I am fetching COUNT from 3 different table based on some conditions but to group them on time interval. (Like: 1 hour, 30 minutes.)
I need the following output:
Date Interval Success Un-Success Closed CLInotFound
2/20/2016 01:01 – 02:00 5 3 2 13
2/20/2016 02:01 – 03:00 14 9 23 5
2/20/2016 03:01 – 04:00 8 67 89 345
2/20/2016 04:01 – 05:00 2 23 92 12
2/20/2016 05:01 – 06:00 44 55 78 98
2/20/2016 06:01 – 07:00 12 87 56 445
I am able to calculate them separately but when I am trying to combine the result gets different.
Query 1 For Success & Un-Success:
SELECT CONVERT(VARCHAR(5), A.InsertionDate ,108) AS 'Interval',
COUNT(CASE WHEN A.call_result = 0 then 1 ELSE NULL END) AS 'Success',
COUNT(CASE WHEN A.call_result = 1 then 1 ELSE NULL END) AS 'Un-Success'
from dbo.AutoRectifier A
WHERE CONVERT(DateTime,A.InsertionDate,101) BETWEEN '2016-02-19 02:10:35.000' AND '2016-02-19 07:15:35.000'
GROUP BY A.InsertionDate;
Query 2 For Closed:
SELECT CONVERT(VARCHAR(5), C.DateAdded ,108) AS 'Interval',
COUNT(*) AS 'Closed' FROM dbo.ChangeTicketState C
WHERE C.SourceFlag = 'S-CNR' AND C.RET LIKE '%CLOSE%'
AND C.DateAdded BETWEEN '2016-02-19 02:10:35.000' AND '2016-02-19 07:15:35.000'
GROUP BY C.DateAdded;
Query 3 For CLI Not Found:
SELECT CONVERT(VARCHAR(5), T.DateAdded ,108) AS 'Interval',
COUNT(*) 'CLI Not Found' FROM dbo.TICKET_INFO T
WHERE T.CONTACT_NUMBER = '' AND T.DateAdded BETWEEN '2016-02-19 02:10:35.000' AND '2016-02-19 07:15:35.000'
GROUP BY T.DateAdded;
You have got several problems to solve in you question.
You have to produce a union result set from Query1, Query2, Query3 to group it. You can use UNION ALL for it but all 3 queries must have similar column list for it. So, add
0 as Closed, 0 as CLInotFound
to select-list of the Query1,
add
0 as Success, 0 as Un-Success, 0 as CLInotFound
to select-list of the Query2 and add
0 as Success, 0 as Un-Success, 0 as Closed
to Query3
Then you can write
select * from Query1
union all
select * from Query2
union all
select * from Query3
Don't convert date to varchar at Query1, Query2, Query3. Better return datetime from query to use it for grouping after union. So, query 1 will look like
SELECT A.InsertionDate AS Date, ...
Query2 -
SELECT C.DateAdded AS Date, ...
etc.
Then you can group results on per-hour basis, for instance using GROUP BY SUBSTRING(CONVERT(VARCHAR(20), Date ,120), 1, 13)
So, the result will look like
SELECT SUBSTRING(CONVERT(VARCHAR(20), Date ,120), 1, 13) as Interval,
sum(Success) as
sum(Un-Success) as,
sum(Closed) as,
sum(CLInotFound) as
from (
select * from Query1
union all
select * from Query2
union all
select * from Query3
) q
GROUP BY SUBSTRING(CONVERT(VARCHAR(20), Date ,120), 1, 13)
Its result have slightly different format of Date and Interval field, but shows the idea.
You can use GROUP BY DATEPART(yy, Date), DATEPART(mm, Date), DATEPART(dd, Date), DATEPART(hh, Date) instead of GROUP BY SUBSTRING(CONVERT(VARCHAR(20), Date ,120), 1, 13) and format if as you wish.
Also result set does not contain intervals that not present at original data.
You can add Query4, containing all intervals required and zeros at all fields to fix it.
Related
I am trying to calculate numbers of customers whom are active in the past 3 and 6 months.
SELECT COUNT (DISTINCT CustomerNo)
FROM SalesDetail
WHERE InvoiceDate > (GETDATE() - 180) AND InvoiceDate < (GETDATE() - 90)
SELECT COUNT (DISTINCT CustomerNo)
FROM SalesDetail
WHERE InvoiceDate > (GETDATE() - 90)
However, based on above query, I'll get count Customers which has been active for both in the last 3 months and the last 6 months, even if there are duplicates like this.
