I have the following table structure and data in the database table:
ID
Year
StartWeek
EndWeek
AllocationPercent
5
2021
34
35
50
6
2021
1
3
5
I need to split the multi-week rows into multiple single-week rows, and the end result should be:
ID
Year
StartWeek
EndWeek
AllocationPercent
5
2021
34
34
50
5
2021
35
35
50
6
2021
1
1
5
6
2021
2
2
5
6
2021
3
3
5
Any help with this would be highly appreciated! There are a lot of threads regarding splitting date ranges into multiple rows but I cannot seem to modify those to fit my use case. I know that most likely I need a tally table with the week numbers (which I already have).
Another way to think about this is, because we know the max weeknumber is 53, to generate the set of all possible week numbers, then outer join to that set each week in any source row that is within that range.
;WITH n(n) AS
(
SELECT 0 UNION ALL SELECT n+1 FROM n WHERE n <= 53
)
SELECT w.ID,
w.Year,
StartWeek = n.n,
EndWeek = n.n,
w.AllocationPercent
FROM n
INNER JOIN dbo.TableName AS w
ON n.n BETWEEN w.StartWeek AND w.EndWeek
ORDER BY w.ID, w.Year, n.n;
Results:
ID
Year
StartWeek
EndWeek
AllocationPercent
5
2021
34
34
50
5
2021
35
35
50
6
2021
1
1
5
6
2021
2
2
5
6
2021
3
3
5
Example db<>fiddle
You can use recursive cte :
;with cte as (
select t.id, t.year, t.startweek, t.endweek, t.AllocationPercent
from t
union all
select id, year, startweek + 1, endweek, AllocationPercent
from cte c
where startweek < endweek
)
select id, year, startweek, startweek as endweek, AllocationPercent
from cte
order by id, startweek, endweek;
db fiddle
Related
I have a table with 3 columns (Year, Month, Value) like this in Sql Server :
Year
Month
Value
ValueOfLastTwelveMonths
2021
1
30
30
2021
2
24
54 (30 + 24)
2021
5
26
80 (54+26)
2021
11
12
92 (80+12)
2022
1
25
87 (SUM of values from 1 2022 TO 2 2021)
2022
2
40
103 (SUM of values from 2 2022 TO 3 2021)
2022
4
20
123 (SUM of values from 4 2022 TO 5 2021)
I need a SQL request to calculate ValueOfLastTwelveMonths.
SELECT Year,
Month,
Value,
SUM (Value) OVER (PARTITION BY Year, Month)
FROM MyTable
This is much easier if you have a row for each month and year, and then (if needed) you can filter the NULL rows out. The reason it's easier is because then you know how many rows you need to look back at: 11.
If you make a dataset of the years and months, you can then LEFT JOIN to your data, aggregate, and then finally filter the data out:
SELECT *
INTO dbo.YourTable
FROM (VALUES(2021,1,30),
(2021,2,24),
(2021,5,26),
(2021,11,12),
(2022,1,25),
(2022,2,40),
(2022,4,20))V(Year,Month,Value);
GO
WITH YearMonth AS(
SELECT YT.Year,
V.Month
FROM (SELECT DISTINCT Year
FROM dbo.YourTable) YT
CROSS APPLY (VALUES(1),(2),(3),(4),(5),(6),(7),(8),(9),(10),(11),(12))V(Month)),
RunningTotal AS(
SELECT YM.Year,
YM.Month,
YT.Value,
SUM(YT.Value) OVER (ORDER BY YM.Year, YM.Month
ROWS BETWEEN 11 PRECEDING AND CURRENT ROW) AS Last12Months
FROM YearMonth YM
LEFT JOIN dbo.YourTable YT ON YM.Year = YT.Year
AND YM.Month = YT.Month)
SELECT Year,
Month,
Value,
Last12Months
FROM RunningTotal
WHERE Value IS NOT NULL;
GO
DROP TABLE dbo.YourTable;
I have a table of records like this:
Item
From
To
A
2018-01-03
2018-03-16
B
2021-05-25
2021-11-10
The output of select should look like:
Item
Month
Year
A
01
2018
A
02
2018
A
03
2018
B
05
2021
B
06
2021
B
07
2021
B
08
2021
Also the range should not exceed the current month. In example above we are asuming current day is 2021-08-01.
I am trying to do something similar to THIS with CONNECT BY LEVEL but as soon as I also select my table next to dual and try to order the records the selection never completes. I also have to join few other tables to the selection but I don't think that would make a difference.
I would very much appreciate your help.
Row generator it is, but not as you did it; most probably you're missing lines #11 - 16 in my query (or their alternative).
SQL> with test (item, date_from, date_to) as
2 -- sample data
3 (select 'A', date '2018-01-03', date '2018-03-16' from dual union all
4 select 'B', date '2021-05-25', date '2021-11-10' from dual
5 )
6 -- query that returns desired result
7 select item,
8 extract(month from (add_months(date_from, column_value - 1))) month,
9 extract(year from (add_months(date_from, column_value - 1))) year
10 from test cross join
11 table(cast(multiset
12 (select level
13 from dual
14 connect by level <=
15 months_between(trunc(least(sysdate, date_to), 'mm'), trunc(date_from, 'mm')) + 1
16 ) as sys.odcinumberlist))
17 order by item, year, month;
ITEM MONTH YEAR
----- ---------- ----------
A 1 2018
A 2 2018
A 3 2018
B 5 2021
B 6 2021
B 7 2021
B 8 2021
7 rows selected.
