Can someone help me with this query? I want to get the result of all the customer_id which repeats more than once in 24hrs
SELECT
O.Order_No, O.Customer_ID, O.DateOrdered, O.IPAddress,
C.FirstName, C.LastName, CD.nameoncard
FROM
Order_No O
INNER JOIN
CardData CD ON O.card_id = CD.id
INNER JOIN
Customers C ON O.customer_id = C.customer_id
ORDER BY
O.order_no desc
adding more details..
so suppose order with customer id xx was placed on 04/23 2:30 pm and again 2nd order was placed with same customer Id xx on same day 04/23 5:30 pm.
i want the query to return me customer Id xx
Thanks
select Customer_ID, CAST(DateOrdered as Date) DateOrdered, count(*) QTDE
from Order_No
group by Customer_ID, CAST(DateOrdered as Date)
having count(*) > 1
To get the customers who have orders issued after the first one, then you could use the following query:
select distinct A.Customer_ID
from Order_No A
inner join (select Customer_ID, min(DateOrdered) DateOrdered from Order_No group by Customer_ID ) B
on A.Customer_ID = B.Customer_ID
and A.DateOrdered - B.DateOrdered <= 1
and A.DateOrdered > B.DateOrdered
SQL Fiddle
To get all customers that have ANY TIME more than one order issued in period less or equal than 24h
select distinct A.Customer_ID
from Order_No A
inner join Order_No B
on A.Customer_ID = B.Customer_ID
and A.DateOrdered > B.DateOrdered
and A.DateOrdered - B.DateOrdered <= 1
SQL Fiddle
Self-join:
SELECT distinct O.Customer_ID
FROM
Order_No O
inner join Order_No o2
on o.customerID = o2.customerID
and datediff(hour, o.DateOrdered, o2.DateOrdered) between 0 and 24
and o.Order_No <> o2.Order_No
This will return all customer_IDs that have ever placed more than one order in any 24 hour period.
Edited to add the join criteria that the matching records should not be the same record. Should return customers who placed two different orders at the same time, but not customers who placed only one order.
Related
I have 2 table like this
[Info]
[Score]
I want to select top3 * orderby score in May DESC
the result should be look like this.
Try a JOIN on both tables in a derived table with a SUM on Score and order on that
SELECT TOP 3 *
FROM(
SELECT
I.User_Id, I.[Name], I.Age, Score = SUM(S.Score)
FROM
Info I
INNER JOIN
Score S On S.User_Id = I.User_Id
WHERE MONTH(S.[DATE]) = 5 --May (however I suspect this might not be a DATE object)
GROUP BY
I.User_Id, I.[Name], I.Age
) X
ORDER BY X.Score DESC
Here you go, You can use join statement.
SELECT TOP(3) a.user_id, a.Name, a.Age, b.Score FROM Users a JOIN Score b On a.user_id=b.user_id Order By b.Score desc
The following will be helpfull.
SELECT TOP 3 S.User_Id, SUM(S.Score) Score, U.Name, U.Age
FROM Info U
INNER JOIN Score S ON U.User_Id = S.User_Id
WHERE MONTH(S.Date) = 5 --Only May Month.
GROUP BY S.User_Id, U.Name, U.Age
ORDER BY 2 DESC
i need your help! I got some simple SQL skills, but this query kills me...
My Tables
Now i want the TOP5 WorkTimes on the Equipment (What Equipment got the longest WorkTime).
I want this OUTPUT:
MY Query:
SELECT
Equipment, EquipmentName, count(Equipment) as Count
FROM
Operations o
LEFT JOIN Orders ord ON ord.Id = o.[Order]
LEFT OUTER JOIN Equipments e ON ord.Equipment = e.EquipmentNumber
GROUP BY
Equipment, EquipmentName
ORDER BY Count DESC;
Another Question is how i can show o.Worktime?
i got an error with GroupBy...
please help me Thanks!
