I have a table which logs each individual piece produced across several production machines, going back a number of years. Periodically (e.g. once per week) I want to check this table to establish "best performance" records for each machine and product combination, storing them in a new table according to the following rules;
The machine must have produced a minimum of 10,000 parts over a 10 day period - if only 9000 parts were produced over 10 days, this is an invalid record
The machine must have been running the same product without changing over for the entire period i.e. if on day 5 the product changed, this is an invalid record
The Performance data table looks like below [VisionMachineResults]
ID
MCSAP
DateTime
ProductName
InspectionResult
1
123456
2020-01-01 08:29:34:456
Product A
0
2
123456
2020-01-01 08:45:50:456
Product B
1
3
844214
2020-01-01 08:34:48:456
Product A
2
4
978415
2020-01-02 09:29:26:456
Product C
0
5
985633
2020-01-04 23:29:11:456
Product A
2
I am able to produce a result which gives a list of individual days performance per SAP / Product Combination, but I then need to process the data in a complex loop outside of SQL to establish the 10 day groups.
My current query is:
SELECT CAST(DateTime AS date) AS InputDate,
MCSAP,
ZAssetRegister.LocalName,
ProductName,
SUM(CASE WHEN InspectionResult = 0 THEN 1 END) AS OKParts,
COUNT(CASE WHEN InspectionResult > 0 THEN 1 END) AS NGParts
FROM [VisionMachineResults]
INNER JOIN ZAssetRegister ON VisionMachineResults.MCSAP = ZAssetRegister.SAP_Number
GROUP BY CAST(DateTime AS date),
MCSAP,
ProductName,
ZAssetRegister.LocalName
ORDER BY InputDate,
ZAssetRegister.LocalName;
Would it be possible to have the SQL query give the result in 10 day groups, instead of per individual day i.e.
01-01-2021 to 11-01-2021 | Machine 1 | Product 1 | 20,000 | 5,000
02-01-2021 to 12-01-2021 | Machine 1 | Product 1 | 22,000 | 1,000
03-01-2021 to 13-01-2021 | Machine 1 | Product 1 | 18,000 | 4,000
etc...
I would then iterate through the rows to find the one with the best percentage of OK parts. Any ideas appreciated!
This process needs to be considered in many levels. First, you mention 10 consecutive days. We dont know if those days include weekends, if the machines are running 24/7. If the dates running can skip over holidays as well? So, 10 days could be Jan 1 to Jan 10. But if you skip weekends, you only have 6 actual WEEKDAYS.
Next, consideration of a machine working on more than one product, such as a switching between dates, or even within a single day.
As a commenter indicated, having column names by same as a reserved word (such as DateTime), bad practice and try to see if any new columns are common key words that may cause confusion and avoid them.
You also mention that you had to do complex looping checks, and how to handle joining out to 10 days, the splits, etc. I think I have a somewhat elegant approach to doing this and should prove to be rather simple in the scheme of things.'
You are using SQL-Server, so I will do this using TEMP tables via "#" table names. This way, when you are done with a connection, or a call to making this a stored procedure, you dont have to keep deleting and recreating them. That said, let me take you one-step-at-a-time.
First, I'm creating a simple table matching your structure, even with the DateTime context.
CREATE TABLE VisionMachineResults
(
ID int IDENTITY(1,1) NOT NULL,
MCSAP nvarchar(6) NOT NULL,
DateTime datetime NOT NULL,
ProductName nvarchar(10) NOT NULL,
InspectionResult int NOT NULL,
CONSTRAINT ID PRIMARY KEY CLUSTERED
(
[ID] ASC
) WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
GO
Now, I'm inserting the data, similar to what you have, but not millions of rows. You mention you are looking for 10 days out, so I just padded the end with several extras to simulate that. I also explicitly forced a gap change of product by the one machine on Jan 5th. Additionally, I added a product change on Jan 7th to trigger this a "break" within your 10-day consideration. You'll see the results later.
