I know this sounds really simple but I just cannot seem to get my head around it.
I have a temporary table that holds for example, Handler, MonthName, MonthNumber and MTD, which is a total for that month. What I need to do with that data is then create a running total for each Handler, from April to March. Now, here is the bit I am struggling with. Not all Handlers will have data for all months.
For example.
Handler MonthName MonthNo MTD
Julian Slaughter April 1 10000
Julian Slaughter June 3 12000
Julian Slaughter July 4 10000
Julian Slaughter September 6 12000
Bob Monkhouse April 1 5000
Bob Monkhouse July 4 5000
So I want the results to look like this
Julian Slaughter April 1 10000
Julian Slaughter May 2 10000
Julian Slaughter June 3 22000
Julian Slaughter July 4 32000
Julian Slaughter August 5 32000
Julian Slaughter September 6 44000
...and so on until March
Bob Monkhouse April 1 5000
Bob Monkhouse May 2 5000
Bob Monkhouse June 3 5000
Bob Monkhouse July 4 10000
...and so on until March
I have tried LEFT JOIN onto a table of the Month Names\Numbers and I have had an attempt at
OVER(PARTITION ..... ORDER BY ..... RANGE\ROWS)
but can't get the missing months.
Thanks in advance, sorry for the poor formatting, not sure how to do tables on here.
EDIT - Here is my LEFT JOIN attempt
SELECT
Months.MonthNo,
Department,
Executive,
#8.MonthNo,
MTD = SUM([TY MTD Prem]) OVER (PARTITION BY Department, Executive, [Exec Code] ORDER BY #8.MonthNo RANGE UNBOUNDED PRECEDING)
FROM Months
LEFT JOIN #8 ON Months.MonthNo = #8.MonthNo
For one Executive, I only get 4 rows, not the 12 I need. Can't show you the results for Data Protection purposes.
DECLARE #start_date date, #end_date date
SELECT #start_date='2012-04-01',#end_date='2013-03-31'
;WITH xo AS
(
SELECT #start_date AS cte_start_date
UNION ALL
SELECT DATEADD(MONTH, 1, cte_start_date)
FROM xo
WHERE DATEADD(MONTH, 1, cte_start_date) <= #end_date
), x as (
select *,row_number() over (order by cte_start_date) monthno
from xo
)
, y as (
select distinct handler from test
)
SELECT y.handler, datename(mm,x.cte_start_date), x.monthno
,(select sum(mtd) from test a where a.handler=y.handler and a.monthno<=x.monthno) mtd
FROM y
cross join x
order by 1,3
see example on SQLFiddle http://sqlfiddle.com/#!3/7d483/15
Sorry for the delay. The proposed solution worked a treat. I had to use the same code several times in various other parts of my giant query but it worked great.
Related
For each of the 12 months, I'm looking to create a field that sums the sales dollars at the account level for the most recent month and the 2nd most recent month based on the current date.
For example, given that today's date is 2022-10-28, 'MostRecentNovember' would sum up sales from November 2021. '2ndMostRecentNovember' would sum up sales from November 2020. Once the current date moves into November 2022, this query would adjust to pull MostRecentNovember sales from 2022 and 2ndMostRecentNovember sales from 2021.
Conversely, given that today's date is 2022-10-28 'MostRecentJune' would sum up sales from June 2022 and '2ndMostRecentJune' would sum up sales from June 2021.
In the end state, each account would have 24 fields: January - December for Most Recent and January - December for 2nd most recent
Below is my attempt at this code, this gets partially there, but it's not getting what I need. I've also tried with a CTE, but that didn't seem to do it either
SELECT NovemberMostRecent_Value =
sum(case when datepart(year,tran_date) = datepart(year, getdate())
AND DATEPART(month, tran_date) = 11 then value else 0 end)
NovemberSecondMostRecent_Value =
sum(case when datepart(year,tran_date) = datepart(year, getdate())-1
AND DATEPART(month, tran_date) = 11 then value else 0 end)
Here's a snippet of the source data table
account_no
tran_date
value
123
2021-11-22
500
123
2021-11-01
500
123
2020-11-20
1500
123
2022-06-03
5000
123
2021-06-04
2000
456
2020-11-03
525
456
2021-11-04
125
A table of desired Results
account_no
NovemberMostRecent
November2ndMostRecent
June MostRecent
June2ndMostRecent
123
1000
1500
5000
2000
456
125
525
0
0
We use dense_rank() by year desc (partitioned by month) and pivot.