You can try this query:
select equip_nr,
(select equipmentname from table_equipments where equipmentnr = [to].equip_nr) equip_name,
sum(timeInMins) / 60.0 Worktime
from (
select (select equipmentnr from table_orders where id = [to].[order]) equip_nr,
case when workunittime = 'RH' then worktime * 60 else worktime end timeInMins
from table_operations [to]
where exists(select 1 from table_orders
where [to].[order] = id
and location = '152')
and [start] >= '2018-07-01 00:00:00.000' and [start] < '2018-08-01 00:00:00.000'
) [to] group by equip_nr
By the way, LEFT JOIN is equivalent to LEFT OUTER JOIN.
Just use SUM(worktime) as aggregate function, instead of COUNT(Equipment)
SELECT
e.[ID_Equipment]
, Name
, SUM( IIF(o.WorkUnitTime='MIN', worktime/60.0, worktime) ) as WorktimeMIN
FROM
Operations o
LEFT JOIN Orders ord ON ord.ID_Order = o.ID_Order
LEFT OUTER JOIN Equipment e ON ord.ID_Equipment = e.ID_Equipment
GROUP BY
e.[ID_Equipment]
, Name
ORDER BY
WorktimeMIN DESC
See SQL Fiddle here: http://sqlfiddle.com/#!18/5b5ed/11
select D.[Date], E.emp_name, E.emp_jde, count(C.[agent_no]) calls, count(S.[EMPJDENUM]) sales
from
(select cast([start_date] as date) dte, [agent_no]
from call_table
where [skill_name] like '%5700 sales l%'
and [Agent_Time] != '0'
) C
full outer join
(select [AC#DTE_dt], [EMPJDENUM]
from sales_table
where [ICGCD2] in ('LAWN', 'HORT')
and [CHANNEL]= 'INQ'
and [ITMQTY]>3
) S on c.dte=s.[AC#DTE_dt]
right join
(select [Date]
from Date_table
) D on c.dte=d.[Date] or s.[AC#DTE_dt]=d.[Date]
right join
(select [emp_name], [emp_jde], [agent_no]
from Employee_table
) E on C.[agent_no]=E.agent_no and S.[EMPJDENUM]=E.emp_jde
group by D.[Date], E.emp_name, E.emp_jde
Date Tables -
Note: Not all dates will have both calls and sales.
Additional Tables -
What needs to be accomplished -
1) Join and Aggregate calls and sales by Employee by joining the calls table (on agent_no) and sales (on JDE) table
2) Since not all dates will include both calls and sales - use the date dimension table to ensure all dates are represented
The desired result would look like this -
The query I wrote executes - it takes so long I just end up canceling the query.
Any help would be appreciated.
Without seeing the query plan, it is a little tricky, but here are a couple of suggestions that might improve the performance:
remove the leading wildcard in where [skill_name] like '5700 sales l%'
put the group by into the subqueries
I have an example here that implements both of those. (Note that I did some reformatting just to try to understand what your query was doing.)
select D.[Date], E.emp_name, E.emp_jde, C.Calls, S.Sales
from Date_table As D
Left Join (
select cast([start_date] as date) As CallDate, [agent_no], Count(*) As Calls
from call_table
where [skill_name] like '5700 sales l%'
and [Agent_Time] != '0'
Group By Cast([start_date] As date), [agent_no]) As C On D.[Date] = C.CallDate
Left Join (
select [AC#DTE_dt] As SaleDate, [EMPJDENUM], Count(*) As Sales
from sales_table
where [ICGCD2] in ('LAWN', 'HORT')
and [CHANNEL]= 'INQ'
and [ITMQTY]>3
Group By [AC#DTE_dt], [EMPJDENUM]) As S on D.[Date] = s.SaleDate
right join Employee_table As E
on C.[agent_no]=E.agent_no
and S.[EMPJDENUM]=E.emp_jde;
Edit
In order to get a row for each possible combination of date and employee, you will need a cross join of the date table and the employee table.
select D.[Date], E.emp_name, E.emp_jde, C.Calls, S.Sales
from Date_table As D,
Employee_table as E
Left Join (
select cast([start_date] as date) As CallDate, [agent_no], Count(*) As Calls
from call_table
where [skill_name] like '5700 sales l%'
and [Agent_Time] != '0'
Group By Cast([start_date] As date), [agent_no]) As C
On D.[Date] = C.CallDate
And E.agent_no = C.agent_no
Left Join (
select [AC#DTE_dt] As SaleDate, [EMPJDENUM], Count(*) As Sales
from sales_table
where [ICGCD2] in ('LAWN', 'HORT')
and [CHANNEL]= 'INQ'
and [ITMQTY]>3
Group By [AC#DTE_dt], [EMPJDENUM]) As S
on D.[Date] = s.SaleDate
and E.emp_jde = S.[EMPJDENUM];
I am having problems grouping by the month of a date when using a function. It was working before but the query was less complicated as I am now using a function that uses a rolling year from the current month. Here is my code.