SQL>
Recursive CTEs are the standard SQL approach to this type of problem. In Oracle, this looks like:
with cte(item, fromd, tod) as (
select item, fromd, tod
from t
union all
select item, add_months(fromd, 1), tod
from cte
where add_months(fromd, 1) < last_day(tod)
)
select item, extract(year from fromd) as year, extract(month from fromd) as month
from cte
order by item, fromd;
Here is a db<>fiddle.
I have a simple data
Date Count by english count by chinese
08-Mar-19 12 54
09-Mar-19 15 66
10-Mar-19 45 32
11-Mar-19 21 70
12-Mar-19 57 64
29-Mar-19 43 53
30-Mar-19 67 21
I want to group this data by week and the sum should be cumulative.The date starts from 8 march so the week should be calculated that way only. So the result should be
count by english count by chinese
08-MAR-19-14-MAR-19 150 286
15-MAR-19-22-MAR-19 150 286 (no data so same as above)
23-MAR-19-30-MAR-19 260 360
Tried using cumulative and sum but not able to achieve it
You can generate your week ranges, then use an outer join to see which data fits in each week, and use an analytic sum to get the result you want;
with week_ranges (date_from, date_to) as (
select min_date + ((level - 1) * 7), min_date + (level * 7)
from (
select min(some_date) as min_date, ceil((max(some_date) - min(some_date)) / 7) as weeks
from your_table
)
connect by level <= weeks
)
select distinct wr.date_from, wr.date_to - 1 as date_to,
sum(count_english) over (order by wr.date_from) as count_english,
sum(count_chinese) over (order by wr.date_from) as count_chinese
from week_ranges wr
left join your_table yt
on yt.some_date >= wr.date_from
and yt.some_date < wr.date_to
order by date_from;
which with your sample data gets:
DATE_FROM DATE_TO COUNT_ENGLISH COUNT_CHINESE
---------- ---------- ------------- -------------
2019-03-08 2019-03-14 150 286
2019-03-15 2019-03-21 150 286
2019-03-22 2019-03-28 150 286
2019-03-29 2019-04-04 260 360
Note this is splitting it up into four 7-days weeks, rather than one of 7 days and two of 8 days...
db<>fiddle
Here's one option; note that "my weeks" are different than yours because - your data is somewhat inconsistent as they vary from 6 to 7 days. That's also why the final result is different, but the general idea should be OK.
SQL> alter session set nls_date_format = 'dd.mm.yyyy';
Session altered.
SQL> with test (datum, cbe) as
2 -- sample data
3 (select date '2019-03-08', 12 from dual union all
4 select date '2019-03-09', 15 from dual union all
5 select date '2019-03-10', 45 from dual union all
6 select date '2019-03-11', 21 from dual union all
7 select date '2019-03-12', 57 from dual union all
8 select date '2019-03-29', 43 from dual union all
9 select date '2019-03-30', 67 from dual
10 ),
11 span as
12 -- min and max date value, so that we could create a "calendar"
13 (select min(datum) mindat,
14 max(datum) maxdat
15 from test
16 ),
17 periods as
18 -- "calendar" whose periods are weeks
19 (select s.mindat + (level - 1) * 7 datum_from,
20 (s.mindat + level * 7) - 1 datum_to
21 from span s
22 connect by level <= (s.maxdat - s.mindat) / 7 + 1
23 )
24 -- running sum per weeks
25 select distinct
26 p.datum_from,
27 p.datum_to,
28 sum(t.cbe) over (order by p.datum_from) sum_cbe
29 from test t full outer join periods p on t.datum between p.datum_from and p.datum_to
30 order by p.datum_from;
DATUM_FROM DATUM_TO SUM_CBE
---------- ---------- ----------
08.03.2019 14.03.2019 150
15.03.2019 21.03.2019 150
22.03.2019 28.03.2019 150
29.03.2019 04.04.2019 260
SQL>
My table structure in SQL Server looks as below.
id startdate enddate value
---------------------------------------
1 2019-02-06 2019-02-07 11
1 2019-01-22 2019-02-05 10
1 2019-01-15 2019-01-21 14
1 2018-12-13 2018-01-14 15
1 2018-12-09 2018-12-12 14
1 2018-08-13 2018-12-08 17
1 2018-07-19 2018-08-12 19
1 2018-06-13 2018-07-18 20
Now my query needs to display value from highest start date for that month. Which is fine and I know what needs to be done but Not start just highest date value for that month, if no value is there for that start date, we carry forward value from last month. So basically if you notice on above data, after December 2018 values, there are no values for November, October, September etc but I want to return MM/YYYY values for that month in result but value for those months should be what we found on earlier month which is August values which in this example is 17. Please note that enddate will always be as of one day before new start date begins. Probably that can be used for back filling and carry forwarding missing month values?