Customer A bought once in past 3 months
Customer A bought once in past 6 months too
How do I filter out the customers, so that if customer A has been active in both past 3 and 6 months, he/she will only be counted in the 'active in past 3 months' query and not in the 'active in past 6 months' too.
I solve this problem this way
Let us consider you have following table. You might have more columns but for the result you want, we only require customer_id and date they bought something on.
CREATE TABLE [dbo].[customer_invoice](
[id] [int] IDENTITY(1,1) NOT NULL,
[customer_id] [int] NULL,
[date] [date] NULL,
CONSTRAINT [PK_customer_invoice] PRIMARY KEY([id]);
I created this sample data on this table
INSERT INTO [dbo].[customer_invoice]
([customer_id]
,[date])
VALUES
(1,convert(date,'2019-12-01')),
(2,convert(date,'2019-11-05')),
(2,convert(date,'2019-8-01')),
(3,convert(date,'2019-7-01')),
(4,convert(date,'2019-4-01'));
Lets not try to jump directly on the final solution directly but take a single leap each time.
SELECT customer_id, MIN(DATEDIFF(DAY,date,GETDATE())) AS lastActiveDays
FROM customer_invoice GROUP BY customer_id;
The above query gives you the number of days before each customer was active
customer_id lastActiveDays
1 15
2 41
3 168
4 259
Now We will use this query as subquery and Add a new column ActiveWithinCategory so that in later step we can group our data by the column.
SELECT customer_id, lastActiveDays,
CASE WHEN lastActiveDays<90 THEN 'active within 3 months'
WHEN lastActiveDays<180 THEN 'active within 6 months'
ELSE 'not active' END AS ActiveWithinCategory
FROM(
SELECT customer_id, MIN(DATEDIFF(DAY,date,GETDATE())) AS lastActiveDays
FROM customer_invoice GROUP BY customer_id
)AS temptable;
This query gives you the the following result
customer_id lastActiveDays ActiveWithinCategory
1 15 active within 3 months
2 41 active within 3 months
3 168 active within 6 months
4 259 not active
Now use the above whole thing as subquery and Group the data using ActiveWithinCategory
SELECT ActiveWithinCategory, COUNT(*) AS NumberofCustomers FROM (
SELECT customer_id, lastActiveDays,
CASE WHEN lastActiveDays<90 THEN 'active within 3 months'
WHEN lastActiveDays<180 THEN 'active within 6 months'
ELSE 'not active' END AS ActiveWithinCategory
FROM(
SELECT customer_id, MIN(DATEDIFF(DAY,date,GETDATE())) AS lastActiveDays
FROM customer_invoice GROUP BY customer_id
)AS temptable
) AS FinalResult GROUP BY ActiveWithinCategory;
And Here is your final result
ActiveWithinCategory NumberofEmployee
active within 3 months 2
active within 6 months 1
not active 1
If you want to achieve same thing is MySQL Database
Here is the final Query
SELECT ActiveWithinCategory, count(*) NumberofCustomers FROM(
SELECT MIN(DATEDIFF(curdate(),date)) AS lastActiveBefore,
IF(MIN(DATEDIFF(curdate(),date))<90,
'active within 3 months',
IF(MIN(DATEDIFF(curdate(),date))<180,'active within 6 months','not active')
) ActiveWithinCategory
FROM customer_invoice GROUP BY customer_id
) AS FinalResult GROUP BY ActiveWithinCategory;
I suspect that you want to do conditional aggregation here:
SELECT
CustomerNo,
COUNT(CASE WHEN InvoiceDate > GETDATE() - 90 THEN 1 END) AS cnt_last_3,
COUNT(CASE WHEN InvoiceDate > GETDATE() - 180 AND InvoiceDate < GETDATE() - 90
THEN 1 END) AS cnt_first_3
FROM yourTable
GROUP BY
CustomerNo;
Here cnt_last_3 is the count over the immediate past 3 months, and cnt_first_3 is the count from the 3 month period starting 6 months ago and ending 3 months ago.
If you want the distinct count you may add distinct like this
Select
count( Case when dt between getdate()- 90 and getdate() then id else null end) cnt_3_months
,count(distinct Case when dt between getdate() - 180 and getdate() - 90 then id else null end) cnt_6_months
from a
This question already has answers here:
How can I get multiple counts with one SQL query?
