Related
Here is my example table:
CREATE TABLE demo1
(
ProviderID int NOT NULL,
ProviderClientID int NOT NULL,
ClientIdentifier nvarchar(9) NOT NULL,
ClientIdentifierTypeID int NOT NULL
);
INSERT INTO demo1 (ProviderID, ProviderClientID, ClientIdentifier, ClientIdentifierTypeID)
VALUES
(5, 7, 123444567, 1),
(5, 7, 000111234, 2),
(5, 11, 145342332, 1),
(5, 12, 234212345, 1),
(5, 13, 324564332, 3),
(5, 14, 123222467, 3),
(5, 19, 234444879, 1),
(5, 19, 000111643, 2),
(5, 19, 999234252, 3),
(5, 20, 456333245, 1)
The column ClientIdentifierTypeID values mean:
1 - Drivers License #,
2 - SchoolID,
3 - StateID
So clients can be in the table multiple times with different identifier types.
I want to select each client & just their drivers license #. If they don't have drivers license, then get their state id. I don't want their school id at all.
This is going to be part of a client count I am going to do next.
Here is what I tried in my query so far (I filter out school id already):
WITH A AS
(
SELECT
*
FROM
demo1
WHERE
ClientIdentifierTypeID IN ('1', '3')
), B AS
(
SELECT
*,
ROW_NUMBER() OVER(PARTITION BY [ProviderClientID] ORDER BY [ClientIdentifierTypeID]) AS rn
FROM
A
)
SELECT
*
FROM
B
WHERE
rn = 1
EDIT: I am re-reading through my query, it seems do what I want.
When there is a license# rn will be 1. If no license, the state id will have rn=1.
If counts clients including school id then disable where clause otherwise enable it.
-- sql server
SELECT ProviderClientID
, COUNT(1) count_client
, MIN(CASE WHEN ClientIdentifierTypeID = 1
THEN ClientIdentifier
WHEN ClientIdentifierTypeID = 3
THEN ClientIdentifier
END)
FROM demo1
-- WHERE ClientIdentifierTypeID IN ('1', '3')
GROUP BY ProviderClientID;
I use two Selects to filter. One is to get the uses who has driver License . Second block is to get the users who has Sate but not driver license.
then combine both lists with UNION ALL.
This is one possibility.
--client has driver License
SELECT * FROM demo1
WHERE ClientIdentifierTypeID in (1)
AND ClientIdentifierTypeID not in (3,2)
UNION ALL
-- Clients who has State and not driver License
SELECT * FROM demo1
WHERE ClientIdentifierTypeID in (3)
and ProviderClientID Not in (SELECT ProviderClientID FROM demo1
WHERE ClientIdentifierTypeID in (1)
)
I have 2 tables #Claims and #ClaimsActivity:
Query:
declare #Claims table (ClaimID int)
insert into #Claims
values (6070), (6080)
declare #ClaimsActivity table
(
Activityid int,
ClaimID int,
Activity int,
ActivityDate datetime,
ClaimStatus int
)
insert into #ClaimsActivity
values (1, 6070, 0, '2017-11-05 20:23:16.640', 0),
(3, 6070, 6, '2017-11-06 13:50:28.203', 0),
(4, 6070, 9, '2017-11-07 13:39:28.410', 0),
(5, 6070, 10, '2017-11-07 13:40:49.980', 0),
(7, 6070, 8, '2017-11-07 15:46:18.367', 1),
(8, 6070, 8, '2017-11-07 16:50:49.543', 1),
(9, 6070, 9, '2017-11-07 16:50:54.733', 0),
(10, 6070, 4, '2017-11-07 16:55:22.135', 0),
(11, 6070, 6, '2017-11-08 18:32:15.101', 0),
(12, 6080, 0, '2017-11-12 11:15:17.199', 0),
(13, 6080, 8, '2017-11-13 09:12:23.203', 1)
select *
from #Claims
select *
from #ClaimsActivity
order by ActivityDate
I need to add 2 columns based on data in #ClaimsActivity: IsReopened and DateReopened
The logic is:
If the last ClaimStatus (based on ActivityDate) = 1 then IsReopened = 0
But if the last ClaimStatus = 0 then it need to go and check whether one of the Activity is = 9 (Claim Reopened)
and if one of the Activity = 9 then IsReopened should = 1 and DateReopened should be the last date when it was reopened
I brought column StatusOfClaim, but I also need IsReopened and DateReopened
select
Claimid,
isnull((select top 1
case when al.ClaimStatus = 1
then 'Closed'
else 'Open'
end
from
#ClaimsActivity al
where
C.ClaimID = al.ClaimID
order by
al.ActivityDate desc), 'Open') as 'Status of Claim',
