I'm trying to split SUM( trs_amt ) and SELECT it into 'trs_sum' column when trs_trust_code is either 1 or 2, and into an 'interest' column when trs_trust_code = 9. I cant seem to figure out how to do it without creating an extra row when adding trs_trust_code to the GROUP BY. I have tried a CASE in SELECT, a CASE in GROUP BY, subqueries
SELECT
trs_desk,
dsk_name,
DATEPART( YEAR, DATEADD( DAY, trs_trx_date, '1600-12-31' ) ) as 'year',
DATEPART( MONTH, DATEADD( DAY, trs_trx_date, '1600-12-31' ) ) as 'month',
COUNT( DISTINCT trs_amt ) AS 'trs_count',
SUM( trs_amt ) AS 'trs_sum',
SUM( trs_comm_amt ) AS 'trs_comm_sum'
FROM cds.trs
JOIN cds.dsk on dsk_code = trs_desk
WHERE trs_desk IN ( 'ACE' )
AND trs_trust_code IN ('1','2','9')
GROUP BY trs_desk, year, month, dsk_name
ORDER BY trs_desk ASC, year DESC, month DESC
Please use the expression case when trs_trust_code = 9 then trs_amt else 0 end in the sum. For example like this:
SELECT
trs_desk,
dsk_name,
DATEPART( YEAR, DATEADD( DAY, trs_trx_date, '1600-12-31' ) ) as 'year',
DATEPART( MONTH, DATEADD( DAY, trs_trx_date, '1600-12-31' ) ) as 'month',
COUNT( DISTINCT trs_amt ) AS 'trs_count',
SUM( case when trs_trust_code = 1 or trs_trust_code = 2 then trs_amt else 0 end ) AS 'trs_sum',
SUM( case when trs_trust_code = 9 then trs_amt else 0 end ) AS 'interest',
SUM( trs_comm_amt ) AS 'trs_comm_sum'
FROM cds.trs
JOIN cds.dsk on dsk_code = trs_desk
WHERE trs_desk IN ( 'ACE' )
AND trs_trust_code IN ('1','2','9')
GROUP BY trs_desk, year, month, dsk_name
ORDER BY trs_desk ASC, year DESC, month DESC
Related
I have data ( int, date , date types)
SELECT * FROM
(
VALUES
(1700171048,'2020-12-21','2021-01-03'),
(1700171048,'2021-01-05','2021-01-12'),
(1700171048,'2021-01-13','2021-01-17'),
(1700171048,'2021-01-18','2021-01-19'),
(1700171048,'2021-01-22','2021-01-27'),
(1700171048,'2021-01-28','2021-02-17')
(1700171049,'2020-12-21','2021-01-03'),
(1700171049,'2021-01-04','2021-01-05'),
(1700171049,'2021-01-06','2021-01-17'),
(1700171049,'2021-01-18','2021-01-19'),
(1700171049,'2021-01-20','2021-01-27'),
(1700171049,'2021-01-28','2021-02-17')
) AS c (id1, st, endt )
I need output( i.e. if start and end dates are continuous then make it part of group )
id1 st endt
1700171048 '2020-12-21' , '2021-01-03'
1700171048 '2021-01-05' , '2021-01-19'
1700171048 '2021-01-22' , '2021-02-17'
1700171049 '2020-12-21' to '2021-02-17'
I tried this, won't work.
select id, case when min(b.st) = max(b.endt) + 1 then min(b.st) end,
case when min(b.endt) = min(b.st) + 1 then max(b.st) end
from c a join c b
group by id
This is a type of gaps-and-islands problem. Use lag() to identify if there is an overlap. Then a cumulative sum of when there is no overlaps and aggregation:
select id1, min(st), max(endt)
from (select t.*,
sum(case when prev_endt >= st + interval '-1 day' then 0 else 1 end) over (partition by id1 order by st) as grp
from (select t.*,
lag(endt) over (partition by id1 order by st) as prev_endt
from t
) t
) t
group by id1, grp;
Here is a db<>fiddle.
