My code is an accumulated total of revenue over a period of time. If a single day is blank (no revenue for that day) I need it to show the totals from the day before. CASE WHEN (today is blank), Yesterday's data ELSE Today's Total
I am not sure what the syntax is on this one.
select distinct
date_trunc('day',admit_date) as admit_date,
revenue,
sum(revenue) over(order by admit_date) as running_rev
from dailyrev
order by admit_date
Expected Results:
Day 1: $100
Day 2: $200
Day 3: (no data so show Day 2 data) $200
Maybe this is what you need:
SELECT admit_date,
prev_revs[cardinality(prev_revs)] AS adj_revenue,
sum(prev_revs[cardinality(prev_revs)])
OVER (ORDER BY admit_date) AS running_sum
FROM (SELECT date_trunc('day', admit_date) AS admit_date,
array_remove(array_agg(revenue)
OVER (order by admit_date),
NULL) AS prev_revs
FROM dailyrev) AS q
ORDER BY admit_date;
Unfortunately PostgreSQL doesn't yet support the IGNORE NULLS clause, then it would have been simpler.
I am not sure if this is what you want, but try this:
SELECT
gs.date::date AS admit_date,
(SELECT revenue FROM dailyrev WHERE admit_date::date = gs.date) AS revenue,
(SELECT SUM(revenue) FROM dailyrev WHERE admit_date::date <= gs.date) AS accumulated_total
FROM
generated_series(
(SELECT MIN(admit_date::date) FROM dailyrev),
(SELECT MAX(admit_date::date) FROM dailyrev),
INTERVAL '1 day'
) gs
ORDER BY gs.date::date;
Yes, it does not look that nice, but..
I am using SQL Server 2014. I have a table like this
create table revenue (id varchar(2), trasdate date, revenue int);
insert into revenue(id, trasdate, revenue)
values ('aa', '2018/09/01', 1234.5),
('aa' , '2018/08/04', 450),
('aa', '2018/07/03',500),
('aa', '2018/06/04',600),
('ab', '2018/09/01', 1234.5),
('ab' , '2018/08/04', 450),
('ab', '2018/07/03',500),
('ab', '2018/06/04',600),
('ab', '2018/05/03', 200),
('ab', '2018/04/02', 150),
('ab', '2018/03/01', 350),
('ab', '2018/02/05', 700),
('aa', '2018/01/07', 400)
;
I am preparing a SQL query to create a SSRS report. I want to calculate a past 3 month average for current and every past 3rd month with result like below. As we are in month of September right now. The result should show something like this:
**id Period Revenue_3Mon**
aa March-May 233
aa June-Aug 516
ab March-May 233
ab June-Aug 516
Though I can figure out about the Period column. I was mainly focussing on getting the Revenue_3Mon. So I initially tried with the below query after some googling. But this query throws an error as incorrect syntax near 'rows' and if I remove rows from the query then it throws an error as Incorrect syntax near the keyword 'between'. And incorrect syntax near i.
select i.id,i.mon,
avg([i.mon_revenue]) over (partition by i.id, i.mon order by [i.id],
[i.mon] rows between 3 preceding and 1 preceding row) as revenue_3mon --
-- using 3 preceding and 1 preceding row you exclude the current row
from (select a.id, month(a.trasdate) as mon,
sum(a.revenue) as mon_revenue
from revenue a
group by a.id, month(a.trasdate)) i
group by i.id, i.mon
order by i.id,i.mon;
After few efforts, I gave up on this query and came up with new solution which was a bit close to my expectation (after lots of trial and errors).