NULL as 'isReopen',
NULL as 'DateReopened'
from
#Claims c
Desired output should be like this:
There are many different ways you can accomplish this, but here is an example using CROSS APPLY and OUTER APPLY:
SELECT
ClaimID,
CASE WHEN tmp.IsOpen = 1 THEN 'Open' ELSE 'Closed' END AS 'Status of Claim',
CASE WHEN tmp.IsOpen = 1 AND lastReopen.Activityid IS NOT NULL THEN 1 ELSE 0 END AS 'isReopen',
lastReopen.ActivityDate AS 'DateReopened'
FROM #Claims c
CROSS APPLY (
SELECT ISNULL((
SELECT TOP 1 CASE WHEN al.ClaimStatus = 1 THEN 0 ELSE 1 END
FROM #ClaimsActivity al
WHERE c.ClaimID = al.ClaimID
ORDER BY al.ActivityDate DESC
), 1) AS IsOpen
) tmp
OUTER APPLY (
SELECT TOP 1
al.Activityid,
al.ActivityDate
FROM #ClaimsActivity al
WHERE c.ClaimID = al.ClaimID AND al.Activity = 9
ORDER BY al.ActivityDate DESC
) lastReopen
The CROSS APPLY is just used to produce a column that tells us whether a claim is open or closed, and we can reuse this throughout the rest of the query.
The OUTER APPLY is used to grab to the last "reopen" activity for each claim, of which you want the date.
I can't attest to the performance of this query, but this should at least give you the correct results.
I have a list of data :
Id StartAge EndAge Amount
1 0 2 50
2 2 5 100
3 5 10 150
4 6 9 160
I have to set Amount for various age group.
The age group >0 and <=2 need to pay 50
The age group >2 and <=5 need to pay 100
The age group >5 and <=10 need to pay 150
But
The age group >6 and <=9 need to pay 160 is an invalid input because >6 and <=9 already exist on 150 amount range.
I have to validate such kind of invalid input before inserting my data as a bulk.Once 5-10 range gets inserted anything that is within this range should not be accepted by system. For example: In above list, user should be allowed to insert 10-15 age group but any of the following should be checked as invalid.
6-9
6-11
3-5
5-7
If Invalid Input exists on my list I don't need to insert the list.
You could try to insert your data to the temporary table first.
DECLARE #TempData TABLE
(
[Id] TINYINT
,[StartAge] TINYINT
,[EndAge] TINYINT
,[Amount] TINYINT
);
INSERT INTO #TempData ([Id], [StartAge], [EndAge], [Amount])
VALUES (1, 0, 2, 50)
,(2, 2, 5, 100)
,(3, 5, 10, 150)
,(4, 6, 9, 160);
Then, this data will be transferred to your target table using INSERT INTO... SELECT... statement.
INSERT INTO <your target table>
SELECT * FROM #TempData s
WHERE
NOT EXISTS (
SELECT 1
FROM #TempData t
WHERE
t.[Id] < s.[Id]
AND s.[StartAge] < t.[EndAge]
AND s.[EndAge] > t.[StartAge]
);
I've created a demo here
We can use recursive CTE to find how records are chained by end age and start age pairs:
DECLARE #DataSource TABLE
(
[Id] TINYINT
,[StartAge] TINYINT
,[EndAge] TINYINT
,[Amount] TINYINT
);
INSERT INTO #DataSource ([Id], [StartAge], [EndAge], [Amount])
VALUES (1, 0, 2, 50)
,(2, 2, 5, 100)
,(3, 5, 10, 150)
,(4, 6, 9, 160)
,(5, 6, 11, 160)
,(6, 3, 5, 160)
,(7, 5, 7, 160)
,(9, 10, 15, 20)
,(8, 7, 15, 20);
WITH PreDataSource AS (
SELECT *, ROW_NUMBER() OVER (PARTITION BY [StartAge] ORDER BY [id]) as [pos]
FROM #DataSource
), DataSource AS
(
SELECT [Id], [StartAge], [EndAge], [Amount], [pos]
FROM PreDataSource
WHERE [id] = 1
UNION ALL
SELECT R.[Id], R.[StartAge], R.[EndAge], R.[Amount], R.[pos]
FROM DataSource A
INNER JOIN PreDataSource R
ON A.[Id] < R.[Id]
AND A.[EndAge] = R.[StartAge]
AND R.[pos] =1
)
SELECT [Id], [StartAge], [EndAge], [Amount]
FROM DataSource;
This is giving us, the following output:
Note, that before this, we are using the following statement to prepare the data:
SELECT *, ROW_NUMBER() OVER (PARTITION BY [StartAge] ORDER BY [id]) as [pos]
FROM #DataSource;
The idea is to find records with same start age and to calculated which one is inserted first. Then, in the CTE we are getting only the first.
