SQL Sum() returning postive and negative values - sql

I'm trying to get SUM() to return the sum of a column summing the positive and negative values in the column. Instead its currently returning one positive value and one negative value, can anyone help?
SELECT
LedgerAP.Period, LedgerAP.Account, SUM(LedgerAP.Amount) Amount
FROM
LedgerAP
WHERE
LedgerAP.Period >= 201500 AND LedgerAP.Account = N'105.71'
GROUP BY LedgerAP.Period, LedgerAP.Account
HAVING SUM(Amount) <> 0
UNION ALL
SELECT
LedgerAR.Period, LedgerAR.Account, SUM(LedgerAR.Amount)
FROM
LedgerAR
WHERE
LedgerAR.Period >= 201500 AND LedgerAR.Account = N'105.71'
GROUP BY LedgerAR.Period, LedgerAR.Account
UNION ALL
SELECT
LedgerEx.Period, LedgerEx.Account, SUM(LedgerEx.Amount)
FROM
LedgerEx
WHERE
LedgerEx.Period >= 201500 AND LedgerEx.Account = N'105.71'
GROUP BY LedgerEx.Period, LedgerEx.Account
UNION ALL
SELECT
LedgerMisc.Period, LedgerMisc.Account, SUM(LedgerMisc.Amount)
FROM
LedgerMisc
WHERE
LedgerMisc.Period >= 201500 AND LedgerMisc.Account = N'105.71'
GROUP BY LedgerMisc.Period, LedgerMisc.Account

I think you need to re-aggregate your results:
with l as (
<your query here>
)
select period, account, sum(amount)
from l
group by period, account;
You can do the same thing with a subquery instead of a CTE.

Related

How to use CASE WHEN in group by

I want to use group by for the table NRW_MONTH_DATA.
SELECT [OBJECT_ID]
,[YEAR_MONTH]
,[SELLING_AMOUNT]
,[DEFAULT_SELLING_DATA]
,[LOCK_SELLING_AMOUNT]
,[RGCB]
,[ICKZ]
,[YCKZ]
FROM [dbo].[NRW_MONTH_DATA]
IF LOCK_SELLING_AMOUNT is 0 then group by OBJECT_ID and calculate the sum of [RGCB],[ICKZ] and [YCKZ]
SELECT #SELLING_AMOUNT=(ISNULL(SUM(YCKZ),0)+ISNULL(SUM(RGCB),0)+ ISNULL(SUM(ICKZ),0))
FROM [dbo].[NRW_MONTH_DATA]
WHERE OBJECT_ID=#OBJECT_ID
AND YEAR_MONTH >=#SELLING_CENSUS_START_YM
AND YEAR_MONTH <=#SELLING_CENSUS_END_YM
GROUP BY OBJECT_ID
Now I want to add a condition that if LOCK_SELLING_AMOUNT is 1 , I need to
SELECT #SELLING_AMOUNT=ISNULL(SUM(DEFAULT_SELLING_DATA),0)
ELSE use original result to calculate the sum of the 3 columns.
I use CASE WHEN but is seems that I could not use it in group by
SELECT #SELLING_AMOUNT=
CASE LOCK_SELLING_AMOUNT WHEN 1 THEN SELLING_AMOUNT
ELSE (ISNULL(SUM(YCKZ),0)+ISNULL(SUM(RGCB),0)+ ISNULL(SUM(ICKZ),0))
END
The error is like
The column'dbo.NRW_MONTH_DATA.LOCK_SELLING_AMOUNT' in the select list is invalid because the column is not included in the aggregate function or GROUP BY clause.
Thank you in advance.
I need the group by to calculate the sum of them. Each row has an object_id and a LOCK_SELLING_AMOUNT and other columns for one month, I want to use group to calculate the sum during month span.
It works well when I do not consider the LOCK_SELLING_AMOUNT
First, you don't want GROUP BY. So just use:
SELECT #SELLING_WATER = (COALESCE(SUM(YCKZ), 0) + COALESCE(SUM(RGCB), 0)+ COALESCE(SUM(ICKZ), 0))
FROM [dbo].[NRW_MONTH_DATA]
WHERE OBJECT_ID=#OBJECT_ID AND
YEAR_MONTH >= #SELLING_CENSUS_START_YM
YEAR_MONTH <= #SELLING_CENSUS_END_YM;
Now, the problem is that a column can change values on different rows. So, what row does LOCK_SELLING_AMOUNT come from? We could assume it is the same on all rows. Or perhaps you want an aggregation function:
SELECT #SELLING_WATER = (CASE WHEN MAX(LOCK_SELLING_AMOUNT) = 1
THEN MAX(CASE WHEN LOCK_SELLING_AMOUNT = 1 THEN SELLING_AMOUNT END)
ELSE (COALESCE(SUM(YCKZ), 0) + COALESCE(SUM(RGCB), 0)+ COALESCE(SUM(ICKZ), 0))
END)
FROM [dbo].[NRW_MONTH_DATA]
WHERE OBJECT_ID=#OBJECT_ID AND
YEAR_MONTH >= #SELLING_CENSUS_START_YM
YEAR_MONTH <= #SELLING_CENSUS_END_YM;