Declare #count as int;
declare #max as int;
set #count = 4
declare #temp as table (id varchar(2), monthoftrasdate int, revenue int,
[3monavg] int);
SET #MAX = (SELECT distinct MAX(a.ROWNUM) FROM (SELECT id, month(trasdate)
as mon, SUM(revenue) TotalRevenue,
-- sum(revenue) as mon_revenue,
ROW_NUMBER() OVER(PARTITION BY ID ORDER BY MONTH(TRASDATE)) AS ROWNUM
FROM revenue
GROUP BY ID, MONTH(TRASDATE)
) A GROUP BY A.ID);
while (#count <= #max )
begin
WITH CTE AS (
SELECT id, month(trasdate) as mon, SUM(revenue) TotalRevenue,
-- sum(revenue) as mon_revenue,
ROW_NUMBER() OVER(PARTITION BY ID ORDER BY MONTH(TRASDATE)) AS
ROWNUM
FROM revenue
GROUP BY ID, MONTH(TRASDATE)
)
insert into #temp
SELECT A.ID,A.MON, a.TotalRevenue
,( SELECT avg(b.TotalRevenue) as avgrev
FROM CTE B
WHERE B.ROWNUM BETWEEN A.ROWNUM-3 AND A.ROWNUM-1
AND A.ID = B.ID --AND A.mon = B.mon
--and b.ROWNUM < a.ROWNUM
and (a.mon > 3 and a.ROWNUM > 3)
GROUP BY B.id
) AS REVENUE_3MON
FROM CTE A
set #count = #count + 1
end
select distinct a.* from #temp a
The reason I had to use 'distinct' is because the query was showing duplicate records for every id and every month. So far the result shows like below
id MonthofTrasdate Revenue 3MonAvg
aa 1 400 NULL
aa 2 700 NULL
aa 3 350 NULL
aa 4 150 483
aa 5 200 400
aa 6 600 233
aa 7 500 316
aa 8 450 433
aa 9 1234 516
ab 1 400 NULL
ab 2 700 NULL
ab 3 350 NULL
ab 4 150 483
ab 5 200 400
ab 6 600 233
ab 7 500 316
ab 8 450 433
ab 9 1234 516
This pulls out past 3 month average for every month. But i will just manipulate the rest on SSRS the way i want it.
As currently my table has no data for previous year. This works for me showing the appropriate result for next couple of months for now. But my concern is when I have to show my boss for next year Jan, Feb and March then it should be able to pull also for these months as well like Oct-Dec (Previous year), Nov-Jan and Dec - Feb. I am struggling to figure out the proper way to put this in my query.
Can you please help me out with this query? And also let me know what is wrong with my former query.
Problems with your first attempt:
You enclosed some of the aliases and column names in square brackets like [i.mon_revenue]. There is no need for square brackets, but if you want to use them, you have to break them up at the dot: [i].[mon_revenue].
In your window function expression, there is one row too many (in the end).
Window functions are applied at the very end (after the rest of the respective query), so you also have to include i.mon_revenue in your GROUP BY clause of the outer query.
Knowing that the inner query will produce one row per id and mon, there will never be preceding rows in an id-mon partition. Therefore, you must not partition by both, but only by id.
To simplify the query after resolving the issues: ordering by a partition column generally makes no sense, and since - as already mentioned - the inner query returns unique id-mon combinations, you don't have to group by these in the outer query. Looking at that query, we see that the outer query just directly selects and uses the values from the inner query, which makes a separation in two queries unneccessary. So, in fact, you wanted to perform the following query, which will produce the rolling 3-month average (I added the monthly TotalRevenue as well):
SELECT id, MONTH(trasdate) AS mon, SUM(revenue) AS TotalRevenue,
AVG(SUM(revenue)) OVER (PARTITION BY id ORDER BY MONTH(trasdate) ROWS BETWEEN 3 PRECEDING AND 1 PRECEDING) AS revenue_3mon
FROM revenue
GROUP BY id, MONTH(trasdate)
ORDER BY id, MONTH(trasdate);
Suggestions on your second attempt:
When calculating the #MAX value, you rely on the fact that each id has revenues for the same number of months. Are you sure?
The code inside the WHILE loop does not depend on #count, so it will add the same data into the #temp table multiple times, which is probably the reason why you thought you needed a DISTINCT. Therfore: No need for the variables, no need for a loop and a #temp, no need for DISTINCT.