I'm trying to create a join table with 2 existing tables. something like below:
This is the first table queries and looks like this
https://ibb.co/sg2MXKf
SELECT
DATEPART( week, dbo.Income.IncomeDate ) AS [Week Income],
DATEPART( YEAR, dbo.Income.IncomeDate ) AS [Year],
SUM ( dbo.Income.CardAmount ) AS [Total Card],
SUM ( dbo.Income.CashAmount ) AS [Total Cash],
SUM ( dbo.Income.TipsAmount ) AS [Total Tip],
SUM ( dbo.Income.SalaryAmount ) AS [Total Salary],
SUM ( dbo.Income.Adjustment ) AS [Total Adjustment]
FROM
dbo.Income
GROUP BY
DATEPART( week, dbo.Income.IncomeDate ),
DATEPART( YEAR, dbo.Income.IncomeDate )
ORDER BY
DATEPART(YEAR, dbo.Income.IncomeDate )
And this is the second table queries and looks like this
https://ibb.co/z8sRwpT
SELECT
DATEPART( wk, dbo.Transactions.PaymentMadeOn ) AS [Week],
COUNT (DATEPART( wk, dbo.Transactions.PaymentMadeOn )) AS [Expenses Count],
DATEPART( YEAR, dbo.Transactions.PaymentMadeOn ) AS [Year],
SUM ( dbo.Transactions.PaymentAmount ) AS [Total]
FROM
dbo.Transactions
GROUP BY
DATEPART( wk, dbo.Transactions.PaymentMadeOn ),
DATEPART( YEAR, dbo.Transactions.PaymentMadeOn )
ORDER BY
DATEPART( YEAR, dbo.Transactions.PaymentMadeOn )
What I expected is something this. Both table 1 and 2 combined, and the total expenses added.
https://ibb.co/0DbZLYV
As commented by SO folks, we cannot access the images that describe your expected results. However we understand that you are looking to JOIN the results of both queries that you are showing.
Here is how to do it : you turn each query into a subquery, and you JOIN them together on their common key fields ; in your use case, this must be Year and Week. The ORDER BY clause needs to be moved to the outer query. In the SELECT, WHERE and ORDER BY clauses, you can freely access all the fields from the subqueries, using the aliases that you defined (here A and B).
Sample code (you will have to adapt the SELECT, I cannot tell what you want it to look like) :
SELECT
A.[Week Income],
A.[Year],
A.[Total] - B.[Total Salary] AS [Balance]
...
FROM (
SELECT
DATEPART( week, dbo.Income.IncomeDate ) AS [Week Income],
DATEPART( YEAR, dbo.Income.IncomeDate ) AS [Year],
SUM ( dbo.Income.CardAmount ) AS [Total Card],
SUM ( dbo.Income.CashAmount ) AS [Total Cash],
SUM ( dbo.Income.TipsAmount ) AS [Total Tip],
SUM ( dbo.Income.SalaryAmount ) AS [Total Salary],
SUM ( dbo.Income.Adjustment ) AS [Total Adjustment]
FROM
dbo.Income
GROUP BY
DATEPART( week, dbo.Income.IncomeDate ),
DATEPART( YEAR, dbo.Income.IncomeDate )
) AS A
LEFT JOIN (
SELECT
DATEPART( wk, dbo.Transactions.PaymentMadeOn ) AS [Week],
COUNT (DATEPART( wk, dbo.Transactions.PaymentMadeOn )) AS [Expenses Count],
DATEPART( YEAR, dbo.Transactions.PaymentMadeOn ) AS [Year],
SUM ( dbo.Transactions.PaymentAmount ) AS [Total]
FROM
dbo.Transactions
GROUP BY
DATEPART( wk, dbo.Transactions.PaymentMadeOn ),
DATEPART( YEAR, dbo.Transactions.PaymentMadeOn )
) AS B ON A.[Week Income] = B.[Week] AND A.[Year] = B.[Year]
ORDER BY
A.[Year],
A.[Week Income]
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.
I have the following query :
select
(select Sum(Stores) from XYZ where Year = '2013' and Month = '8' )
-
(select Sum(SalesStores) from ABC where Year = '2013' and Month = '8') as difference
Here in the above query Year and Month are also columns of a table.
I would like to know if there is a way to run the same query so that , it is run against every month of the year ?