SQLite Getting multiple results with LIMIT 1

I have the following problem.
Part of a task is to determine the visitor(s) with the most money spent between 2000 and 2020.
It just looks like this.
SELECT UserEMail FROM Visitor
JOIN Ticket ON Visitor.UserEMail = Ticket.VisitorUserEMail
where Ticket.Date> date('2000-01-01') AND Ticket.Date < date ('2020-12-31')
Group by Ticket.VisitorUserEMail
order by SUM(Price) DESC;
Is it possible to output more than one person if both have spent the same amount?
Use rank():
SELECT VisitorUserEMail
FROM (SELECT VisitorUserEMail, SUM(PRICE) as sum_price,
RANK() OVER (ORDER BY SUM(Price) DESC) as seqnum
FROM Ticket t
WHERE t.Date >= date('2000-01-01') AND Ticket.Date <= date('2021-01-01')
GROUP BY t.VisitorUserEMail
) t
WHERE seqnum = 1;
Note: You don't need the JOIN, assuming that ticket buyers are actually visitors. If that assumption is not true, then use the JOIN.
Use a CTE that returns all the total prices for each email and with NOT EXISTS select the rows with the top total price:
WITH cte AS (
SELECT VisitorUserEMail, SUM(Price) SumPrice
FROM Ticket
WHERE Date >= '2000-01-01' AND Date <= '2020-12-31'
GROUP BY VisitorUserEMail
)
SELECT c.VisitorUserEMail
FROM cte c
WHERE NOT EXISTS (
SELECT 1 FROM cte
WHERE SumPrice > c.SumPrice
)
or:
WITH cte AS (
SELECT VisitorUserEMail, SUM(Price) SumPrice
FROM Ticket
WHERE Date >= '2000-01-01' AND Date <= '2020-12-31'
GROUP BY VisitorUserEMail
)
SELECT VisitorUserEMail
FROM cte
WHERE SumPrice = (SELECT MAX(SumPrice) FROM cte)
Note that you don't need the function date() because the result of date('2000-01-01') is '2000-01-01'.
Also I think that the conditions in the WHERE clause should include the =, right?