The conditions A.mon > 3 and A.rownum > 3 are redundant with your current data. In general, I guess, you don't want to explicitly excluse the months from January to March, so A.mon > 3 should be removed. A.rownum > 3 could be removed, too, unless you really don't want to see a 3-month average when there are only 2 preceding months or less.
As the subquery for the average is restricted to only one id, there's no need for a GROUP BY.
Since the ROW_NUMBER function doesn't care about gaps in the months, I suggest to use a different numbering function, for example DATEDIFF(month, MAX(trasdate), GETDATE()) AS mnum. Of course, the comparison in the WHERE clause of the subquery then has to be changed to B.mnum BETWEEN A.mnum+1 AND A.mnum+3.
So, your second attempt can be reduced to this, which will produce the same result as the above, at least with your sample data, where no gaps in the months exist:
WITH CTE AS (
SELECT id, MONTH(trasdate) AS mon, SUM(revenue) AS TotalRevenue,
DATEDIFF(month, MAX(trasdate), GETDATE()) AS mnum
FROM revenue
GROUP BY id, MONTH(trasdate)
)
SELECT id, mon, TotalRevenue
, (SELECT AVG(B.TotalRevenue)
FROM CTE B
WHERE B.mnum BETWEEN A.mnum+1 AND A.mnum+3
AND A.id = B.id
) AS revenue_3mon
FROM CTE A
ORDER BY id, mnum DESC;
Now, guess what, an expression like my mnum using DATEDIFF increases by one every month as we move to the past, regardless of a change of years, so this might be useful for grouping as well, whether you want to (or can?) use Window functions or not:
With OVER()
SELECT id, MONTH(MIN(trasdate)) AS mon, YEAR(MIN(trasdate)) AS yr, SUM(revenue) AS TotalRevenue,
AVG(SUM(revenue)) OVER (PARTITION BY id ORDER BY MIN(trasdate) ROWS BETWEEN 3 PRECEDING AND 1 PRECEDING) AS revenue_3mon
FROM revenue
GROUP BY id, DATEDIFF(month, trasdate, GETDATE())
ORDER BY id, DATEDIFF(month, trasdate, GETDATE()) DESC;
Without OVER()
WITH CTE AS (
SELECT id, MIN(trasdate) AS min_dt, SUM(revenue) AS TotalRevenue,
DATEDIFF(month, trasdate, GETDATE()) AS mnum
FROM revenue
GROUP BY id, DATEDIFF(month, trasdate, GETDATE())
)
SELECT id, MONTH(min_dt) AS mon, YEAR(min_dt) AS yr, TotalRevenue
, (SELECT AVG(B.TotalRevenue)
FROM CTE B
WHERE B.mnum BETWEEN A.mnum+1 AND A.mnum+3
AND A.id = B.id
) AS revenue_3mon
FROM CTE A
ORDER BY id, mnum DESC;
Both queries allow for retrieving the minimum and maximum date for each period (including month and year).
If you instead wanted what you originally posted under The result should show something like this (just grouping by previous 3-months intervals), you just would have to group your original revenue table by id and (DATEDIFF(month, trasdate, GETDATE())-1)/3 (filtering WHERE DATEDIFF(month, trasdate, GETDATE()) > 0). If so, this kind of grouping and aggregation could, of course, be done also by the Report Server.
I think this should do what you want:
select r.*,
avg(r.mon_revenue) over (partition by r.id
order by r.mon_min
rows between 3 preceding and 1 preceding row
) as revenue_3mon
-- using 3 preceding and 1 preceding row you exclude the current row
from (select r.id, month(r.trasdate) as mon,
min(r.trasdate) as mon_min,
sum(r.revenue) as mon_revenue
from revenue r
group by r.id, year(r.trasdate), month(r.trasdate)
) 4
order by r.id, r.mon, r.mon_min;
Notes:
I fixed the code so it recognizes years as well as dates.