(12 answers)
Closed 4 years ago.
I have a set of queries that represent the data from different sysdates (from the last 5, 7 and 30 days).
My doubt is how to express in a query this results in this matter:
STATE | 5 DAYS | 7 DAYS | 30 DAYS
---------------------------------
INIT | 1 | 1 | 2
---------------------------------
SECN | 2 | 2 | 2
NOTE: This is from a single table with different sysdates in consideration
NOTE2: An query example is this
select
CASE WHEN STATUS = 'INI' then 'Initial'
WHEN STATUS = 'SECN' the 'Second'
END 'Status', count(*)
from db.FilesTable
where 1=1
and DAT_Files >= DATEADD(day,-5,GETDATE())
Use conditional aggregation to count records only when a particular condition occurs. The CASE will be computed before the aggregation occurs, so you can put any expression on any column.
select
State = T.Status,
[5 Days] = COUNT(CASE WHEN T.DAT_Files >= DATEADD(day, -5, GETDATE()) THEN 1 END),
[7 Days] = COUNT(CASE WHEN T.DAT_Files >= DATEADD(day, -7, GETDATE()) THEN 1 END),
[30 Days] = COUNT(1)
from
db.FilesTable AS T
where
T.Status IN ('INI', 'SECN') AND
DAT_Files >= DATEADD(day, -30, GETDATE()) -- Biggest period filter here
GROUP BY
T.Status
I think you could write a query of this type:
SELECT State,
SUM (CASE WHEN ColA < 6 THEN 1 ELSE 0 END) AS '5 Days',
SUM (CASE WHEN ColA IN (6, 7) THEN 1 ELSE 0 END) AS '7 Days',
SUM (CASE WHEN ColA > 7 AND ColA < 31 THEN 1 ELSE 0 END) AS '30 Days'
FROM TableA
Obviously you might want to adjust something, but this gives some direction.
I have table that shows these information
Month NewClients OnHoldClients
5-2017 10 2
6-2017 16 4
7-2017 11 1
8-2017 15 6
9-2017 18 7
I am trying to find the accumulative total for each month
which is
(NewClients - OnHoldClients) + Previous Month Total
Something like this
Month NewClients OnHoldClients Total
5-2017 10 2 8
6-2017 16 4 20
7-2017 11 1 30
8-2017 15 6 39
9-2017 18 7 50
the query i tried to build was something like this but I think should be an easier way to do that
UPDATE MyTable
SET Total = (SELECT TOP 1 Total FROM MyTable B WHERE B.Month < A.Month) + NewClients - OnHoldClients
FROM MyTable A
Before we begin, note the mere fact that you're facing such calculative problem is a symptom that maybe you don't have the best possible design. Normally for this purpose calculated values are being stored along the way as the records are inserted. So i'd say you'd better have a total field to begin with and calculate it as records amass.
Now let's get down to the problem at hand. i composed a query which does that nicely but it's a bit verbose due to recursive nature of the problem. However, it yields the exact expected result:
DECLARE #dmin AS date = (SELECT min(mt.[Month]) from dbo.MyTable mt);
;WITH cte(_Month, _Total) AS (
SELECT mt.[Month] AS _Month, (mt.NewClients - mt.OnHoldClients) AS _Total
FROM dbo.MyTable mt
WHERE mt.[Month] = #dmin
UNION ALL
SELECT mt.[Month] AS _Month, ((mt.NewClients - mt.OnHoldClients) + ccc._Total) AS _Total
FROM dbo.MyTable mt
CROSS APPLY (SELECT cc._Total FROM (SELECT c._Total,
CAST((row_number() OVER (ORDER BY c._Month DESC)) AS int) as _Rank
FROM cte c WHERE c._Month < mt.[Month]) as cc
WHERE cc._Rank = 1) AS ccc
WHERE mt.[Month] > #dmin
)
SELECT c._Month, max(c._Total) AS Total
FROM cte c
GROUP BY c._Month
It is a recursive CTE structure that goes about each record all along the way to the initial month and adds up to the final Total value. This query only includes Month and Total fields but you can easily add the other 2 to the list of projection.