select *
from
(
select account_no
,value
,concat(datename(month, tran_date), '_', dense_rank() over(partition by month(tran_date) order by year(tran_date) desc)) as month_rnk
from t
) t
pivot (sum(value) for month_rnk in(June_1, June_2, November_1, November_2)) p
account_no
June_1
June_2
November_1
November_2
123
5000
2000
1000
1500
456
null
null
125
525
Fiddle
I have a table like this
date amount
2020-02-01 5
2020-02-02 2
2020-02-03 10
2020-02-04 2
2020-02-06 3
2020-02-07 1
And I need sum() every 3 days as below:
date amount sum
2020-02-01 5 5
2020-02-02 2 7
2020-02-03 10 17
2020-02-04 2 2
2020-02-06 3 5
2020-02-07 1 1
...
So when a difference between days is 3, the summation should start over. Some days may not be in the table.
I tried to do this with window function like sum(amount) over (order by date) but I have no idea how to set a fixed number of days and get the date difference in cumulative sum like this. Is it possible in any SQL?
In MS Sql Server
select t.[date], t.Amount, sum(t.Amount) over(partition by datediff(d, '2020-02-01', t.[date])/3 order by t.[date]) cum
from tbl t
'2020-02-01' is a starting date you want.
Disclaimer
The following solution was written based on a Preview version of SQL Server 2022, and thus may not reflect the final release.
For a bit of fun, if you had access to SQL Server 2022 (which went into preview yesterday) you could use DATE_BUCKET to "round" the date in the PARTITION BY to 3 days, using the minimum date as the starting date.
DECLARE #StartDate date,
#EndDate date;
SELECT #StartDate = MIN(date),
#EndDate = MAX(date)
FROM dbo.YourTable;
SELECT date,
SUM(amount) OVER (PARTITION BY DATE_BUCKET(DAY,3,date,#StartDate) ORDER BY date) AS Amount
FROM dbo.YourTable
WHERE date >= #StartDate
AND date <= #EndDate; --Incase this would be parametrised
Image of results as expected, as Fiddles of 2022 don't exist:
I have the following sql Code (where clause just to limit rows currently)
select
month,
monthname,
year,
count(distinct case when a.dim_service_type_id_desc like '%Direct Payment%' then a.DIM_PERSON_ID else null end) as No_dp,
count(distinct a.DIM_PERSON_ID) as no_ppl
from
SERVICE_PROVISIONS a
inner join date_tbl d on CONVERT(VARCHAR(35),a.start_dttm,112) = d.dim_date_id
where
a.dim_person_id >0
and year = 2018
group by
month,
monthname,
year
my output is this
month monthname year No_dp no_ppl
1 January 2018 142 1604
2 February 2018 111 1526
3 March 2018 133 1636
4 April 2018 1107 3829
5 May 2018 140 1575
6 June 2018 131 1389
7 July 2018 200 893
8 August 2018 2 73
9 September 2018 1 32
10 October 2018 2 21
11 November 2018 2 21
12 December 2018 2 19
So my question is - the customer wants to see how many services were open (using start date and end date) during the previous 12 months (not how many were started, but how many were current and not ended). This is fine when using the current month, however they want to show this also for the previous 12 months as a rolling dynamic figure.
So for example this month in July they want to see how many services were open during the last 12 months. Last month June, they want to see how many services were open during the 12 months previous to June and so on for the previous 12 months.
The table needs to have the month name for the last 12 months and in a column show the number of services that were open in the previous 12 months next to that month.
I hope that makes sense, sorry if it doesn't, feel free to ask questions and I will try to clarify.
The output needs to look something like the current output table, but it is currently only showing how many services were started within that month, which isn't what we want.
The date table is a reference table which has different date formats etc. It can be used or added to if needed.
I've had to make several assumptions about your data. Hopefully the query I'll show in a minute will be easy for you to adjust if any of these are wrong:
I am guessing by its name that start_dttm is a datetime or datetime2 column.
I assume there is a corresponding column called end_dttm that gives the end date/time of a service, and that a null in this column would indicate that a service has not yet ended.
My best guess as to what it means for a service to be "open" in a given month is that it began sometime either within or prior to that month, and has not ended by the time that month is over.
I assume from your original query that multiple services having the same dim_person_id do not represent distinct services.