insert into VisionMachineResults
(MCSAP, [DateTime], ProductName, InspectionResult )
values
( '123456', '2020-01-01 08:29:34.456', 'Product A', 0 ),
( '123456', '2020-01-01 08:29:34.456', 'Product B', 1 ),
( '844214', '2020-01-01 08:29:34.456', 'Product A', 2 ),
( '978415', '2020-01-02 08:29:34.456', 'Product C', 0 ),
( '985633', '2020-01-04 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-05 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-05 08:29:34.456', 'Product B', 0 ),
( '985633', '2020-01-06 08:29:34.456', 'Product A', 2 ),
( '985633', '2020-01-07 08:29:34.456', 'Product B', 0 ),
( '985633', '2020-01-08 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-09 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-10 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-11 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-12 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-13 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-14 08:29:34.456', 'Product A', 1 ),
( '985633', '2020-01-15 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-16 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-17 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-18 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-19 08:29:34.456', 'Product A', 0 ),
( '985633', '2020-01-20 08:29:34.456', 'Product A', 0 )
go
So now, consider this the baseline of YOUR production data. My first query will be doing a bunch of things, but storing the pre-aggregations INTO #tmpPartDailyCounts result table. This way you can look at them at the different stages to apply sanity check to my approach.
Here, on a per machine (MCSAP), and Date (without time portion), I am grabbing certain aggregates, and keeping them grouped by machine and date.
select
VMR.MCSAP,
cast(VMR.DateTime as Date) as InputDate,
min( VMR.ProductName ) ProductName,
max( VMR.ProductName ) LastProductName,
count( distinct VMR.ProductName ) as MultipleProductsSameDay,
sum( case when VMR.InspectionResult = 0 then 1 else 0 end ) OKParts,
sum( case when NOT VMR.InspectionResult = 0 then 1 else 0 end ) BadParts,
count(*) TotalParts
into
#tmpPartDailyCounts
from
VisionMachineResults VMR
group by
VMR.MCSAP,
cast(VMR.DateTime as Date)
You were joining to an asset table and dont think you really need that. If the machine made the product, does it matter if a final assembly is complete? Dont know, you would know better.
Now, the aggregates and why. The min( VMR.ProductName ) ProductName and max( VMR.ProductName ) LastProductName, this is just to carry-forward the product name created on the date in question for any final output. If on a given day, only one product was made, it would be the same anyhow, just pick one. However, if on any day there are multiple products, the MIN() and MAX() will be of different values. If the same product across all that are built, then both values would be the same -- ON ANY SINGLE GIVEN DATE.
The rest are simple aggregates of OK parts, BAD parts (something was wrong), but also the TOTAL Parts created, regardless of any inspection failure. This is the primary qualifier for you to hit you 10,000, but if you wanted to change to 10,000 GOOD parts, change accordingly.
select
VMR.MCSAP,
cast(VMR.DateTime as Date) as InputDate,
min( VMR.ProductName ) ProductName,
max( VMR.ProductName ) LastProductName,
count( distinct VMR.ProductName ) as MultipleProductsSameDay,
sum( case when VMR.InspectionResult = 0 then 1 else 0 end ) OKParts,
sum( case when NOT VMR.InspectionResult = 0 then 1 else 0 end ) BadParts,
count(*) TotalParts
into
#tmpPartDailyCounts
from
VisionMachineResults VMR
group by
VMR.MCSAP,
cast(VMR.DateTime as Date)
Now, at this point, I have a pre-aggregation done on a per machine and date basis. Now, I want to get some counter that is sequentially applied on a per date that a product was done. I will pull this result into a temp table #tmpPartDays. By using the over/partition, this will create a result that first puts the records in order of MCSAP, then by the date and dumps an output with whatever the ROW_NUMBER() is to that. So, if there is no activity for a given machine such as over a weekend or holiday that the machine is not running, the SEQUENTIAL counter via OVER/PARTITION will keep them sequentially 1 through however many days... Again, query the result of this table and you'll see it.
By querying against the pre-aggregated table, that may account for 500k records and results down to say 450 via per machine/day, This query is now only querying against the 450 and will be very quick.
