I asked this question in regard to SQL Server, but what's the answer for an Oracle environment (10g)?
If I have a table containing schedule information that implies particular dates, is there a SQL statement that can be written to convert that information into actual rows, using something like MSSQL's Commom Table Expressions, perhaps?
Consider a payment schedule table with these columns:
StartDate - the date the schedule begins (1st payment is due on this date)
Term - the length in months of the schedule
Frequency - the number of months between recurrences
PaymentAmt - the payment amount :-)
SchedID StartDate Term Frequency PaymentAmt
-------------------------------------------------
1 05-Jan-2003 48 12 1000.00
2 20-Dec-2008 42 6 25.00
Is there a single SQL statement to allow me to go from the above to the following?
Running
SchedID Payment Due Expected
Num Date Total
--------------------------------------
1 1 05-Jan-2003 1000.00
1 2 05-Jan-2004 2000.00
1 3 05-Jan-2005 3000.00
1 4 05-Jan-2006 4000.00
2 1 20-Dec-2008 25.00
2 2 20-Jun-2009 50.00
2 3 20-Dec-2009 75.00
2 4 20-Jun-2010 100.00
2 5 20-Dec-2010 125.00
2 6 20-Jun-2011 150.00
2 7 20-Dec-2011 175.00
Your thoughts are appreciated.
Oracle actually has syntax for hierarchical queries using the CONNECT BY clause. SQL Server's use of the WITH clause looks like a hack in comparison:
SELECT t.SchedId,
CASE LEVEL
WHEN 1 THEN
t.StartDate
ELSE
ADD_MONTHS(t.StartDate, t.frequency)
END 'DueDate',
CASE LEVEL
WHEN 1 THEN
t.PaymentAmt
ELSE
SUM(t.paymentAmt)
END 'RunningExpectedTotal'
FROM PaymentScheduleTable t
WHERE t.PaymentNum <= t.Term / t.Frequency
CONNECT BY PRIOR t.startdate = t.startdate
GROUP BY t.schedid, t.startdate, t.frequency, t.paymentamt
ORDER BY t.SchedId, t.PaymentNum
I'm not 100% on that - I'm more confident about using:
SELECT t.SchedId,
t.StartDate 'DueDate',
t.PaymentAmt 'RunningExpectedTotal'
FROM PaymentScheduleTable t
WHERE t.PaymentNum <= t.Term / t.Frequency
CONNECT BY PRIOR t.startdate = t.startdate
ORDER BY t.SchedId, t.PaymentNum
...but it doesn't include the logic to handle when you're dealing with the 2nd+ entry in the chain to add months & sum the amounts. The summing could be done with GROUP BY CUBE or ROLLUP depending on the detail needed.
I don't understand why 5 payment days for schedid = 1 and 7 for scheid = 2?
48 /12 = 4 and 42 / 6 = 7. So I expected 4 payment days for schedid = 1.
Anyway I use the model clause:
create table PaymentScheduleTable
( schedid number(10)
, startdate date
, term number(3)
, frequency number(3)
, paymentamt number(5)
);
insert into PaymentScheduleTable
values (1,to_date('05-01-2003','dd-mm-yyyy')
, 48
, 12
, 1000);
insert into PaymentScheduleTable
values (2,to_date('20-12-2008','dd-mm-yyyy')
, 42
, 6
, 25);
commit;
And now the select with model clause:
select schedid, to_char(duedate,'dd-mm-yyyy') duedate, expected, i paymentnum
from paymentscheduletable
model
partition by (schedid)
dimension by (1 i)
measures (
startdate duedate
, paymentamt expected
, term
, frequency)
rules
( expected[for i from 1 to term[1]/frequency[1] increment 1]
= nvl(expected[cv()-1],0) + expected[1]
, duedate[for i from 1 to term[1]/frequency[1] increment 1]
= add_months(duedate[1], (cv(i)-1) * frequency[1])
)
order by schedid,i;
This outputs:
SCHEDID DUEDATE EXPECTED PAYMENTNUM
---------- ---------- ---------- ----------
1 05-01-2003 1000 1
1 05-01-2004 2000 2
1 05-01-2005 3000 3
1 05-01-2006 4000 4
2 20-12-2008 25 1
2 20-06-2009 50 2
2 20-12-2009 75 3
2 20-06-2010 100 4
2 20-12-2010 125 5
2 20-06-2011 150 6
2 20-12-2011 175 7
11 rows selected.