Try this
;WITH CTE([Month],NewClients,OnHoldClients)
AS
(
SELECT '5-2017',10,2 UNION ALL
SELECT '6-2017',16,4 UNION ALL
SELECT '7-2017',11,1 UNION ALL
SELECT '8-2017',15,6 UNION ALL
SELECT '9-2017',18,7
)
SELECT [Month],
NewClients,
OnHoldClients,
SUM(MonthTotal)OVER( ORDER BY [Month]) AS Total
FROM
(
SELECT [Month],
NewClients,
OnHoldClients,
SUM(NewClients-OnHoldClients)OVER(PArtition by [Month] Order by [Month]) AS MonthTotal
FROM CTE
)dt
Result,Demo:http://rextester.com/DKLG54359
Month NewClients OnHoldClients Total
--------------------------------------------
5-2017 10 2 8
6-2017 16 4 20
7-2017 11 1 30
8-2017 15 6 39
9-2017 18 7 50
I have a T-SQL Quotes table and need to be able to count how many quotes were in an open status during past months.
The dates I have to work with are an 'Add_Date' timestamp and an 'Update_Date' timestamp. Once a quote is put into a 'Won' or 'Loss' columns with a value of '1' in that column it can no longer be updated. Therefore, the 'Update_Date' effectively becomes the Closed_Status timestamp.
Here's a few example records:
Quote_No Add_Date Update_Date Open_Quote Win Loss
001 01-01-2016 NULL 1 0 0
002 01-01-2016 3-1-2016 0 1 0
003 01-01-2016 4-1-2016 0 0 1
Here's a link to all the data here:
https://drive.google.com/open?id=0B4xdnV0LFZI1T3IxQ2ZKRDhNd1k
I asked this question previously this year and have been using the following code:
with n as (
select row_number() over (order by (select null)) - 1 as n
from master..spt_values
)
select format(dateadd(month, n.n, q.add_date), 'yyyy-MM') as yyyymm,
count(*) as Open_Quote_Count
from quotes q join
n
on (closed_status = 1 and dateadd(month, n.n, q.add_date) <= q.update_date) or
(closed_status = 0 and dateadd(month, n.n, q.add_date) <= getdate())
group by format(dateadd(month, n.n, q.add_date), 'yyyy-MM')
order by yyyymm;
The problem is this code is returning a cumulative value. So January was fine, but then Feb is really Jan + Feb, and March is Jan+Feb+March, etc. etc. It took me a while to discover this and the numbers returned now way, way off and I'm trying to correct them.
From the full data set the results of this code are:
Year-Month Open_Quote_Count
2017-01 153
2017-02 265
2017-03 375
2017-04 446
2017-05 496
2017-06 560
2017-07 609
The desired result would be how many quotes were in an open status during that particular month, not the cumulative :
Year-Month Open_Quote_Count
2017-01 153
2017-02 112
2017-03 110
2017-04 71
Thank you in advance for your help!
Unless I am missing something, LAG() would be a good fit here
Example
Declare #YourTable Table ([Year-Month] varchar(50),[Open_Quote_Count] int)
Insert Into #YourTable Values
('2017-01',153)
,('2017-02',265)
,('2017-03',375)
,('2017-04',446)
,('2017-05',496)
,('2017-06',560)
,('2017-07',609)
Select *
,NewValue = [Open_Quote_Count] - lag([Open_Quote_Count],1,0) over (Order by [Year-Month])
From #YourTable --<< Replace with your initial query
Returns
Year-Month Open_Quote_Count NewValue
2017-01 153 153
2017-02 265 112
2017-03 375 110
2017-04 446 71
2017-05 496 50
2017-06 560 64
2017-07 609 49
How can I arrive at a query for the below scenario?
Data:
Date Product Result Total
15/01/2015 ABC Pass 5
15/01/2015 XYZ Pass 8
15/01/2015 MNO Fail 2
23/01/2015 ABC Pass 10
23/01/2015 XYZ Fail 3
I need the result in the below format:
Date Total Pass Fail
15/01/2015 15 13 2
23/01/2015 13 10 3
Use conditional Aggregate
select Date
sum(Total) Total,
SUM(case when Result ='Pass' then Total else 0 end) Pass,
SUM(case when Result ='Fail' then Total else 0 end) Fail
From yourtable
Group by Date
Try this using PIVOT . FIDDLER DEMO
SELECT Date,
sum(pass) + sum(fail) AS Total,
sum(pass) AS Pass,
sum(fail) AS Fail
FROM TableName
PIVOT (SUM(Total) FOR Result in (pass, fail)) AS P
GROUP BY Date