SELECT
PDC.MCSAP,
PDC.InputDate,
MultipleProductsSameDay,
ROW_NUMBER() OVER(PARTITION BY MCSAP
ORDER BY [InputDate] )
AS CapDay
into
#tmpPartDays
FROM
#tmpPartDailyCounts PDC
ORDER BY
PDC.MCSAP;
Now, is the kicker, tying this all together. I'm starting with just the #tmpPartDays JOINED to itself on the same MCSAP AND a MUST-HAVE matching record 10 days out... So this resolves issues of weekend / holidays since serial consecutive.
This now give me the begin/end date range such as 1-10, 2-11, 3-12, 4-13, etc.
I then join to the tmpPartDailyCounts result on the same part AND the date is at the respective begin (PD.InputDate) and END (PD2.InputDate). I re-apply the same aggregates to get the total counts WITHIN EACH Part + 10 day period. Run this query WITHOUT the "HAVING" clause to see what is coming out.
select
PD.MCSAP,
PD.InputDate BeginDate,
PD2.InputDate EndDate,
SUM( PDC.MultipleProductsSameDay ) as TotalProductsMade,
sum( PDC.OKParts ) OKParts,
sum( PDC.BadParts ) BadParts,
sum( PDC.TotalParts ) TotalParts,
min( PDC.ProductName ) ProductName,
max( PDC.LastProductName ) LastProductName
from
#tmpPartDays PD
-- join again to get 10 days out for the END cycle
JOIN #tmpPartDays PD2
on PD.MCSAP = PD2.MCSAP
AND PD.CapDay +9 = PD2.CapDay
-- Now join to daily counts for same machine and within the 10 day period
JOIN #tmpPartDailyCounts PDC
on PD.MCSAP = PDC.MCSAP
AND PDC.InputDate >= PD.InputDate
AND PDC.InputDate <= PD2.InputDate
group by
PD.MCSAP,
PD.InputDate,
PD2.InputDate
having
SUM( PDC.MultipleProductsSameDay ) = 10
AND min( PDC.ProductName ) = max( PDC.LastProductName )
AND SUM( PDC.TotalParts ) >= 10
Finally, the elimination of the records you DONT want. Since I dont have millions of records to simulate, just follow along. I am doing a HAVING on
SUM( PDC.TotalParts ) >= 10
SUM( PDC.MultipleProductsSameDay ) = 10
If on ANY day there are MORE than 1 product created, the count would be 11 or more, thus indicating not the same product, so that would cause an exclusion. But also, if at the tail-end of data such as only 7 days of production, it would never HIT 10 which was your 10-day qualifier also.
2. AND min( PDC.ProductName ) = max( PDC.LastProductName )
Here, since we are spanning back to the DAILY context, if ANY product changes on any date, the Product Name (via min) and LastProductName (via max) will change, regardless of the day, and regardless of the name context. So, by making sure both the min() and max() are the same, you know it is the same product across the entire span.
3. AND SUM( PDC.TotalParts ) >= 10
Finally, the count of things made. In this case, I did >= 10 because I was only testing with 1 item per day, thus 10 days = 10 items. In your scenario, you may have 987 in one day, but 1100 in another, thus balancing low and high production days to get to that 10,000, but for sample of data, just change YOUR context to the 10,000 limit minimum.
This SQLFiddle shows the results as it gets down to the per machine/day and showing the sequential activity. The last MCSAP machine starts on Jan 4th, but has a sequential day row assignment starting at 1 to give proper context to the 1-10, 2-11, etc.
First SQL Fiddle showing machine/day
Second fiddle shows final query WITHOUT the HAVING clause and you can see the first couple rows of TotalProductsMade is 11 which means SOMETHING on any of the day-span in question created different products and would be excluded from final. For the begin and end dates of Jan 6-15 and Jan 7-16, you will see the MIN/MAX products showing Product A and Product B, thus indicating that SOMEWHERE within its 10-day span a product switched... These too will be excluded.
The FINAL query This query shows the results with the HAVING clause applied.
One option that comes to my mind is the use of a numbers table (google Jeff Moden on SQL Server Central for more background).
The number table then uses a start date (from the range of dates to investigate) that in addition to generate a date to link to also generates a "bucket" by which to group afterwards.