Assuming you are bulk inserting the mentioned data into a temp table(#tmp) or table variable (#tmp).
If you are working on sql server 2012 try the below.
select *
from(select *,lag(endage,1,0)over(order by endage) as [col1]
from #tmp)tmp
where startage>=col1 and endage>col1
The result of this query should be inserted into your main table.
I need to count totals number of records in a table, 'a', where a field in 'a', say 'type', has a certain value, 'v'. From all these records where a.type = 'v', I need to group these twice: first by field 'b_id', and again by month. The date range for these records must be restricted to the last year from the current date
I already have the totals for the 'b_id' field with ISNULL() as follows:
SELECT ISNULL(
SELECT COUNT(*)
FROM a
WHERE a.type = 'v'
AND b.b_id = a.b_id
), 0) AS b_totals
The data lies in table a, and is joined on table b. 'b_id' is the primary key for table b, and is found in table a (thought it is not part of a's key). The key for a is irrelevant to the data I need to pull, but can be stated as "a_id" for simplicity.
How do I:
Restrict these records to the past twelve months from the current date.
Take the total for any and all values of b.id, and categorize them by month. This is in addition to the totals of b.id by year. The date is stored in field "date_occurred" in table 'a' as a standard date/time type.
The schema at the end should look something like this, assuming that the current month is October and the year is 2016:
b.id | b_totals | Nov. 2015 | Dec. 2015 | Jan. 2016 .... Oct. 2016
__________________________________________________________________
ID_1 1 0 0 0 1
ID_2 3 2 0 1 0
ID_3 5 1 1 3 0
EDIT: I should probably clarify that I'm counting the records in table 'a' where field 'f' has a certain value 'v.' From these records, I need to group them by building then by month/date. I updated my ISNULL query to make this more clear, as well as the keys for a and b. "date_occured" should be in table a, not b, that was a mistake/typo on my end.
If it helps, the best way I can describe the data from a high level without giving away any sensitive data:
'b' is a table of locations, and 'b.b_id' is the ID for each location
'a' is a table of events. The location for these events is found in 'a.b_id' and joined on 'b.b_id' The date that each event occured is in 'a.date_occurred'
I need to restrict the type of events to a certain value. In this case, the type is field 'type.' This is the "where" clause in my ISNULL SQL query that gets the totals by location.
From all the events of this particular type, I need to count how many times this event occurred in the past year for each location. Once I have these totals from the past year, I need to count them by month.
Table structure:
The table structure of a is something like
a.a_id | a.b_id | a.type | a.date_occurred
Again, I do not need the ID's from a: just a series of counts based on type, b_id, and date_occurred.
EDIT 2: I restricted the totals of b_id to the past year with the following query:
SELECT ISNULL(
SELECT COUNT(*)
FROM a
WHERE a.type = 'v'
AND b.b_id = a.b_id
AND a.date_occurred BETWEEN (DATEADD(yyyy, -1, GETDATE()) AND (GETDATE())
), 0) AS b_totals
Now need to do this with a PIVOT and the months.