Group by in columns and rows, counts and percentages per day

I have a table that has data like following.
attr |time
----------------|--------------------------
abc |2018-08-06 10:17:25.282546
def |2018-08-06 10:17:25.325676
pqr |2018-08-05 10:17:25.366823
abc |2018-08-06 10:17:25.407941
def |2018-08-05 10:17:25.449249
I want to group them and count by attr column row wise and also create additional columns in to show their counts per day and percentages as shown below.
attr |day1_count| day1_%| day2_count| day2_%
----------------|----------|-------|-----------|-------
abc |2 |66.6% | 0 | 0.0%
def |1 |33.3% | 1 | 50.0%
pqr |0 |0.0% | 1 | 50.0%
I'm able to display one count by using group by but unable to find out how to even seperate them to multiple columns. I tried to generate day1 percentage with
SELECT attr, count(attr), count(attr) / sum(sub.day1_count) * 100 as percentage from (
SELECT attr, count(*) as day1_count FROM my_table WHERE DATEPART(week, time) = DATEPART(day, GETDate()) GROUP BY attr) as sub
GROUP BY attr;
But this also is not giving me correct answer, I'm getting all zeroes for percentage and count as 1. Any help is appreciated. I'm trying to do this in Redshift which follows postgresql syntax.
Let's nail the logic before presenting:
with CTE1 as
(
select attr, DATEPART(day, time) as theday, count(*) as thecount
from MyTable
)
, CTE2 as
(
select theday, sum(thecount) as daytotal
from CTE1
group by theday
)
select t1.attr, t1.theday, t1.thecount, t1.thecount/t2.daytotal as percentofday
from CTE1 t1
inner join CTE2 t2
on t1.theday = t2.theday
From here you can pivot to create a day by day if you feel the need
I am trying to enhance the query #johnHC btw if you needs for 7days then you have to those days in case when
with CTE1 as
(
select attr, time::date as theday, count(*) as thecount
from t group by attr,time::date
)
, CTE2 as
(
select theday, sum(thecount) as daytotal
from CTE1
group by theday
)
,
CTE3 as
(
select t1.attr, EXTRACT(DOW FROM t1.theday) as day_nmbr,t1.theday, t1.thecount, t1.thecount/t2.daytotal as percentofday
from CTE1 t1
inner join CTE2 t2
on t1.theday = t2.theday
)
select CTE3.attr,
max(case when day_nmbr=0 then CTE3.thecount end) as day1Cnt,
max(case when day_nmbr=0 then percentofday end) as day1,
max(case when day_nmbr=1 then CTE3.thecount end) as day2Cnt,
max( case when day_nmbr=1 then percentofday end) day2
from CTE3 group by CTE3.attr
http://sqlfiddle.com/#!17/54ace/20
In case that you have only 2 days:
http://sqlfiddle.com/#!17/3bdad/3 (days descending as in your example from left to right)
http://sqlfiddle.com/#!17/3bdad/5 (days ascending)
The main idea is already mentioned in the other answers. Instead of joining the CTEs for calculating the values I am using window functions which is a bit shorter and more readable I think. The pivot is done the same way.
SELECT
attr,
COALESCE(max(count) FILTER (WHERE day_number = 0), 0) as day1_count, -- D
COALESCE(max(percent) FILTER (WHERE day_number = 0), 0) as day1_percent,
COALESCE(max(count) FILTER (WHERE day_number = 1), 0) as day2_count,
COALESCE(max(percent) FILTER (WHERE day_number = 1), 0) as day2_percent
/*
Add more days here
*/
FROM(
SELECT *, (count::float/count_per_day)::decimal(5, 2) as percent -- C
FROM (
SELECT DISTINCT
attr,
MAX(time::date) OVER () - time::date as day_number, -- B
count(*) OVER (partition by time::date, attr) as count, -- A
count(*) OVER (partition by time::date) as count_per_day
FROM test_table
)s
)s
GROUP BY attr
ORDER BY attr
A counting the rows per day and counting the rows per day AND attr
B for more readability I convert the date into numbers. Here I take the difference between current date of the row and the maximum date available in the table. So I get a counter from 0 (first day) up to n - 1 (last day)
C calculating the percentage and rounding
D pivot by filter the day numbers. The COALESCE avoids the NULL values and switched them into 0. To add more days you can multiply these columns.
Edit: Made the day counter more flexible for more days; new SQL Fiddle
Basically, I see this as conditional aggregation. But you need to get an enumerator for the date for the pivoting. So:
SELECT attr,
COUNT(*) FILTER (WHERE day_number = 1) as day1_count,
COUNT(*) FILTER (WHERE day_number = 1) / cnt as day1_percent,
COUNT(*) FILTER (WHERE day_number = 2) as day2_count,
COUNT(*) FILTER (WHERE day_number = 2) / cnt as day2_percent
FROM (SELECT attr,
DENSE_RANK() OVER (ORDER BY time::date DESC) as day_number,
1.0 * COUNT(*) OVER (PARTITION BY attr) as cnt
FROM test_table
) s
GROUP BY attr, cnt
ORDER BY attr;
Here is a SQL Fiddle.

How to find the row where the sum of all values in a column reaches a specified value?