Similar to:
-- generate date frame from and to
DECLARE
#date_start date = Convert( date, '20211110', 112 ),
#date_end date = Convert( date, '20220110', 112 )
;
WITH
cteN
(
Number
)
AS
( -- build a list of 10 single digit numbers
SELECT Cast( 0 AS int ) AS Number UNION SELECT 1 UNION SELECT 2 UNION SELECT 3 UNION SELECT 4 UNION SELECT 5 UNION SELECT 6 UNION SELECT 7 UNION SELECT 8 UNION SELECT 9
)
,
cteNumbers
(
Number
)
AS
( -- splice single digit numbers to list from 0 to 99999
SELECT
cN10000.Number * 10000 + cN1000.Number * 1000 + cN100.Number * 100 + cN10.Number * 10 + cN1.Number
FROM
cteN AS cN10000
CROSS JOIN cteN AS cN1000
CROSS JOIN cteN AS cN100
CROSS JOIN cteN AS cN10
CROSS JOIN cteN AS cN1
)
,
cteBucketOffset
(
DatediffNum,
Offset
)
AS
( -- determine the offset in datediffs to number buckets later correctly
SELECT
Cast( Datediff( dd, #date_start, #date_end ) AS int ) - 1 AS DatediffNum,
Cast( Datediff( dd, #date_start, #date_end ) % 10 AS tinyint ) - 1 AS Offset
)
,
cteDates
(
Dated,
Bucket,
BucketNumber,
BucketOffset,
DatediffNum
)
AS
( -- generate list of dates with bucket batches and numbers
SELECT
Dateadd( dd, cN.Number * -1, #date_end ) AS Dated,
Cast( ( cBO.Offset + cN.Number ) / 10 AS int ) AS Bucket,
Cast( ( cBO.Offset + cN.Number ) % 10 AS tinyint ) AS BucketNumber,
cBO.Offset,
cBO.DatediffNum
FROM
cteNumbers AS cN
CROSS JOIN cteBucketOffset AS cBO
WHERE
cN.Number <= Datediff( dd, #date_start, #date_end )
)
SELECT
*
FROM
cteDates AS cD
ORDER BY
cD.Dated ASC
;
Long winded due to showing each step. The result is a table-on-the-fly usable to join back to the raw data. "Bucket" can then be used instead of the date itself to group raw data.
Once this data is built then decisions can be made on the grouped conditions like having a minimum number of rows.
Seems just a matter of grouping on the year and the day of the year divided by 10.
SELECT
CONCAT(CONVERT(VARCHAR(10),MIN([DateTime]),105), ' to ', CONVERT(VARCHAR(10), MAX([DateTime]), 105)) AS InputDateRange
, MCSAP
, MAX(ZAssetRegister.LocalName) AS LocalName
, ProductName
, SUM(CASE WHEN InspectionResult = 0 THEN 1 END) AS OKParts
, COUNT(CASE WHEN InspectionResult > 0 THEN 1 END) AS NGParts
, COUNT(DISTINCT CAST([Datetime] AS DATE)) AS total_days
FROM VisionMachineResults
JOIN ZAssetRegister
ON VisionMachineResults.MCSAP = ZAssetRegister.SAP_Number
GROUP BY
DATEPART(YEAR, [DateTime]),
CEILING(DATEPART(DAYOFYEAR, [DateTime])/10.0),
MCSAP,
ProductName
ORDER BY
MIN([DateTime]),
MAX(ZAssetRegister.LocalName);
Simplified test on db<>fiddle here
Data Presentation
Would like to calculate year to date and previous year to date current month on sql view so that to simply data presentation on ssrs to make it run faster. Is there a way to write a view which can perform this ?
Ignoring the fact that I think you have some errors in your Previous YTD summary numbers..