In an attempt to make this sufficiently detailed from the absolute minimum of detail provided in the question I have created these 2 example tables with some data:
CREATE TABLE Bexample
([ID] int)
;
INSERT INTO Bexample
([ID])
VALUES
(1),
(2),
(3),
(4),
(5),
(6),
(7),
(8),
(9)
;
CREATE TABLE Aexample
([ID] int, [B_PK] int, [SOME_DT] datetime)
;
INSERT INTO Aexample
([ID], [B_PK], [SOME_DT])
VALUES
(1, 1, '2015-01-01 00:00:00'),
(2, 2, '2015-02-01 00:00:00'),
(3, 3, '2015-03-01 00:00:00'),
(4, 4, '2015-04-01 00:00:00'),
(5, 5, '2015-05-01 00:00:00'),
(6, 6, '2015-06-01 00:00:00'),
(7, 7, '2015-07-01 00:00:00'),
(8, 8, '2015-08-01 00:00:00'),
(9, 9, '2015-09-01 00:00:00'),
(10, 1, '2015-10-01 00:00:00'),
(11, 2, '2015-11-01 00:00:00'),
(12, 3, '2015-12-01 00:00:00'),
(13, 1, '2016-01-01 00:00:00'),
(14, 2, '2016-02-01 00:00:00'),
(15, 3, '2016-03-01 00:00:00'),
(16, 4, '2016-04-01 00:00:00'),
(17, 5, '2016-05-01 00:00:00'),
(18, 6, '2016-06-01 00:00:00'),
(19, 7, '2016-07-01 00:00:00'),
(20, 8, '2016-08-01 00:00:00'),
(21, 9, '2016-09-01 00:00:00'),
(22, 1, '2016-10-01 00:00:00'),
(23, 2, '2016-11-01 00:00:00'),
(24, 3, '2016-12-01 00:00:00')
;
Now, using those tables and data I can generate a result table like this:
id Nov 2015 Dec 2015 Jan 2016 Feb 2016 Mar 2016 Apr 2016 May 2016 Jun 2016 Jul 2016 Aug 2016 Sep 2016 Oct 2016
1 0 0 1 0 0 0 0 0 0 0 0 1
2 1 0 0 1 0 0 0 0 0 0 0 0
3 0 1 0 0 1 0 0 0 0 0 0 0
4 0 0 0 0 0 1 0 0 0 0 0 0
5 0 0 0 0 0 0 1 0 0 0 0 0
6 0 0 0 0 0 0 0 1 0 0 0 0
7 0 0 0 0 0 0 0 0 1 0 0 0
8 0 0 0 0 0 0 0 0 0 1 0 0
9 0 0 0 0 0 0 0 0 0 0 1 0
Using a query that needs both a "common table expression (CTE) and "dynamic sql" to produce that result:
"Dynamic SQL" is a query that generates SQL which is then executed. This is needed because the column names change month to month. So, for the dynamic sql we declare 2 variables that will hold the generated SQL. One of these is to store the columns names, which gets used in 2 places, and the other is to hold the completed query. Note instead of executing this you may display the generated SQL as you evelop your solution (note the comments near execute at the end of the query).
In addition to the example tables and data, we also have a "time series" of 12 months to consider. This is "dynamic" as it is calculated from today's date and I have assumed that if today is any day within November 2016, that "the last 12 months" starts at 1 Nov 2015, and concludes at 31 Oct 2016 (i.e. 12 full months, no partial months).
The core of calculating this is here:
DATEADD(month,-12, DATEADD(month, DATEDIFF(month,0,GETDATE()), 0) )
which firstly locates the first day of the current month with DATEDIFF(month,0,GETDATE()) then deducts a further 12 months from that date. With that as a start date a "recursive CTE" is used to generate 12 rows, one for each month for the past 12 full months.
The purpose of these 12 rows is to ensure that when we consider the actual table data there will be no gaps in the 12 columns. This is achieved by using the generated 12 rows as the "from table" in our query, and the "A" table is LEFT JOINED based on the year/month of a date column [some_dt] to the 12 monthly rows.
So, we generate 12 rows join the sample data to these which is used to generate the SQL necessary for a "PIVOT" of the data. Here it is useful to actually see that an example of that generated sql, which looks like this:
SELECT id, [Nov 2015],[Dec 2015],[Jan 2016],[Feb 2016],[Mar 2016],[Apr 2016],[May 2016],[Jun 2016],[Jul 2016],[Aug 2016],[Sep 2016],[Oct 2016] FROM
(
select
format([mnth],'MMM yyyy') colname
, b.id
, a.b_pk
from #mylist
cross join bexample b
left join aexample a on #mylist.mnth = DATEADD(month, DATEDIFF(month,0,a.some_dt), 0)
and b.id = a.b_pk
) sourcedata
pivot
(
count([b_pk])
FOR [colname] IN ([Nov 2015],[Dec 2015],[Jan 2016],[Feb 2016],[Mar 2016],[Apr 2016],[May 2016],[Jun 2016],[Jul 2016],[Aug 2016],[Sep 2016],[Oct 2016])
) p
So, hopefully you can see in that generated SQL code that the dynamically created 12 rows become 12 columns. Note that because we are executing "dynamic sql" the 12 rows we generated as a CTE need to be stored as a "temporary table" (#mylist).