I didn't set out to answer my own question, but I'm doing work with Oracle now and I have had to learn some new Oracle-flavored things.
Anyway, the CONNECT BY statement is really nice--yes, much nicer than MSSQL's hierchical query approach, and using that construct, I was able to produce a very clean query that does what I was looking for:
SELECT DISTINCT
t.SchedID
,level as PaymentNum
,add_months(T.StartDate,level - 1) as DueDate
,(level * t.PaymentAmt) as RunningTotal
FROM SchedTest t
CONNECT BY level <= (t.Term / t.Frequency)
ORDER BY t.SchedID, level
My only remaining issue is that I had to use DISTINCT because I couldn't figure out how to select my rows from DUAL (the affable one-row Oracle table) instead of from my table of schedule data, which has at least 2 rows. If I could do the above with FROM DUAL, then my DISTINCT indicator wouldn't be necessary. Any thoughts?
Other than that, I think this is pretty nice. Et tu?
Related
Hi I'm trying to find out how frequently a business would change their address. I've got two tables one with trading address and the other with office address. The complicated part is one id will have several sequence numbers. I need to find out the difference between one address's create date and another address create date.
Trading address table
ID
Create_date
Seq_no
Address
1
2002-03-23
1
20 bottle way
1
2002-05-23
2
12 sunset blvd
2
2003-01-14
1
76 moonrise ct
Office address table
ID
Create_date
Seq_no
Address
1
2004-02-13
1
12 paper st
2
2005-03-01
1
30 pencil way
2
2005-04-01
2
25 mouse rd
2
2005-08-01
3
89 glass cct
My result set will be
Difference
NumberOfID's
30 days
1
60 days
1
120 days
1
Other
2
I think I solved it. Steps are
I did an union and created a separate column to find out actual
sequence no for the union set.
Used LEAD function to create a separate column of to bring up the date.
Date difference to find out the actual difference between id's
Case statement to categorize the days and counting the id's
WITH BASE AS (
SELECT ID,SEQ_NO,CREATE_DATE
FROM TradingAddress
UNION ALL
SELECT ID,SEQ_NO,CREATE_DATE
FROM OfficeAddress
),
WORKINGS AS (
SELECT ID,CREATE_DATE,
DENSE_RANK() OVER (PARTITION BY ID ORDER BY CREATE_DATE ASC) AS SNO,
LEAD(CREATE_DATE) OVER (PARTITION BY ID ORDER BY CREATE_DATE) AS REF_DATE,
DATEDIFF(DAY,CREATE_DATE,LEAD(CREATE_DATE) OVER (PARTITION BY ID ORDER BY CREATE_DATE)) AS DATE_DIFFERENCE
FROM BASE
),
WORKINGS_2 AS (
SELECT *,
CASE WHEN DATE_DIFFERENCE BETWEEN 1 AND 30 THEN '1-30 DAYS'
WHEN DATE_DIFFERENCE BETWEEN 31 AND 60 THEN '31-60 DAYS'
WHEN DATE_DIFFERENCE BETWEEN 61 AND 90 THEN '61-90 DAYS'
WHEN DATE_DIFFERENCE BETWEEN 91 AND 120 THEN '91-120 DAYS'ELSE 'MORE THAN 120 DAYS'
END AS DIFFERENCE_DAYS
FROM WORKINGS
WHERE REF_DATE IS NOT NULL
)
SELECT DIFFERENCE_DAYS,COUNT(DIFFERENCE_DAYS) AS NUMBEROFIDS
FROM WORKINGS_2
GROUP BY DIFFERENCE_DAYS
you can do this in this way
SELECT DATEDIFF(day,t1.create_date,t2.create_date) AS 'yourdats', Count (*) as ids FROM test1 t1 join test2 t2 on t1.id = t2.id GROUP BY DATEDIFF(day,t1.create_date,t2.create_date)
This is my table:
id
Total
Date
1
3
410
2
4
121
3
7
630
4
8
629
5
9
101
Date part is saved as int month and day. How to find the total amount made in the previous month of the current month?