SELECT
CASE
WHEN DATEDIFF(mm,dbo.fn_firstofmonth(getdate()), dbo.fn_firstofmonth(D.expected_date)) < 12
THEN DATEDIFF(mm,dbo.fn_firstofmonth(getdate()), dbo.fn_firstofmonth(D.expected_date)) + 1
ELSE 13 END AS [Expected Month],
P.probability AS [Category], COUNT(O.id) AS [Customers]
FROM opportunity_probability P
INNER JOIN opportunity_detail D ON D.probability_id = P.id
INNER JOIN opportunities O ON D.opportunity_id = O.id
INNER JOIN
(
SELECT opportunity_id
FROM opportunity_detail
GROUP BY opportunity_id
) T ON T.opportunity_id = O.customer_id
GROUP BY P.probability, MONTH(D.expected_date)
ORDER BY P.probability, MONTH(D.expected_date)
It works if I have D.expected_date in the GROUP BY but I need to group on the MONTH of this date as it does not bring through the data correctly.
You could always remove the group by, then put your entire select into another select, and than group by the outer select:
select t.A, t.B from (select A, datepart(month, b) as B) t group by t.A, t.B
This way you can address your month field as if it where a normal field.
Example is far from complete, but should get you on your way.
You can try to find month by this code:
GROUP BY P.probability, DATEPART(month, D.expected_date)
try this
SELECT
to_char(D.expected_date, 'YYYY-MM'),
CASE
WHEN DATEDIFF(mm,dbo.fn_firstofmonth(getdate()), dbo.fn_firstofmonth(D.expected_date)) < 12
THEN DATEDIFF(mm,dbo.fn_firstofmonth(getdate()), dbo.fn_firstofmonth(D.expected_date)) + 1
ELSE 13 END AS [Expected Month],
P.probability AS [Category], COUNT(O.id) AS [Customers]
FROM opportunity_probability P
INNER JOIN opportunity_detail D ON D.probability_id = P.id
INNER JOIN opportunities O ON D.opportunity_id = O.id
INNER JOIN
(
SELECT opportunity_id
FROM opportunity_detail
GROUP BY opportunity_id
) T ON T.opportunity_id = O.customer_id
GROUP BY P.probability, to_char(D.expected_date, 'YYYY-MM')
ORDER BY P.probability, to_char(D.expected_date, 'YYYY-MM')
I was trying to write a query for the SQL Server sample DB Northwind. The question was: "Show the most recent five orders that were purchased by a customer who has spent more than $25,000 with Northwind."
In my query the Alias name - "Amount" is not being recognized. My query is as follows:
select top(5) a.customerid, sum(b.unitprice*b.quantity) as "Amount", max(c.orderdate) as Orderdate
from customers a join orders c
on a.customerid = c.customerid
join [order details] b
on c.orderid = b.orderid
group by a.customerid
--having Amount > 25000 --throws error
having sum(b.unitprice*b.quantity) > 25000 --works, but I don't think that this is a good solution
order by Orderdate desc
Pls let me know what I am doing wrong here, as I am a newbie in writing T Sql. Also can this query and my logic be treated as production level query?
TIA,
You must use the aggregate in the query you have. This all has to do with the order in which a SELECT statement is executed. The syntax of the SELECT statement is as follows:
SELECT
FROM
WHERE
GROUP BY
HAVING
ORDER BY
The order in which a SELECT statement is executed is as follows. Since the SELECT clause isn't executed until after the HAVING clause, you can't use the alias like you can in the ORDER BY clause.