So my result should look like below.
id date value
----------------------------
1 2019-02 11
1 2019-01 10
1 2018-12 15
1 2018-11 17
1 2018-10 17
1 2018-09 17
1 2018-08 17
1 2018-07 19
1 2018-06 20
Do you think this can be done without using cursor here?
Alexander Volok's answer is solid, so I won't go into too much extra code. But I thought I'd explain the reasoning. In essence, what you need to do is create a skeleton date table containing all the dates and primary keys you want returned. I'm guessing you have more than one id value in your real data, so probably something like this (whether you choose to persist it or not is up to you)
create table #skelly
(
id int,
_year int,
_month int
primary key (id, _year, _month)
)
You can get much more precise if you need to be, by only including dates which fall between the min and max StartDate per id, but that's an exercise I leave up to you.
From there, it's then just a matter of filling in the values you care about against that skeleton table. You can do this in a number of ways; by joining, cross applying or a correlated subquery (as Alexander Volok used).
DECLARE #start DATE, #end DATE;
SELECT #start = '20180601', #end = GETDATE();
;WITH Months AS
(
SELECT EOMONTH(DATEADD(month, n-1, #start)) AS DateValue FROM (
SELECT TOP (DATEDIFF(MONTH, #start, #end) + 1)
n = ROW_NUMBER() OVER (ORDER BY [object_id])
FROM sys.all_objects
) D
)
, InputData AS
(
SELECT 1 AS id, '2019-02-06' startdate, '2019-02-07' as enddate, 11 AS [value] UNION ALL
SELECT 1, '2019-01-22', '2019-01-25', 10 UNION ALL
SELECT 1, '2019-01-15', '2019-01-17', 14 UNION ALL
SELECT 1, '2018-12-13', '2018-12-19', 15 UNION ALL
SELECT 1, '2018-12-09', '2018-12-10', 14 UNION ALL
SELECT 1, '2018-08-13', '2018-12-08', 17 UNION ALL
SELECT 1, '2018-07-19', '2018-07-25', 19 UNION ALL
SELECT 1, '2018-06-13', '2018-07-18', 20
)
SELECT FORMAT(m.DateValue, 'yyyy-MM') AS [Month]
, (SELECT TOP 1 I.value FROM InputData I WHERE I.startdate < M.DateValue ORDER BY I.startdate DESC ) [Value]
FROM months m
ORDER BY M.DateValue DESC
Results to:
Month Value
2019-02 11
2019-01 10
2018-12 15
2018-11 17
2018-10 17
2018-09 17
2018-08 17
2018-07 19
2018-06 20
Suppose I have 2 years of data. From January 2010 to Dec 2011.
I want to classify each of the months as periods. So January 2010 will be my 1, February 2010 my 2, and so on until December 2011 my 24 period.
I know I could do it something like:
select
year,mn,
case when year=2010 and mn=01 then 1
else when year=2010 and mn=02 then 2
else when year=2010 and mn=03 then 3
//and so on until // else when year=2011 and mn=12 then 24 end
from mytable;
The result would be something like:
year mn period
2010 1 1
2010 2 2
2010 3 3
2010 4 4
2010 5 5
2010 6 6
2010 7 7
2010 8 8
2010 9 9
2010 10 10
2010 11 11
2010 12 12
2011 1 13
2011 2 14
2011 3 15
2011 4 16
2011 5 17
2011 6 18
2011 7 19
2011 8 20
2011 9 21
2011 10 22
2011 11 23
2011 12 24
I want to avoid this kind of long and not wise method.
select
year, mn,
row_number() over (order by year, mn) as period
from t
No need for fancy windowing functions. Just do it the simple way. For a given {epoch-year} and {epoch-month} (e.g., 2010 and 1 respectively), the formula
( ( 12*year + mn ) - ( 12*{epoch-year} + {epoch-month} )
will give you the offset in month from the epoch. Add 1 to that and you have your period number. That leads you to something like this:
select year ,
mn ,
( ( 12*year + mn )
- ( 12*{epoch-year} + {epoch-month} )
) + 1 as period
...
from some-table
where year > {epoch-year}
OR ( year = {epoch-year} and mn >= {epoch-month} )
IF you don't have a specific epoch in mind, you can do something like this:
select t.year ,
t.mn ,
( ( 12*year + mn )
- ( 12*epoch.year + epoch.month )
) + 1 as period
...
from ( select year,mn
from some-table
order by year , mn
limit 1
) epoch
cross join some-table t
You should note that one can come up with a formula to number periods based on period lengths longer than 1 month: just compute the offset in months and and use integer division to divide that offset by the period length in months, thus getting to the sequential period number, something like
( ( 12*year + mn )
- ( 12*2010 + 1 )
) DIV 3 + 1 as period
should give you periods of 3 months in length
A cheap version for this particular case:
SELECT year, mn, (year - 2010) * 12 + mn AS period
FROM tbl;
This would also account for months that may be missing in your data.
And it would give you consistent numbers even when only selecting some rows.