The expression [i.mon_revenue] is not a valid column reference (in your case). You have no column with the name "i.mon_revenue" (with the . in the name).
I changed the column alias to r to match the table.
I added a date column for each month to make it easier to express the ordering.
The outer group by is not necessary.
There are several syntax errors in your code. This should give you what you need. The inner query is the important bit but hopefully this will be enough to get you on your way.
I switch our the temp table for variable and changed the revenue column to not be INT as you have decimal values in there but other than that your original sample table is unchanged
DECLARE #revenue table (id varchar(2), trasdate date, revenue float)
insert into #revenue(id, trasdate, revenue)
values ('aa', '2018/09/01', 1234.5),
('aa' , '2018/08/04', 450),
('aa', '2018/07/03',500),
('aa', '2018/06/04',600),
('ab', '2018/09/01', 1234.5),
('ab' , '2018/08/04', 450),
('ab', '2018/07/03',500),
('ab', '2018/06/04',600),
('ab', '2018/05/03', 200),
('ab', '2018/04/02', 150),
('ab', '2018/03/01', 350),
('ab', '2018/02/05', 700),
('aa', '2018/01/07', 400)
SELECT
*
FROM
(
SELECT
*
, MONTH(trasdate) as MonthNumber
, AVG(revenue) OVER (PARTITION BY id
ORDER BY
id
, MONTH(trasdate) ROWS BETWEEN 3 PRECEDING AND 1 PRECEDING) as ThreeMonthAvg
FROM #revenue
) a
WHERE MONTH(GETDATE()) - MonthNumber IN (0, 3, 6, 9)
This gives the following results
aa 2018-06-04 600 6 400
aa 2018-09-01 1234.5 9 516.666666666667
ab 2018-03-01 350 3 700
ab 2018-06-04 600 6 233.333333333333
ab 2018-09-01 1234.5 9 516.666666666667
I'm doing some cohort analysis and want to see for a group of customers in November, how many transact weekly, fortnightly, and monthly; and for how long
I have this for the week and month (weekly example):
WITH weekly_users AS (
SELECT user_fk
, DATE_TRUNC('week',created_at) AS week
, (DATE_PART('year', created_at) - 2016) * 52 + DATE_PART('week', created_at) - 45 AS weeks_between
FROM transactions
WHERE created_at >= '2016-11-01' AND created_at < '2017-12-01'
GROUP BY user_fk, week, weeks_between
),
t2 AS (
SELECT weekly_users.*
, COUNT(*) OVER (PARTITION BY user_fk
ORDER BY week ROWS BETWEEN UNBOUNDED PRECEDING
AND 1 PRECEDING) AS prev_rec_cnt
FROM weekly_users
)
SELECT week
, COUNT(*)
FROM t2
WHERE weeks_between = prev_rec_cnt
GROUP BY week
ORDER BY week;
But weekly is too little of an interval, and monthly too much. So I want fortnight. Has anyone done this before? From Googling it seems like a challenge
Thanks in advance
Just worked it out, this is how you'd do it:
WITH fortnightly_users AS (
SELECT user_fk
, EXTRACT(YEAR FROM created_at) * 100 + CEIL(EXTRACT(WEEK FROM created_at)/2) AS fortnight
, (EXTRACT(YEAR FROM created_at) - 2016) * 26 + CEIL(EXTRACT(WEEK FROM created_at)/2) - 23 AS fortnights_between
FROM transactions
WHERE created_at >= '2016-11-01' AND created_at < '2017-12-01'
GROUP BY user_fk, fortnight, fortnights_between
),
t2 AS (
SELECT fortnightly_users.*
, COUNT(*) OVER (PARTITION BY user_fk
ORDER BY fortnight ROWS BETWEEN UNBOUNDED PRECEDING
AND 1 PRECEDING) AS prev_rec_cnt
FROM fortnightly_users
)
SELECT fortnight
, COUNT(*)
FROM t2
WHERE fortnights_between = prev_rec_cnt
GROUP BY fortnight
ORDER BY fortnight;
So you get the week number, then divide by 2. Rounding up to avoid fractional numbers for fortnights
Can you show how can this be done in t-sql?