The query to generate AND execute that SQL is this.
DECLARE #cols AS VARCHAR(MAX)
DECLARE #query AS VARCHAR(MAX)
;with mylist as (
select DATEADD(month,-12, DATEADD(month, DATEDIFF(month,0,GETDATE()), 0) ) as [mnth]
union all
select DATEADD(month,1,[mnth])
from mylist
where [mnth] < DATEADD(month,-1, DATEADD(month, DATEDIFF(month,0,GETDATE()), 0) )
)
select [mnth]
into #mylist
from mylist
SELECT #cols = STUFF((SELECT ',' + QUOTENAME(format([mnth],'MMM yyyy'))
FROM #mylist
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
SET #query = 'SELECT id, ' + #cols + ' FROM
(
select
format([mnth],''MMM yyyy'') colname
, b.id
, a.b_pk
from #mylist
cross join bexample b
left join aexample a on #mylist.mnth = DATEADD(month, DATEDIFF(month,0,a.some_dt), 0)
and b.id = a.b_pk
) sourcedata
pivot
(
count([b_pk])
FOR [colname] IN (' + #cols + ')
) p '
--select #query -- use select to inspect the generated sql
execute(#query) -- once satisfied that sql is OK, use execute
drop table #mylist
You can see this working at: http://rextester.com/VVGZ39193
I want to share another attempt at explaining the issues faced by your requirements.
To follow this you MUST understand this sample data. I have 2 tables #events (a) and #locations (b). The column names should be easy to follow I hope. The
declare #Events table
( [id] int IDENTITY(1007,2)
, [b_id] int
, [date_occurred] datetime
, [type] varchar(20)
)
;
INSERT INTO #Events
([b_id], [date_occurred],[type])
VALUES
(1, '2015-01-11 00:00:00','v'),
(2, '2015-02-21 00:00:00','v'),
(3, '2015-03-11 00:00:00','v'),
(4, '2015-04-21 00:00:00','v'),
(5, '2015-05-11 00:00:00','v'),
(6, '2015-06-21 00:00:00','v'),
(1, '2015-07-11 00:00:00','v'),
(2, '2015-08-11 00:00:00','v'),
(3, '2015-09-11 00:00:00','v'),
(5, '2015-10-11 00:00:00','v'),
(5, '2015-11-21 00:00:00','v'),
(6, '2015-12-21 00:00:00','v'),
(1, '2016-01-21 00:00:00','v'),
(2, '2016-02-21 00:00:00','v'),
(3, '2016-03-21 00:00:00','v'),
(4, '2016-04-21 00:00:00','v'),
(5, '2016-05-21 00:00:00','v'),
(6, '2016-06-21 00:00:00','v'),
(1, '2016-07-11 00:00:00','v'),
(2, '2016-08-21 00:00:00','v'),
(3, '2016-09-21 00:00:00','v'),
(4, '2016-10-11 00:00:00','v'),
(5, '2016-11-11 00:00:00','v'),
(6, '2016-12-11 00:00:00','v');
declare #Locations table
([id] int, [name] varchar(13))
;
INSERT INTO #Locations
([id], [name])
VALUES
(1, 'Atlantic City'),
(2, 'Boston'),
(3, 'Chicago'),
(4, 'Denver'),
(5, 'Edgbaston'),
(6, 'Melbourne')
;
OK. So with that data we can easily create a set of counts using this query:
select
b.id
, b.name
, format(a.date_occurred,'yyyy MMM') mnth
, count(*)
FROM #events a
inner join #locations b ON b.id = a.b_id
WHERE a.type = 'v'
and a.date_occurred >= DATEADD(month,-12, DATEADD(month, DATEDIFF(month,0,GETDATE()), 0) )
group by
b.id
, b.name
, format(a.date_occurred,'yyyy MMM')
And that output looks like this:
id name mnth
-- ------------- -------- -
1 Atlantic City 2016 Jan 1
1 Atlantic City 2016 Jul 1
2 Boston 2016 Aug 1
2 Boston 2016 Feb 1
3 Chicago 2016 Mar 1
3 Chicago 2016 Sep 1
4 Denver 2016 Apr 1
4 Denver 2016 Oct 1
5 Edgbaston 2015 Nov 1
5 Edgbaston 2016 May 1
5 Edgbaston 2016 Nov 1
6 Melbourne 2015 Dec 1
6 Melbourne 2016 Dec 1
6 Melbourne 2016 Jun 1
So, with a "simple" query that is easy to pass parameters into, the output is BY ROWS
and the column headings are FIXED
NOW do you understand why transposing those rows into columns, with VARIABLE COLUMN HEADING forces the use of dynamic sql?