If there are months without data/rows within XYZ or ABC tables then I would use FULL OUTER JOIN:
SELECT ISNULL(x.[Month], y.[Month]) AS [Month],
ISNULL(x.Sum_Stores, 0) - ISNULL(y.Sum_SalesStores, 0) AS Difference
FROM
(
SELECT [Month], Sum(Stores) AS Sum_Stores
FROM XYZ
WHERE [Year] = '2013'
GROUP BY [Month]
) AS x
FULL OUTER JOIN
(
SELECT [Month], Sum(SalesStores) AS Sum_SalesStores
FROM ABC
WHERE [Year] = '2013'
GROUP BY [Month]
) AS y ON x.[Month] = y.[Month]
;WITH Months(Month) AS
(
SELECT 1
UNION ALL
SELECT Month + 1
FROM Months
where Month < 12
)
SELECT '2013' [Year], m.Month, COALESCE(SUM(Stores), 0) - COALESCE(SUM(SalesStores), 0) [Difference]
FROM months m
LEFT JOIN XYZ x ON m.Month = x.Month
LEFT JOIN ABC a ON a.Month = m.Month
GROUP BY m.Month
You could use GROUP BY in your inner trades, and then run a join, like this:
SELECT left.Month, (left.sum - COALESCE(right.sum, 0)) as difference
FROM (
SELECT Month, SUM(Stores) as sum
FROM XYZ WHERE Year = '2013'
GROUP BY Month
) left
LEFT OUTER JOIN (
SELECT Month, SUM(Stores) as sum
FROM ABC WHERE Year = '2013'
GROUP BY Month
) right ON left.Month = right.Months
Note the use of COALESCE. It lets you preserve the value of the first SUM in case when there are no records for the month in the ABC table.
In the following example uses the UNION ALL operator with CTE
;WITH cte AS
(SELECT SUM(Stores) AS Stores, [Month]
FROM dbo.XYZ
WHERE [Year] = '2013'
GROUP BY [Month]
UNION ALL
SELECT -1.00 * SUM(SalesStores), [Month]
FROM dbo.ABC
WHERE [Year] = '2013'
GROUP BY [Month]
)
SELECT [Month], SUM(Stores) AS Difference
FROM cte
GROUP BY [Month]
Demo on SQLFiddle
;WITH Months(Month) AS
(
SELECT 1
UNION ALL
SELECT Month + 1
FROM Months
where Month < 12
)
SELECT Months. Month ,
(select isnull(Sum(Stores),0) from XYZ where Year = '2013' and Month = Months.Month) - (select isnull(Sum(SalesStores),0) from ABC where Year = '2013' and Month =Months.Month) as difference
FROM Months
I have a table containing the following line:
I'd like to create a view that displays the following result (without changing my original table) :
For each line having the same id,day,month and year I'd like to leave a single line with the cost and count and insert 0 in the others.
Here is a portable approach not requiring PARTITION. I have assumed you will not have the same datetimeIN value for more than one row in a group:
select t.id, t.day, t.month, t.year,
case when tm.id is null then 0 else t.cost end as cost,
case when tm.id is null then 0 else t.Count end as Count,
t.datetimeIN, t.datetimeOUT
from MyTable t
left outer join (
select id, day, month, year, min(datetimeIN) as minIN
from MyTable
group by id, day, month, year
) tm on t.id = tm.id
and t.day = tm.day
and t.month = tm.month
and t.year = tm.year
and t.datetimeIN = tm.minIN
You can do something like this:
SELECT id, day, month, year,
CASE WHEN nNum = 1 then cost else 0 end as cost,
CASE WHEN nNum = 1 then "Count" else 0 end as "Count",
datetimeIN, datetimeOUT
FROM (
SELECT id, day, month, year,
cost, "Count", datetimeIN, datetimeOUT,
row_number() OVER (PARTITION BY id, day, month, year
ORDER BY datetimeIN) as nNum
FROM TableName
) A
It uses row_number() to number the rows, and then a CASE statement to single out the first one and make it behave differently.
See it working on SQL Fiddle here.
or, using a common table expression:
with commonTableExp ([day], [month], [year], minDate) as (
select [day], [month], [year], min(datetimeIn)
from #temp
group by [day], [month], [year])
select id,
dt.[day],
dt.[month],
dt.[year],
case when datetimein = minDate then [cost] else 0 end,
case when datetimein = minDate then [count] else 0 end,
dateTimeIn
from #temp dt join commonTableExp cte on
dt.[day] = cte.[day] and
dt.[month] = cte.[month] and
dt.[year] = cte.[year]
order by dateTimeIn
Query
Select id, [day], [month], [year], Case When K.RowID = 1 Then [cost] Else 0 End as Cost, Case When K.RowID = 1 Then [count] Else 0 End as [count], [DateTimeIN], [DateTimeOut] From
(
select ROW_NUMBER() Over(Partition by id, [day], [month], [year] Order by ID ) as RowID, * From Testing
)K
Drop table Testing
Click here to see SQL Profiler details for Red Filter's Query
Click here to see SQL Profiler details for my Query
For More Information You can see SQL Fiddle