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.
Related
Right now I'm in the testing phase of this query so I'm only testing it on two Queries. I've gotten stuck on the final part where I want to left join everything (this will have to be extended to 12 separate queries). The problem is basically as the title suggests--I want to join 12 queries on the created Row_Num column using the WITH() statement, instead of creating 12 separate tables and saving them as table in a database.
WITH Jan_Table AS
(SELECT ROW_NUMBER() OVER (ORDER BY a.SALE_DATE) as Row_ID, a.SALE_DATE, sum(a.revenue) as Jan_Rev
FROM ba.SALE_TABLE a
WHERE a.SALE_DATE BETWEEN '2015-01-01' and '2015-01-31'
GROUP BY a.SALE_DATE)
SELECT ROW_NUMBER() OVER (ORDER BY a.SALE_DATE) as Row_ID, a.SALE_DATE, sum(a.revenue) as Jun_Rev, j.Jan_Rev
FROM ba.SALE_TABLE a
LEFT JOIN Jan_Table j
on "j.Row_ID" = a.Row_ID
WHERE a.SALE_DATE BETWEEN '2015-06-01' and '2015-06-30'
GROUP BY a.SALE_DATE
And then I get this error message:
ERROR: column "j.Row_ID" does not exist
I put in the "j.Row_ID" because the previous message was:
ERROR: column a.row_id does not exist Hint: Perhaps you meant to
reference the column "j.row_id".
Each query works individually without the JOIN and WITH functions. I have one for every month of the year and want to join 12 of these together eventually.
The output should be a single column with ROW_NUM and 12 Monthly Revenues columns. Each row should be a day of the month. I know not every month has 31 days. So, for example, Feb only has 28 days, meaning I'd want days 29, 30, and 31 as NULLs. The query above still has the dates--but I will remove the "SALE_DATE" column after I can just get these two queries to join.
My initially thought was just to create 12 tables but I think that'd be a really bad use of space and not the most logical solution to this problem if I were to extend this solution.
edit
Below are the separate outputs of the two qaruies above and the third table is what I'm trying to make. I can't give you the raw data. Everything above has been altered from the actual column names and purposes of the data that I'm using. And I don't know how to create a dataset--that's too above my head in SQL.
Jan_Table (first five lines)
Row_Num Date Jan_Rev
1 2015-01-01 20
2 2015-01-02 20
3 2015-01-03 20
4 2015-01-04 20
5 2015-01-05 20
Jun_Table (first five lines)
Row_Num Date Jun_Rev
1 2015-06-01 30
2 2015-06-02 30
3 2015-06-03 30
4 2015-06-04 30
5 2015-06-05 30
JOINED_TABLE (first five lines)
Row_Num Date Jun_Rev Date Jan_Rev
1 2015-06-01 30 2015-01-01 20
2 2015-06-02 30 2015-01-02 20
3 2015-06-03 30 2015-01-03 20
4 2015-06-04 30 2015-01-04 20
5 2015-06-05 30 2015-01-05 20
It seems like you can just use group by and conditional aggregation for your full query:
select day(sale_date),
max(case when month(sale_date) = 1 then sale_date end) as jan_date,
max(case when month(sale_date) = 1 then revenue end) as jan_revenue,
max(case when month(sale_date) = 2 then sale_date end) as feb_date,
max(case when month(sale_date) = 2 then revenue end) as feb_revenue,
. . .
from sale_table s
group by day(sale_date)
order by day(sale_date);
You haven't specified the database you are using. DAY() is a common function to get the day of the month; MONTH() is a common function to get the months of the year. However, those particular functions might be different in your database.
Please consider the following payment data:
customerID paymentID pamentType paymentDate paymentAmount
---------------------------------------------------------------------
1 1 A 2015-11-28 500
1 2 A 2015-11-29 -150
1 3 B 2016-03-07 300
2 4 A 2015-03-03 200
2 5 B 2016-05-25 -100
2 6 C 2016-06-24 700
1 7 B 2015-09-22 110
2 8 B 2016-01-03 400
I need to tally per year, per customer, the sum of the diverse payment types (A = invoice, B = credit note, etc), as follows:
year customerID paymentType paymentSum
-----------------------------------------------
2015 1 A 350 : paymentID 1 + 2
2015 1 B 110 : paymentID 7
2015 1 C 0
2015 2 A 200 : paymentID 4
2015 2 B 0
2015 2 C 0
2016 1 A 0
2016 1 B 300 : paymentID 3
2016 1 C 0
2016 2 A 0
2016 2 B 300 : paymentID 5 + 8
2016 2 C 700 : paymentId 6
It is important that there are values for every category (so for 2015, customer 1 has 0 payment value for type C, but still it is good to see this).
In reality, there are over 10 payment types and about 30 customers. The total date range is 10 years.
Is this possible to do in only SQL, and if so could somebody show me how? If possible by using relatively easy queries so that I can learn from it, for instance by storing intermediary result into a #temptable.