Your requirements, no matter how many words you throw at it, leads to complexity in the sql.
You can run the above data/query here: https://data.stackexchange.com/stackoverflow/query/574718/count-and-group-records-by-month-and-field-value-from-the-last-year
I am working on a Data Warehouse project and the client provides daily sales data. On-hand quantities are provided in most lines but are often missing. I need help on how to fill those missing values based on prior OH and sales information.
Here's a sample data:
Line# Store Item OnHand SalesUnits DateKey
-----------------------------------------------
1 001 A 100 20 1
2 001 A 80 10 2
3 001 A null 30 3 --[OH updated with 70 (80-10)]
4 001 A null 5 4 --[OH updated with 40 (70-30)]
5 001 A 150 10 5 --[OH untouched]
6 001 B null 4 1 --[OH untouched - new item]
7 001 B 80 12 2
8 001 B null 10 3 --[OH updated with 68 (80-12]
Lines 1 and 2 are not to be updated because OnHand quantities exist.
Lines 3 and 4 are to be updated based on their preceding rows.
Line 5 is to be left untouched because OnHand is provided.
Line 6 is to be left untouched because it is the first row for Item B
Is there a way I can do this in a set operation? I know I can do it easily using a fast_forward cursor but it will take a long time (15M+ rows).
Thanks for your help!
Test data:
declare #t table(
Line# int, Store char(3), Item char, OnHand int, SalesUnits int, DateKey int
)
insert #t values
(1, '001', 'A', 100, 20, 1),
(2, '001', 'A', 80 , 10, 2),
(3, '001', 'A', null, 30, 3),
(4, '001', 'A', null, 5, 4),
(5, '001', 'A', 150, 10, 5),
(6, '001', 'B', null, 4, 1),
(7, '001', 'B', null, 4, 2),
(8, '001', 'B', 80, 12, 3),
(9, '001', 'B', null, 10, 4)
Script to populate not using cursor:
;with a as
(
select Line#, Store, Item, OnHand, SalesUnits, DateKey, 1 correctdata from #t where DateKey = 1
union all
select t.Line#, t.Store, t.Item, coalesce(t.OnHand, a.onhand - a.salesunits), t.SalesUnits, t.DateKey, t.OnHand from #t t
join a on a.DateKey = t.datekey - 1 and a.item = t.item and a.store = t.store
)
update t
set OnHand = a.onhand
from #t t join a on a.line# = t.line#
where a.correctdata is null
Script to populate using cursor:
declare #datekey int, #store int, #item char, #Onhand int,
#calculatedonhand int, #salesunits int, #laststore int, #lastitem char
DECLARE sales_cursor
CURSOR FOR
SELECT datekey+1, store, item, OnHand -SalesUnits, salesunits
FROM #t sales
order by store, item, datekey
OPEN sales_cursor;
FETCH NEXT FROM sales_cursor
INTO #datekey, #store, #item, #Onhand, #salesunits
WHILE ##FETCH_STATUS = 0
BEGIN
SELECT #calculatedonhand = case when #laststore = #store and #lastitem = #item
then coalesce(#onhand, #calculatedonhand - #salesunits) else null end
,#laststore = #store, #lastitem = #item
UPDATE s
SET onhand=#calculatedonhand
FROM #t s
WHERE datekey = #datekey and #store = store and #item = item
and onhand is null and #calculatedonhand is not null
FETCH NEXT FROM sales_cursor
INTO #datekey, #store, #item, #Onhand, #salesunits
END
CLOSE sales_cursor;
DEALLOCATE sales_cursor;
I recommand you use the cursor version, I doubt you can get a decent performance using the recursive query. I know people in here hate cursors, but when your table has that size, it can be the only solution.