I recreated the data as per your example
CREATE TABLE #t (TransDate date, Customer varchar(30), Amount float)
INSERT INTO #t VALUES
('2020-09-21', 'Customer 1', 200),
('2020-09-22', 'Customer 2', 300),
('2020-08-03', 'Customer 2', 450),
('2020-08-04', 'Customer 1', 1200),
('2019-09-14', 'Customer 1', 859),
('2019-02-05', 'Customer 2', 230),
('2019-07-26', 'Customer 2', 910),
('2019-11-17', 'Customer 1', 820)
Then the following statement will produce what you need. It is NOT the most elegant way of doing this but it will convert to a view easily and was all I could come up with in the time I had.
SELECT
m.Customer
, m.MTD as [Current Month]
, y.YTD as [Current YTD]
, p.YTD as [Previous YTD]
FROM (
SELECT Customer, Yr = Year(TransDate), Mn = MONTH(TransDate), MTD = SUM(Amount) FROM #t t WHERE MONTH(TransDate) = MONTH(GetDate()) and YEAR(TransDate) = YEAR(GetDate())
GROUP by Customer, YEAR(TransDate), MONTH(TransDate)
) m
JOIN (SELECT Customer, Yr = YEAR(TransDate), YTD = SUM(Amount) FROM #t t GROUP by Customer, YEAR(TransDate)) y on m.Customer =y.Customer and m.Yr = y.Yr
JOIN (SELECT Customer, Yr = YEAR(TransDate), YTD = SUM(Amount) FROM #t t GROUP by Customer, YEAR(TransDate)) p on y.Customer =p.Customer and y.Yr = p.Yr + 1
This gives the following results (which don;t match your example but I think your sample is incorrect)
Please I need your help..
for an Objective
match SO (Sales Order) quantity to PO (Purchase Order) quantity based on FIFO (First In, First Out) where the first stock items purchased must be the first items sold.
I have a table Stock which use to track the movement of stock in and out of imaginary stock warehouse. The warehouse is initially empty, and stock then moves into the warehouse as a result of a stock purchase (‘IN’) and stock moves out of the warehouse when it is sold (‘OUT’). Each type of stock item is identified by an ItemID. Each movement of stock in or out of the warehouse, due to a purchase or sale of a given item, results in a row being added to the Stock table, uniquely identified by the value in the StockID identify column, and describing how many items were added or removed and the date of the transaction.
Table stock :
StockId DocumentID ItemID TranDate TranCode Quantity
------------------------------------------------------------
1 PO001 A021 2016.01.01 IN 3
4 SO010 A021 2016.01.02 OUT 2
2 PO002 A021 2016.01.10 IN 7
3 PO003 A021 2016.02.01 IN 9
5 SO011 A021 2016.02.11 OUT 8
6 SO012 A023 2016.02.12 OUT 6
How could I write a query to give output like the table below?
SOID POID Quantity
------------------------
SO010 PO001 2
SO011 PO001 1
SO011 PO002 7
SO012 PO003 6
So, seeing as no one else has given this a go, I figure I'll post something that resembles an answer (I believe).
Essentially, what you want to do is keep track of the number of things you have in stock and the number of things that have gone out, based on the date (I haven't accounted for multiple things coming in or going out on the same date, though).
DECLARE #Table TABLE
(
DocumentID VARCHAR(10) NOT NULL,
TranCode VARCHAR(3) NOT NULL,
TranDate DATE NOT NULL,
Quantity INT NOT NULL
); -- I'm ignoring the other columns here because they don't seem important to your overall needs.
INSERT #Table (DocumentID, TranCode, TranDate, Quantity)
VALUES
('PO001', 'IN', '2016-01-01', 3),
('SO010', 'OUT', '2016-01-02', 2),
('PO002', 'IN', '2016-01-10', 7),
('PO003', 'IN', '2016-02-01', 9),
('SO011', 'OUT', '2016-02-11', 8),
('SO012', 'OUT', '2016-02-12', 6);
WITH CTE AS
(
SELECT DocumentID,
TranCode,
TranDate,
Quantity,
RunningQuantity = -- Determine the current IN/OUT totals.
(
SELECT SUM(Quantity)
FROM #Table
WHERE TranCode = T.TranCode
AND TranDate <= T.TranDate
),
PrevQuantity = -- Keep track of the previous IN/OUT totals.