Any help is greatly appreciated!
a simple GROUP BY with SUM() on the paymentAmount will gives you what you wanted
select year = datepart(year, paymentDate),
customerID,
paymentType,
paymentSum = sum(paymentAmount)
from payment_data
group by datepart(year, paymentDate), customerID, paymentType
This is a simple query that generates the required 0s. Note that it may not be the most efficient way to generate this result set. If you already have lookup tables for customers or payment types, it would be preferable to use those rather than the CTEs1 I use here:
declare #t table (customerID int,paymentID int,paymentType char(1),paymentDate date,
paymentAmount int)
insert into #t(customerID,paymentID,paymentType,paymentDate,paymentAmount) values
(1,1,'A','20151128', 500),
(1,2,'A','20151129',-150),
(1,3,'B','20160307', 300),
(2,4,'A','20150303', 200),
(2,5,'B','20160525',-100),
(2,6,'C','20160624', 700),
(1,7,'B','20150922', 110),
(2,8,'B','20160103', 400)
;With Customers as (
select DISTINCT customerID from #t
), PaymentTypes as (
select DISTINCT paymentType from #t
), Years as (
select DISTINCT DATEPART(year,paymentDate) as Yr from #t
), Matrix as (
select
customerID,
paymentType,
Yr
from
Customers
cross join
PaymentTypes
cross join
Years
)
select
m.customerID,
m.paymentType,
m.Yr,
COALESCE(SUM(paymentAmount),0) as Total
from
Matrix m
left join
#t t
on
m.customerID = t.customerID and
m.paymentType = t.paymentType and
m.Yr = DATEPART(year,t.paymentDate)
group by
m.customerID,
m.paymentType,
m.Yr
Result:
customerID paymentType Yr Total
----------- ----------- ----------- -----------
1 A 2015 350
1 A 2016 0
1 B 2015 110
1 B 2016 300
1 C 2015 0
1 C 2016 0
2 A 2015 200
2 A 2016 0
2 B 2015 0
2 B 2016 300
2 C 2015 0
2 C 2016 700
(We may also want to play games with a numbers table and/or generate actual start and end dates for years if the date processing above needs to be able to use an index)
Note also how similar the top of my script is to the sample data in your question - except it's actual code that generates the sample data. You may wish to consider presenting sample code in such a way in the future since it simplifies the process of actually being able to test scripts in answers.
1CTEs - Common Table Expressions. They may be thought of as conceptually similar to temp tables - except we don't actually (necessarily) materialize the results. They also are incorporated into the single query that follows them and the whole query is optimized as a whole.
Your suggestion to use temp tables means that you'd be breaking this into multiple separate queries that then necessarily force SQL to perform the task in an order that we have selected rather than letting the optimizer choose the best approach for the above single query.
I have a table with data as follows
Person_ID Date Sale
1 2016-05-08 2686
1 2016-05-09 2688
1 2016-05-14 2689
1 2016-05-18 2691
1 2016-05-24 2693
1 2016-05-25 2694
1 2016-05-27 2695
and there are a million such id's for different people. Sale count is recorded only when a sale increases else it is not. Therefore data for id' 2 can be different from id 1.
Person_ID Date Sale
2 2016-05-10 26
2 2016-05-20 29
2 2016-05-18 30
2 2016-05-22 39
2 2016-05-25 40
Sale count of 29 on 5/20 means he sold 3 products on 20th, and had sold 26 till 5/10 with no sale in between these 2 dates.
Question: I want a sql/dynamic sql to calculate the daily a sales of all the agents and produce a report as follows:
ID Sale_511 Sale_512 Sale_513 -------------- Sale_519 Sale_520
2 0 0 0 --------------- 0 3
(29-26)
Question is how do I use that data to calculate a report. As I do have data between 5/20 to 5/10. SO i can just write a query saying A-B = C?
Can anyone help? Thank you.
P.S - New to SQL so learning.
Using Sql Server 2008.
Most SQL dialects support the lag() function. You can get what you want as:
select person_id, date,
(sale - lag(sale) over (partition by person_id, date)) as Daily_Sales
from t;
This produces one row per date for each person. This format is more typical for how SQL would return such results.
In SQL Server 2008, you can do:
select t.person_id, t.date,
(t.sale - t2.sale) as Daily_Sales
from t outer apply
(select top 1 t2.*
from t t2
where t2.person_id = t.person_id and t2.date < t.date
) t2
I have the following table format.
**ID Name Start Date End Date**
1 ABC 1/1/2015 12/31/2015
1 XYZ 4/1/2015 8/31//2015
1 DEF 1/1/2012 12/31/2012
2 ABC 1/23/2011 1/23/2012
2 ABC 1/31/2012 1/31/2013
3 DEF 2/12/2015 5/30/2015
3 XYZ 4/1/2015 6/01/2015
4 DEF 3/1/2015 12/31/2015
4 DEF 4/1/2015 6/30/2015
I need the count of ID's having Different Name which lies in date range of May 2015
Expected Results
ID COUNT
1 2
3 2
P.S - ID 4 also lies in the date range of MAY 2015, but the Name is same i.e DEF. So I need only ID's 1 and 3 but not 4.
Thank You in advance and appreciated for your efforts.
I imagine your sample data doesn't match your desired results, but I think this is what you're looking for using conditional aggregation:
select id, count(*)
from yourtable
group by id
having sum(case when '5/1/2015' between startdate and enddate then 1 else 0 end) > 1
and count(distinct name) = count(name)
SQL Fiddle Demo
The sum aggregation in the having clause is making sure there are multiple records in between that date. The count clause in the having clause is making sure there aren't any duplicates.
declare
#startdate datetime = '20150501',
#enddate datetime = '20150531'
select t.id, count(distinct t.name)
from mytable t
where t.startdate <= #enddate and t.enddate >= #startdate
group by t.id
having count(distinct t.name) > 1
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?