLE ([Date] DATETIME)
INSERT INTO #t
VALUES
('2016-01-02'),
('2016-01-03'),
('2016-03-02'),
('2016-03-05'),
('2016-05-10'),
('2016-05-11')
SELECT [Date],
1 + SUM([Group]) OVER(ORDER BY [Date]) AS [Group]
FROM
(
SELECT [Date],
CASE WHEN DATEADD(d, -30, [Date]) >= LAG([Date]) OVER(ORDER BY [Date])
THEN 1
ELSE 0
END AS [Group]
FROM #t
) t

Running sum from a point

I have a forecast of change that I need to add on to actuals.
Example:
Date Group Count ActForc
Nov-15 GrpA 10 A
Dec-15 GrpA 12 A
Jan-16 GrpA -1 F
Feb-16 GrpA 2 F
What I would like to see is:
Date Group Count
Nov-15 GrpA 10
Dec-15 GrpA 12
Jan-16 GrpA 11
Feb-16 GrpA 13
but all of the counting/running sum queries I have seen assume that I want the sections to be separate, and give me ways to create sums for each section, but essentially, I want to seed the sum for the second section with the final value from the first section, and continue from that point, without disturbing the values from the second section
If your forecasts are always in the end of the date range, you can also do this by using few window functions inside each other. Here is a running total calculated over a field that checks if the next row is 'F' then it takes count, otherwise 0. When that is then taken instead of count when the next row is F, it will contain the figure you want.
select
[date],
[group],
case when isnull(lead(ActForc) over (order by Date asc),ActForc) = 'F' then
sum(Count2) over (order by Date asc) else [Count] end,
[count],
ActForc
from (
select
[date],
[group],
case when isnull(lead(ActForc) over (order by Date asc),ActForc) = 'F' then [Count] else 0 end as Count2,
[count],
ActForc
from
table1
) X
This should perform better than any recursive CTEs / correlated subqueries because the data isn't read several times. If you have more groups, partitioning the window functions with the group should fix that.
Example in SQL Fiddle with few more months.
Try with a recursive cte.
First create a subquery to have a row_id
Then create the base case with rn = 1
And finally the recursion calculate each next level.
SQL Fiddle Demo
WITH addID as (
SELECT [Date], [Group], [Count], [ActForc],
ROW_NUMBER() OVER ( ORDER BY [DATE]) as rn
FROM myTable
), cte_name ( [Date], [Group], [Count], [level] ) AS
(
SELECT [Date], [Group], [Count], 1 as [level]
FROM addID
WHERE rn = 1
UNION ALL
SELECT A.[Date],
A.[Group],
CASE WHEN [ActForc] = 'F' THEN C.[Count] + A.[Count]
ELSE A.[Count]
END AS [Count],
C.[level] + 1
FROM addID A
INNER JOIN cte_name C
ON A.rn = C.[level] + 1
)
SELECT *
FROM cte_name
OUTPUT
| Date | Group | Count | level |
|----------------------------|-------|-------|-------|
| November, 01 2015 00:00:00 | GrpA | 10 | 1 |
| December, 01 2015 00:00:00 | GrpA | 12 | 2 |
| January, 01 2016 00:00:00 | GrpA | 11 | 3 |
| February, 01 2016 00:00:00 | GrpA | 13 | 4 |

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