Try the following query:
Select Date_/100 as Date_Month, Sum(Total) as MonthlyTotal From YourTable
Where MONTH(GETDATE()) - 1 = (Date_/100)
Group By (Date_/100)
See a demo from db<>fiddle.
I concur with the comments made above. I get it that you can't change the way that you store your "dates" . But you should make whoever made that decision miserable. They are asking for trouble like that.
Having said that -
I rely, here, on the fact that the division of two integers, in SQL Server, if it is not an integer already, is truncated to the next lower integer, and returned as integer.
WITH
-- your input, don't use in final query ...
-- I renamed the third column more aptly to "monthday"
indata(id,Total,monthday) AS (
SELECT 1,3.00,410
UNION ALL SELECT 2,4.55,121
UNION ALL SELECT 3,7.40,630
UNION ALL SELECT 4,8.00,629
)
-- real query starts here - replace following comma with "WITH"
,
per_month AS (
SELECT
monthday / 100 AS monthno
, SUM(total) AS monthtot
FROM indata
GROUP BY monthno
-- ctl monthno | monthtot
-- ctl ---------+----------
-- ctl 1 | 4.55
-- ctl 4 | 3.00
-- ctl 6 | 15.40
)
SELECT
*
FROM per_month
WHERE monthno=MONTH(CURRENT_DATE) - 1;
-- out monthno | monthtot
-- out ---------+----------
-- out 6 | 15.40
Below are my two tables of data
Acct BillingDate REV
101 01/05/2018 5
101 01/30/2018 4
102 01/15/2018 2
103 01/4/2018 3
103 02/05/2018 2
106 03/06/2018 5
Acct BillingDate Lease_Rev
101 01/15/2018 2
102 01/16/2018 1
103 01/19/2018 2
104 02/05/2018 3
105 04/02/2018 1
Desired Output
Acct Jan Feb Mar Apr
101 11
102 3
103 5 2
104 3
105 1
106 5
My SQL Script is Below:
SELECT [NewSalesHistory].[Region]
,[NewSalesHistory].[Account]
,SUM(case when [NewSalesHistory].[billingdate] between '6/1/2016' and '6/30/2016' then REV else 0 end ) + [X].[Jun-16] AS 'Jun-16'
FROM [NewSalesHistory]
FULL join (SELECT [Account]
,SUM(case when [BWLease].[billingdate] between '6/1/2016' and '6/30/2016' then Lease_REV else 0 end ) as 'Jun-16'
FROM [AirgasPricing].[dbo].[BWLease]
GROUP BY [Account]) X ON [NewSalesHistory].[Account] = [X].[Account]
GROUP BY [NewSalesHistory].[Region]
,[NewSalesHistory].[Account]
,[X].[Jun-16]
I am having trouble combining these tables. If there is a rev amt and lease rev amt then it will combine (sum) for that account. If there is not a lease rev amt (which is the majority of the time), it brings back NULLs for all other rev amts accounts in Table 1. Table one can have duplicate accounts with different Rev, while the Table two is one unique account only w Lease rev. The output above is how I would like to see the data.
What am I missing here? Thanks!
I would suggest union all and group by:
select acct,
sum(case when billingdate >= '2016-01-01' and billingdate < '2016-02-01' then rev end) as rev_201601,
sum(case when billingdate >= '2016-02-01' and billingdate < '2016-03-01' then rev end) as rev_201602,
. . .
from ((select nsh.acct, nsh.billingdate, nsh.rev
from NewSalesHistory
) union all
(select bl.acct, bl.billingdate, bl.rev
from AirgasPricing..BWLease bl
)
) x
group by acct;
Okay, so there are a few things going on here:
1) As Gordon Linoff mentioned you can perform a union all on the two tables. Be sure to limit your column selections and name your columns appropriately:
select
x as consistentname1,
y as consistentname2,
z as consistentname3
from [NewSalesHistory]
union all
select
a as consistentname1,
b as consistentname2,
c as consistentname3
from [BWLease]
2) Your desired result contains a pivoted month column. Generate a column with your desired granularity on the result of the union in step one. F.ex. months:
concat(datepart(yy, Date_),'-',datename(mm,Date_)) as yyyyM
Then perform aggregation using a group by:
select sum(...) as desiredcolumnname
...
group by PK1, PK2, yyyyM
Finally, PIVOT to obtain your result: https://learn.microsoft.com/en-us/sql/t-sql/queries/from-using-pivot-and-unpivot?view=sql-server-2017
3) If you have other fields/columns that you wish to present then you first need to determine whether they are measures (can be aggregated) or are dimensions. That may be best addressed in a follow up question after you've achieved what you set out for in this part.