Since I don't know what's in your date_tbl, I'll show an example that doesn't require it. Consider the following query:
select
BeginDate = dateadd(month, -1, dateadd(day, 1, eomonth(getdate(), -Offset.X))),
EndDate = dateadd(day, 1, eomonth(getdate(), -Offset.X))
from
(values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9),(10),(11)) Offset(X)
This will give you 12 records, representing the current month and each of the 11 preceding months. Note that my EndDate here is not actually the last day of the month, but the first day of the following month. I've done this because of assumption 1 above; since your service dates may have time components, I'll determine whether they fall in a given month by checking if their dates are strictly earlier than the start of the following month. Here's what that query gives me:
BeginDate EndDate
2018-07-01 2018-08-01
2018-06-01 2018-07-01
2018-05-01 2018-06-01
2018-04-01 2018-05-01
2018-03-01 2018-04-01
2018-02-01 2018-03-01
2018-01-01 2018-02-01
2017-12-01 2018-01-01
2017-11-01 2017-12-01
2017-10-01 2017-11-01
2017-09-01 2017-10-01
2017-08-01 2017-09-01
Now I'll join the above result set to your SERVICE_PROVISIONS data, looking for records in each month that have dim_person_id > 0 (from your original query) and which satisfy assumption 3 above.
-- Some sample data (assumptions 1 & 2)
declare #SERVICE_PROVISIONS table (dim_person_id bigint, start_dttm datetime, end_dttm datetime);
insert #SERVICE_PROVISIONS values
(1, '20180101', '20180315'),
(1, '20180101', '20180315'),
(2, '20171215', '20180520');
-- The CTE defines the months we'll report on, as described earlier.
with MonthsCTE as
(
select
BeginDate = dateadd(month, -1, dateadd(day, 1, eomonth(getdate(), -Offset.X))),
EndDate = dateadd(day, 1, eomonth(getdate(), -Offset.X))
from
(values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9),(10),(11)) Offset(X)
)
-- This query matches the months from the CTE against the applicable services.
select
[Month] = datepart(month, M.BeginDate),
[MonthName] = datename(month, M.BeginDate),
[Year] = datepart(year, M.BeginDate),
ServicesOpen = count(distinct S.dim_person_id) -- Assumption 4
from
MonthsCTE M
left join #SERVICE_PROVISIONS S on
S.dim_person_id > 0 and
S.start_dttm < M.EndDate and -- Assumption 3
(
S.end_dttm >= M.EndDate or
S.end_dttm is null -- Assumption 2
)
group by
M.BeginDate,
M.EndDate
order by
M.BeginDate;
Note that I moved the dim_person_id > 0 from the WHERE clause to the JOIN so that each of the 12 months will still appear in the result set even if there were no services open during that time. Results:
Month MonthName Year ServicesOpen
8 August 2017 0
9 September 2017 0
10 October 2017 0
11 November 2017 0
12 December 2017 1
1 January 2018 2
2 February 2018 2
3 March 2018 1
4 April 2018 1
5 May 2018 0
6 June 2018 0
7 July 2018 0
something a bit like this - if you can write a query to get the value you want for a row in your ootput, then use cross apply to link to that query. Counting records that have an open record before the month, but no close record before the month seems feasible
SELECT IQ. *, OA.SERVICE_PROVISIONS FROM (select
month,
monthname,
year,
a.dim_person_id dim_person_id,
count(distinct case when a.dim_service_type_id_desc like '%Direct Payment%' then a.DIM_PERSON_ID else null end) as No_dp,
count(distinct a.DIM_PERSON_ID) as no_ppl
from
SERVICE_PROVISIONS a
inner join date_tbl d on CONVERT(VARCHAR(35),a.start_dttm,112) = d.dim_date_id
where
a.dim_person_id >0
and year = 2018
group by
month,
monthname,
year) IQ
CROSS APPLY
(SELECT count(0) OpenThings FROM SERVICE_PROVISIONS SP1 WHERE
(sp1.startdate < DATEFROMPARTS(IQ.year,iq.month,1)
AND
sp1.enddate is null or sp1.enddate > DATEFROMPARTS(IQ.year,iq.month,1)) and sp1.dim_person_id = iq.dim_person_id
) AS OA
I have some data that I am trying to get some counts on. There are dates for when the record was entered and when it was closed, if it has been closed yet. I want to be able to get a count of how many records were still open from the previous month as of the first of the month. Here is an example. First table is the data, second table is the results I am looking for. In the second table, ignore the parenthesis, they are just the IDs of the records that make up that count.