FROM
WHERE
GROUP BY
HAVING
SELECT
ORDER BY
Reference Article: http://www.bennadel.com/blog/70-sql-query-order-of-operations.htm
This is a known limitation in SQL Server, at least, but no idea if it's a bug, intentional or even part of the standard. But the thing is, neither the WHERE or HAVING clauses accept an alias as part of their conditions, you must use only columns from the original source tables, which means that for filtering by calculated expressions, you must copy-paste the very same thing in both the SELECT and WHERE parts.
A workaround for avoiding this duplication can be to use a subquery or cte and apply the filter on the outer query, when the alias is just an "input" table:
WITH TopOrders AS (
select a.customerid, sum(b.unitprice*b.quantity) as "Amount", max(c.orderdate) as Orderdate
from customers a join orders c
on a.customerid = c.customerid
join [order details] b
on c.orderid = b.orderid
group by a.customerid
--no filter here
order by Orderdate desc
)
SELECT TOP(5) * FROM TopOrders WHERE Amount > 25000 ;
Interesting enough, the ORDER BY clause does accepts aliases directly.
You must use Where b.unitprice*b.quantity > 25000 instead of having Amount > 25000.
Having used for aggregate conditions. Your business determine your query condition. If you need to calculate sum of prices that have above value than 25000, must be use Where b.unitprice*b.quantity > 25000 and if you need to show customer that have total price above than 25000 must be use having Amount > 25000 in your query.
select top(5) a.customerid, sum(b.unitprice*b.quantity) as Amount, max(c.orderdate) as Orderdate
from customers a
JOIN orders c ON a.customerid = c.customerid
join [order details] b ON c.orderid = b.orderid
group by a.customerid
having sum(b.unitprice*b.quantity) > 25000 --works, but I don't think that this is a good solution
Order by Amount
I don't have that schema at hand, so table' and column' names might go a little astray, but the principle is the same:
select top (5) ord2.*
from (
select top (1) ord.CustomerId
from dbo.Orders ord
inner join dbo.[Order Details] od on od.OrderId = ord.OrderId
group by ord.CustomerId
having sum(od.unitPrice * od.Quantity) > $25000
) sq
inner join dbo.Orders ord2 on ord2.CustomerId = sq.CustomerId
order by ord2.OrderDate desc;
The Having Clause will works with aggregate function like SUM,MAX,AVG..
You may try like this
SELECT TOP 5 customerid,SUM(Amount)Amount , MAX(Orderdate) Orderdate
FROM
(
SELECT A.customerid, (B.unitprice * B.quantity) As "Amount", C.orderdate As Orderdate
FROM customers A JOIN orders C ON A.customerid = C.customerid
JOIN [order details] B ON C.orderid = B.orderid
) Tmp
GROUP BY customerid
HAVING SUM(Amount) > 25000
ORDER BY Orderdate DESC
The question is little ambiguos.
Show the most recent five orders that were purchased by a customer who
has spent more than $25,000 with Northwind.
Is it asking to show the 5 recent orders by all the customers who have spent more than $25,000 in all of their transactions (which can be more than 5).
The following query shows all the customers who spent $25000 in all of their transactions (not just the recent 5).
In one of the Subquery BigSpenders it gets all the Customers who spent more than $25000.
Another Subquery calculates the total amount for each order.
Then it gets rank of all the orders by OrderDate and OrderID.
Then it filters it by Top 5 orders for each customer.
--
SELECT *
FROM (SELECT C.customerid,
C.orderdate,
C.orderid,
B3.amount,
Row_number()
OVER(
partition BY C.customerid
ORDER BY C.orderdate DESC, C.orderid DESC) Rank
FROM orders C
JOIN
--Get Amount Spend Per Order
(SELECT b2.orderid,
Sum(b2.unitprice * b2.quantity) AS Amount
FROM [order details] b2
GROUP BY b2.orderid) B3
ON C.orderid = B3.orderid
JOIN
--Get Customers who spent more than 25000
(SELECT c.customerid
FROM orders c
JOIN [order details] b
ON c.orderid = b.orderid
GROUP BY c.customerid
HAVING Sum(b.unitprice * b.quantity) > 25000) BigSpenders
ON C.customerid = BigSpenders.customerid) X
WHERE X.rank <= 5