Hope it helps
As an aside, it seems like you are preparing data for reporting. Performing these transformations can be facilitated using a GUI such as MS Power Query. As long as your end goal is not data manipulation in the DB itself, you do not need to resort to raw sql.
This question already has answers here:
How to group by on consecutive values in SQL
(2 answers)
Closed 6 years ago.
I have a requirement to compute bonus payout based on spread goal and date achieved as follows:
Spread Goal | Date Achieved | Bonus Payout
----------------------------------------------
$3,500 | < 27 wks | $2,000
$3,500 | 27 wks to 34 wks | $1,000
$3,500 | > 34 wks | $0
I have a table in SQL Server 2014 where the subset of the data is as follows:
EMP_ID WK_NUM NET_SPRD_LCL
123 10 0
123 11 1500
123 15 3600
123 18 3800
123 19 4000
Based on the requirement, I need to look for records where NET_SPRD_LCL is greater than or equal to 3500 during 2 continuous wk_num.
So, in my example, WK_NUM 15 and 18 (which in my case are continuous because I have a calendar table that I join to to exclude the holiday weeks) are less than 27 wks and have NET_SPRD_LCL > 3500.
For this case, I want to output the MAX(WK_NUM), it's associated NET_SPRD_LCL and BONUSPAYOUT = 2000. So, the output should be as follows:
EMP_ID WK_NUM NET_SPRD_LCL BONUSPAYOUT
123 18 3800 2000
If this meets the first requirement, the script should output and quit. If not, then I will look for the second requirement where Date Achieved is between 27 wks to 34 wks.
I hope I was able to explain my requirement clearly :-)
Thanks for the help.
Nice question! I broke my mind on situations like 4 rows in a turn are with 3500 and more. And came up with this.
You can use CTE, recursive CTE and ROW_NUMBER():
;WITH cte AS(
SELECT EMP_ID,
WK_NUM,
NET_SPRD_LCL,
ROW_NUMBER() OVER (PARTITION BY EMP_ID ORDER BY WK_NUM) rn
FROM YourTable
)
, recur AS (
SELECT EMP_ID,
WK_NUM,
NET_SPRD_LCL,
rn,
1 as lev
FROM cte
WHERE rn = 1
UNION ALL
SELECT c.EMP_ID,
c.WK_NUM,
c.NET_SPRD_LCL,
c.rn,
CASE WHEN c.NET_SPRD_LCL < 3500 THEN Lev+1 ELSE Lev END
FROM cte c
INNER JOIN recur r
ON r.rn+1 = c.rn
)
SELECT TOP 1 WITH TIES
EMP_ID,
WK_NUM,
NET_SPRD_LCL,
CASE WHEN WK_NUM < 27 THEN $2000
WHEN WK_NUM between 27 and 34 THEN $1000
ELSE $0 END as Bonus
FROM recur
WHERE NET_SPRD_LCL >= 3500
ORDER BY ROW_NUMBER() OVER(PARTITION BY EMP_ID,lev ORDER BY WK_NUM)%2
Output for data you provided:
EMP_ID WK_NUM NET_SPRD_LCL Bonus
123 18 3800 2000,00
I was trying to aggregate a 7 days data for FY13 (starts on 10/1/2012 and ends on 9/30/2013) in SQL Server but so far no luck yet. Could someone please take a look. Below is my example data.
DATE BREAD MILK
10/1/12 1 3
10/2/12 2 4
10/3/12 2 3
10/4/12 0 4
10/5/12 4 0
10/6/12 2 1
10/7/12 1 3
10/8/12 2 4
10/9/12 2 3
10/10/12 0 4
10/11/12 4 0
10/12/12 2 1
10/13/12 2 1
So, my desired output would be like:
DATE BREAD MILK
10/1/12 1 3
10/2/12 2 4
10/3/12 2 3
10/4/12 0 4
10/5/12 4 0
10/6/12 2 1
Total 11 15
10/7/12 1 3
10/8/12 2 4
10/9/12 2 3
10/10/12 0 4
10/11/12 4 0
10/12/12 2 1
10/13/12 2 1
Total 13 16
--------through 9/30/2013
Please note, since FY13 starts on 10/1/2012 and ends on 9/30/2012, the first week of FY13 is 6 days instead of 7 days.