Given data in a table with the following schema:
CREATE TABLE purchases (timestamp DATETIME, quantity INT)
I would like to find the point in time (i.e. the timestamp of the row) where the sum of the values in the quantity column passed a certain threshold value.
This is in MS SQL Server, and ideally I'd like to avoid using a cursor if possible.
SELECT timestamp, SUM(quantity)
FROM purchases
GROUP BY timestamp
HAVING SUM(quantity) > someValue
Or if it is a Running Sum
SELECT a1.timestamp
FROM purchases a1, purchases a2
WHERE a1.quantity >= a2.quantity or (a1.quantity=a2.quantity and a1.timestamp = a2.timestamp)
GROUP BY a1.timestamp, a1.quantity
having SUM(a2.quantity) >= someValue
ORDER BY a1.timestamp ASC
LIMIT 1
You could get the smallest timestamp where the sum of the previous values is larger than the threshold:
select min(timestamp)
from purchases p
where (
select sum(x.quantity)
from purchases x
where x.timestamp < p.timestamp
) > #threshold
However, this is not a very efficient query, so it might be better to use a cursor after all.
In SQL Server 2005+ you could try this:
;WITH numbered AS (
SELECT
timestamp,
quantity,
rownum = ROW_NUMBER() OVER (ORDER BY timestamp)
FROM purchases
),
recursive AS (
SELECT
timestamp,
quantity,
rownum,
runningsum = quantity,
passed = CASE WHEN n.quantity < #threshold THEN 0 ELSE 1 END
FROM numbered
UNION ALL
SELECT
n.timestamp,
n.quantity,
n.rownum,
runningsum = n.quantity + r.runningsum,
passed = CASE WHEN n.quantity + r.runningsum < #threshold THEN 0 ELSE 1 END
FROM numbered n
INNER JOIN recursive r ON n.rownum = r.rownum + 1
)
SELECT MIN(timestamp)
FROM recursive
WHERE passed = 1
Basically, same as #Guffa's solution, only makes use of CTEs to avoid the need of triangular join.

How to avoid DIVIDE BY ZERO error in an SQL query

SELECT YEAR, period, round((1- sum(rej_qty) / sum(recd_qty))*100, 0)
FROM TAB_A
WHERE sid = '200'
AND sdid IN ('4750')
AND
(
(
YEAR ='2011'
AND period IN('01_JAN')
)
OR
(
YEAR = '2010'
AND period IN('02_FEB','03_MAR','04_APR','05_MAY','06_JUN','07_JUL','08_AUG','09_SEP','10_OCT','11_NOV','12_DEC')
)
)
group by year, period
For a particular month, recd_qty is ZERO because of which I am getting DIVIDE BY ZERO error.
Is there any way to avoid DIVIDE BY ZERO error?
I there any way where in that particular month is ignored?
Have you tried using NULLIF()?
SELECT
( 100 / NULLIF( 0, 0 ) ) AS value
;
Oracle Doc
http://www.oracle-base.com/articles/9i/ANSIISOSQLSupport.php#NULLIFFunction
Another example
http://www.bennadel.com/blog/984-Using-NULLIF-To-Prevent-Divide-By-Zero-Errors-In-SQL.htm
If you want to ignore such records you can use a subquery
SELECT YEAR, period, round((1- rej_sum / recd_sum)*100, 0) FROM
(
SELECT YEAR, sum(rej_qty) rej_sum, sum(recd_qty) recd_sum
FROM TAB_A
WHERE sid = '200'
AND sdid IN ('4750')
AND
(
(
YEAR ='2011'
AND period IN('01_JAN')
)
OR
(
YEAR = '2010'
AND period IN ('02_FEB','03_MAR','04_APR','05_MAY','06_JUN','07_JUL','08_AUG','09_SEP','10_OCT','11_NOV','12_DEC')
)
)
group by year, period
)
WHERE recd_sum <> 0;
If you want to keep them and handle the division by zero issue, you can use decode or case
SELECT YEAR, period, DECODE(recd_qty, 0, NULL, round((1- sum(rej_qty) / sum(recd_qty))*100, 0))
round(ISNULL(
((1- sum(rej_qty)) / NULLIF( (sum(recd_qty))*100), 0 )),
0
),0)
If you replace your division using NULLIF to set a NULL when there is divide by zero, then an ISNULL to replace the NULL with a 0 - or indeed whatever value you want it to.
CASE WHEN sum(recd_qty) <> 0 THEN round((1- sum(rej_qty) / sum(recd_qty))*100, 0) ELSE 0 END