(
SELECT ISNULL(SUM(Quantity), 0)
FROM #Table
WHERE TranCode = T.TranCode
AND TranDate < T.TranDate
)
FROM #Table T
)
SELECT Outgoing.DocumentID,
Incoming.DocumentID,
Quantity =
CASE WHEN Outgoing.RunningQuantity <= Incoming.RunningQuantity AND Outgoing.PrevQuantity >= Incoming.PrevQuantity
THEN Outgoing.RunningQuantity - Outgoing.PrevQuantity
WHEN Outgoing.RunningQuantity <= Incoming.RunningQuantity AND Outgoing.PrevQuantity < Incoming.PrevQuantity
THEN Outgoing.RunningQuantity - Incoming.PrevQuantity
ELSE Incoming.RunningQuantity - Outgoing.PrevQuantity
END
FROM CTE Outgoing
JOIN CTE Incoming ON
Incoming.TranCode = 'IN'
AND Incoming.RunningQuantity > Outgoing.PrevQuantity
AND Incoming.PrevQuantity < Outgoing.RunningQuantity
WHERE Outgoing.TranCode = 'OUT'
ORDER BY Outgoing.TranDate;
Note: I would highly recommend you keep track of the information in a better way. For example, create a table that actually details which orders took what from which other orders (an order transaction table or something), because while it's not impossible to achieve what you want with the way your data is structured, it's much less complicated if you just store more helpful data.
I hope someone can help with this issue I have, which is I am trying to work out a weekly average from the following data example:
Practice ID Cost FiscalWeek
1 10.00 1
1 33.00 2
1 55.00 3
1 18.00 4
1 36.00 5
1 24.00 6
13 56.00 1
13 10.00 2
13 24.00 3
13 30.00 4
13 20.00 5
13 18.00 6
What I want is to group by the Practice ID but work out the average for each practice (there are over 500 of these not just those above) and work this out for each week so for example at Week 1 there will be no average, but Week 2 will be the average of Weeks 1 and 2, then Week 3 will be the average of Weeks 1, 2 and 3 and then so on. I need to then show this by Practice ID and for each Fiscal Week.
At the moment I have some code that is not pretty and there has to be an easier way, this code is:
I pass all the data into a table variable then using a CTE I then use case statements to set each individual week like:
CASE WHEN fiscalweek = 1 THEN cost ELSE 0 END AS [1],
CASE WHEN fiscalweek = 2 THEN cost ELSE 0 END AS [2],
CASE WHEN fiscalweek = 3 THEN cost ELSE 0 END AS [3]
This would then bring back the week 1 cost and so on into it's own column e.g. 1, 2, 3 etc. , then I've used a second CTE to sum the columns for each week so for example to work out week 6 I would use this code:
sum([1]) as 'Average Wk 1',
sum([1]+[2])/2 as 'Average Wk 2',
sum([1]+[2]+[3])/3 as 'Average Wk 3',
sum([1]+[2]+[3]+[4])/4 as 'Average Wk 4',
sum([1]+[2]+[3]+[4]+[5])/5 as 'Average Wk 5'
sum([1]+[2]+[3]+[4]+[5]+[6])/6 as 'Average Wk 6'
I've thought about various different ways of working out this average accurately in T-SQL so I can then drop this into SSRS eventually. I've thought about using a While..Loop, Cursor but failing to see an easy way of doing this.
You are looking for the cumulative average of the averages. In databases that support window/analytic functions, you can do:
select fiscalweek, avg(cost) as avgcost,
avg(avg(cost)) over (order by fiscalweek) as cumavg
from practices p
group by fiscalweek
order by 1;
If you don't have window functions, then you need to use some form of correlated subquery or join:
select p1.fiscalweek, avg(p1.avgcost)
from (select fiscalweek avg(cost) as avgcost
from practices p
group by fiscalweek
) p1 join
(select fiscalweek avg(cost) as avgcost
from practices p
group by fiscalweek
) p2
on p12 <= p1
group by p1.fiscalweek
order by 1;
I do want to caution you that you are calculating the "average of averages". This is different from the cumulative average, which could be calculated as:
select fiscalweek,
(sum(sum(cost)) over (order by fiscalweek) /
sum(count(*)) over (order by fiscalweek)
) avgcost
from practices p
group by fiscalweek
order by 1;
One treats every week as one data point in the final average (what you seem to want). The other weights each week by the number of points during the week (the latter solution). These can produce very different results when weeks have different numbers of points.