I am using SQL server 2008.
You could add a new computed column for the date values to group them by week and sum the other columns, something like this:
SELECT DATEPART(ww, DATEADD(d,-2,[DATE])) AS WEEK_NO,
SUM(Bread) AS Bread_Total, SUM(Milk) as Milk_Total
FROM YOUR_TABLE
GROUP BY DATEPART(ww, DATEADD(d,-2,[DATE]))
Note: I used DATEADD and subtracted 2 days to set the first day of the week to Monday based on your dates. You can modify this if required.
Use option with GROUP BY ROLLUP operator
SELECT CASE WHEN DATE IS NULL THEN 'Total' ELSE CONVERT(nvarchar(10), DATE, 101) END AS DATE,
SUM(BREAD) AS BREAD, SUM(MILK) AS MILK
FROM dbo.test54
GROUP BY ROLLUP(DATE),(DATENAME(week, DATE))
Demo on SQLFiddle
Result:
DATE BREAD MILK
10/01/2012 1 3
10/02/2012 2 4
10/03/2012 2 3
10/04/2012 0 4
10/05/2012 4 0
10/06/2012 2 1
Total 11 15
10/07/2012 1 3
10/08/2012 4 7
10/10/2012 0 4
10/11/2012 4 0
10/12/2012 2 1
10/13/2012 2 1
Total 13 16
You are looking for a rollup. In this case, you will need at least one more column to group by to do your rollup on, the easiest way to do that is to add a computed column that groups them into weeks by date.
Take a lookg at: Summarizing Data Using ROLLUP
Here is the general idea of how it could be done:
You need a derived column for each row to determine which fiscal week that record belongs to. In general you could subtract that record's date from 10/1, get the number of days that have elapsed, divide by 7, and floor the result.
Then you can GROUP BY that derived column and use the SUM aggregate function.
The biggest wrinkle is that 6 day week you start with. You may have to add some logic to make sure that the weeks start on Sunday or whatever day you use but this should get you started.
The WITH ROLLUP suggestions above can help; you'll need to save the data and transform it as you need.
The biggest thing you'll need to be able to do is identify your weeks properly. If you don't have those loaded into tables already so you can identify them, you can build them on the fly. Here's one way to do that:
CREATE TABLE #fy (fyear int, fstart datetime, fend datetime);
CREATE TABLE #fylist(fyyear int, fydate DATETIME, fyweek int);
INSERT INTO #fy
SELECT 2012, '2011-10-01', '2012-09-30'
UNION ALL
SELECT 2013, '2012-10-01', '2013-09-30';
INSERT INTO #fylist
( fyyear, fydate )
SELECT fyear, DATEADD(DAY, Number, DATEADD(DAY, -1, fy.fstart)) AS fydate
FROM Common.NUMBERS
CROSS APPLY (SELECT * FROM #fy WHERE fyear = 2013) fy
WHERE fy.fend >= DATEADD(DAY, Number, DATEADD(DAY, -1, fy.fstart));
WITH weekcalc AS
(
SELECT DISTINCT DATEPART(YEAR, fydate) yr, DATEPART(week, fydate) dt
FROM #fylist
),
ridcalc AS
(
SELECT
ROW_NUMBER() OVER (ORDER BY yr, dt) AS rid, yr, dt
FROM weekcalc
)
UPDATE #fylist
SET fyweek = rid
FROM #fylist
JOIN ridcalc
ON DATEPART(YEAR, fydate) = yr
AND DATEPART(week, fydate) = dt;
SELECT list.fyyear, list.fyweek, p.[date], COUNT(bread) AS Bread, COUNT(Milk) AS Milk
FROM products p
JOIN #fylist list
ON p.[date] = list.fydate
GROUP BY list.fyyear, list.fyweek, p.[date] WITH ROLLUP;
The Common.Numbers reference above is a simple numbers table that I use for this sort of thing (goes from 1 to 1M). You could also build that on the fly as needed.