Position DateEntered DateClosed
1 12/15/2017 12/20/2017
11 12/20/2017 1/7/2018
2 1/23/2018 2/3/2018
3 1/24/2018
4 2/15/2018
5 2/20/2018 5/16/2018
6 3/3/2018 3/15/2018
7 3/23/2018 4/12/2018
8 4/11/2018 5/10/2018
9 4/12/2018 4/25/2018
10 5/4/2018
Year Month Carried Over
2018 January 1 (11)
2018 February 2 (2,3)
2018 March 3 (3,4,5)
2018 April 4 (3,4,5,7)
2018 May 4 (3,4,5,8)
2018 June 3 (3,4,10)
2018 July 3 (3,4,10)
2018 August 3 (3,4,10)
Is this possible, and if so, how? Been racking my brain on this one for a few hours.
For each month, you want the number of rows that start before that month and end after. I'm thinking:
with dates as (
select cast('2018-01-01' as date) as dte
union all
select dateadd(month, 1, dte)
from dates
where dte < '2018-08-01'
)
select d.dte,
(select count(*)
from t
where t.dateentered < d.dte and
(t.dateclosed > d.dte or t.dateClosed is null)
) as carriedover
from dates d;
Note that this puts the date in a single column, rather than splitting the year and month into separate columns. That is easily arranged, but I prefer to keep date components together.
This question already has answers here:
Closed 11 years ago.
Possible Duplicate:
Running total by grouped records in table
I am trying to put together an SQL statement that returns the SUM of a value by month, but on a year to date basis. In other words, for the month of March, I am looking to get the sum of a value for the months of January, February, and March.
I can easily do a group by to get a total for each month by itself, and potentially calculate the year to date value I need in my application from this data by looping through the results set. However, I was hoping to have some of this work handled with my SQL statement.
Has anyone ever tackled this type of problem with an SQL statement, and if so, what is the trick that I am missing?
My current sql statement for monthly data is similar to the following:
Select month, year, sum(value) from mytable group by month, year
If I include a where clause on the month, and only group by the year, I can get the result for a single month that I am looking for:
select year, sum(value) from mytable where month <= selectedMonth group by year
However, this requires me to have a particular month pre-selected or to utilize 12 different SQL statements to generate one clean result set.
Any guidance that can be provided would be greatly appreciated!
Update: The data is stored on an IBM iSeries.
declare #Q as table
(
mmonth INT,
value int
)
insert into #Q
values
(1,10),
(1,12),
(2,45),
(3,23)
select sum(January) as UpToJanuary,
sum(February)as UpToFebruary,
sum(March) as UpToMarch from (
select
case when mmonth<=1 then sum(value) end as [January] ,
case when mmonth<=2 then sum(value) end as [February],
case when mmonth<=3 then sum(value) end as [March]
from #Q
group by mmonth
) t
Produces:
UpToJanuary UpToFebruary UpToMarch
22 67 90
You get the idea, right?
NOTE: This could be done easier with PIVOT tables but I don't know if you are using SQL Server or not.
As far as I know DB2 does support windowing functions although I don't know if this is also supported on the iSeries version.
If windowing functions are supported (I believe IBM calls them OLAP functions) then the following should return what you want (provided I understood your question correctly)
select month,
year,
value,
sum(value) over (partition by year order by month asc) as sum_to_date
from mytable
order by year, month
create table mon
(
[y] int not null,
[m] int not null,
[value] int not null,
primary key (y,m))
select a.y, a.m, a.value, sum(b.value)
from mon a, mon b
where a.y = b.y and a.m >= b.m
group by a.y, a.m, a.value
2011 1 120 120
2011 2 130 250
2011 3 500 750
2011 4 10 760
2011 5 140 900
2011 6 100 1000
2011 7 110 1110
2011 8 90 1200
2011 9 70 1270
2011 10 150 1420
2011 11 170 1590
2011 12 600 2190
You should try to join the table to itself by month-behind-a-month condition and generate a synthetic month-group code to group by as follows:
select
sum(value),
year,
up_to_month
from (
select a.value,
a.year,
b.month as up_to_month
from table as a join table as b on a.year = b.year and b.month => a.month
)
group by up_to_month, year
gives that:
db2 => select * from my.rep
VALUE YEAR MONTH
----------- ----------- -----------
100 2011 1
200 2011 2
300 2011 3
400 2011 4
db2 -t -f rep.sql
1 YEAR UP_TO_MONTH
----------- ----------- -----------
100 2011 1
300 2011 2
600 2011 3
1000 2011 4