sample records
accountnumber trandate
-------------------------
1000 02-11-2010
1000 02-12-2010
1000 02-13-2010
2000 02-10-2010
2000 02-15-2010
How to compute the # of days between each transactions for each accountnumber?
like this
accountnumber trandate # of days
----------------------------------------
1000 02-11-2010 0
1000 02-12-2010 1
1000 02-13-2010 1
2000 02-10-2010 0
2000 02-15-2010 5
Thanks a lot!
SELECT accountnumber,
trandate,
Datediff(DAY, a.trandate, (SELECT TOP 1 trandate
FROM mytable b
WHERE b.trandate > a.trandate
ORDER BY trandate))
FROM mytable a
ORDER BY trandate
you can use between and
select * from table1 where trandate between 'date1' and 'date2'
Hope this helps.
Select A.AccountNo, A.TranDate, B.TranDate as PreviousTranDate, A.TranDate - B.Trandate as NoOfDays
from
(Select AccountNo, TranDate, Row_Number() as RNO over (Partition by AccountNo order by TranDate)) as A,
(Select AccountNo, TranDate, Row_Number() as RNO over (Partition by AccountNo order by TranDate)) as B
Where A.AccountNo = B.AccountNo and A.RNO -1 = B.RNO
You can also use a CTE expression to increase preformance.
Please help me undestand how order by influences to over clause. I have read msdn and one book and still misunderstood.
Let's say we have such query:
SELECT Count(OrderID) over(Partition By Year(OrderDate))
,*
FROM [Northwind].[dbo].[Orders]
ORDER BY OrderDate
The result is that each raw has the column with the value how many entries in the table have the same year.
alt text http://img-fotki.yandex.ru/get/3912/svin80.2/0_3b871_3bb591da_XL
But what's happened when i try this query?:
SELECT ROW_NUMBER() over(Partition By Year(OrderDate)
order by OrderDate) as RowN
,*
FROM [Northwind].[dbo].[Orders]
ORDER BY RowN
alt text http://img-fotki.yandex.ru/get/3908/svin80.2/0_3b872_c9352fb1_XL
Now I see the only thing that each RowN has 3 different years for each value (1996, 1997, 1998). I expected that RowN will be the same value for all 1996 year dates. Please explain me what happens and why.
In this case:
SELECT ROW_NUMBER() over(Partition By Year(OrderDate)
order by OrderDate) as RowN,*
FROM [Northwind].[dbo].[Orders]
order by RowN
What you're seeing it it's giving you a row number that is partitioned by year, meaning that each year has it's own climbing row number. To make this a bit cleaerer in the results:
SELECT ROW_NUMBER() over(Partition By Year(OrderDate)
order by OrderDate) as RowN,*
FROM [Northwind].[dbo].[Orders]
order by RowN, Year(OrderDate)
This means that each year, say 1997, will have orders 1 through n ordered by the date that year...like this was the 1st order of 1997, 2nd order of 1997, etc.
The results will make far more sense if you do this:
SELECT
Year(OrderDate),
ROW_NUMBER() over(Partition By Year(OrderDate)order by OrderDate) as RowN,
*
FROM [Northwind].[dbo].[Orders]
ORDER BY Year(OrderDate), RowN
Now you can see that each year has increasing row numbers starting from 1, ordered by order date:
Year RowN Order Date
1997 1 10400 1997-01-01 00:00:00
1997 2 10401 1997-01-01 00:00:00
1997 3 10402 1997-01-02 00:00:00
...
1998 1 10808 1998-01-01 00:00:00
1998 2 10809 1998-01-01 00:00:00
1998 3 10810 1998-01-01 00:00:00
...