I dont know If I fully understand the question:But Try Executing this: should help you:
create table #practice(PID int,cost decimal,Fweek int)
insert into #practice values (1,10,1)
insert into #practice values (1,33,2)
insert into #practice values (1,55,3)
insert into #practice values (1,18,4)
insert into #practice values (1,36,5)
insert into #practice values (1,24,6)
insert into #practice values (13,56,1)
insert into #practice values (13,10,2)
insert into #practice values (13,24,3)
insert into #practice values (13,30,4)
insert into #practice values (13,20,5)
insert into #practice values (13,18,6)
select * from #practice
select pid,Cost,
(select AVG(cost) from #practice p2 where p2.Fweek <= p1.Fweek and p1.pid = p2.pid) WeeklyAVG,
Fweek,AVG(COST) over (Partition by PID) as PIDAVG
from #practice p1;
I think this would work:
SELECT t1.pid,
t1.fiscalweek,
(
SELECT SUM(t.cost)/COUNT(t.cost)
FROM tablename AS t
WHERE t.pid = t1.pid
AND t.fiscalweek <= t1.fiscalweek
) AS average
FROM tablename AS t1
GROUP BY t1.pid, t1.fiscalweek
EDIT
To take into account for fiscal weeks without an entry you can simply exchange
SELECT SUM(t.cost)/COUNT(t.cost)
for
SELECT SUM(t.cost)/t1.fiscalweek
to calculate from week 1 or
SELECT SUM(t.cost)/(t1.fiscalweek - MIN(t.fiscalweek) + 1)
to calculate from the first week of this practice.
If all practice averages should start the same week (and not necessarily week no 1) then you'd have to find the minimum of all week numbers.
Also, this won't work if you're calculating across multiple years, but I assume that is not he case.
I have 2 tables STOCK and ITEMS,
I am trying to get a report showing how total items purchased (ITEMS table- items.quanto), total sales for items(ITEMS table- I assume (items.quanto*items.it_unlist) with description(STOCK table- stock.desc1) by month (ITEMS table-items.odr_date) with classification (which is a field in the STOCK table- stock.assoc).
The owner wants this info for each month for 2011, 2012, and YTD 2013
so total qty sold for item with total sales of that item by month 2011, 2012, 2013 YTD
This is my query
select items.item, items.quanto, SUM(items.QUANTO*items.it_unlist) as [total cost], stock.desc1, items.it_sdate from items
inner join
stock
on
stock.number = items.item
where IT_SDATE between '2011-01-01 00:00:00.0' and '2011-12-31 00:00:00.0'
group by items.item, items.quanto, stock.desc1, items.it_sdate
order by IT_SDATE
I was hoping to get each item totaled sales and qty by month but this is what I figured out on my own…lol
any help is appreciated.
select
item,
right(convert(varchar(8), it_sdate, 3), 5) theMonth,
sum(quanto) totalQuantity,
sum(quanto * it_unlist) totalSales,
max(stock.desc1) descr,
max(stock.assoc) assoc
from
items inner join stock on
items.item = stock.number
where
it_sdate > '2011-01-01'
group by
item,
right(convert(varchar(8), it_sdate, 3), 5)
order by
item,
theMonth
http://sqlfiddle.com/#!3/246d3/18/0
if the item column of the items table is primary key, then you can’t display the each and every item number when you are trying to display the total sales and qty.
And also, the IT_DATE column consists of only one date per month in the table, then only the below query is possible, if not we need to write other query.
if not, you can select.
select i.quanto, sum(QUANTO * it_unlist) as [total list],
s.desc1, i.it_sdate from items i inner join stock s on (s.number = i.item)
where IT_SDATE > 2011-01-01
group by i.it_sdate order by IT_SDATE;