I'm trying to find any customers with a total of at least 4 accounts with at least 1 account that has been open in the last 6 months.
So far I'm able to get the customer and total accounts, but I'm not sure how to add a column for the number of new accounts open in the last 6 months.
SELECT CustomerID
,COUNT(AccountID) as 'Total Accounts'
FROM Customer
GROUP BY CustomerID
HAVING COUNT(AccountID) >= 3`
Here are my tables:
and
And here is what my final result should look like. so far I have CustomerID and Total Accounts.
CustomerID | Total Accounts | New Accounts |
-----------+----------------+------------- +
Ben | 3 | 1 |
EDIT: The program I'll be importing this query in doesn't allow case statements.
You can left join the new accounts. Include the filter for startdate in the join condition. For accounts, that don't satisfy that condition no record from account is joined. So the account ID is null for them and won't get counted.
SELECT c.customerid,
count(c.accountid) "Total Accounts",
count(a.accountid) "New Accounts"
FROM customer c
LEFT JOIN account a
ON a.accountid = c.accountid
AND a.startdate >= dateadd(month, -6, getdate())
GROUP BY c.customerid
HAVING count(c.accountid) >= 4
AND count(a.accountid) >= 1;
Count, like most aggregate functions, ignores nulls. I'd use this property by joining the two tables and using a case expression to return only the new accounts:
SELECT CustomerId,
COUNT(*) AS TotalAccounts,
COUNT(CASE WHEN DATEDIFF(MONTH, StartDate, GETDATE()) <= 6 THEN 1 END)
AS NewAccounts
FROM Customer c
JOIN Accounts a ON c.AccountId = a.AccountId
GROUP BY CustomerId
HAVING COUNT(*) >= 4 AND
COUNT(CASE WHEN DATEDIFF(MONTH, StartDate, GETDATE()) <= 6 THEN 1 END) > 0
This query will give you the total account count and the number that is new.
SELECT C.CustomerID,
COUNT(C.AccountID) as Total_Acc,
SUM(CASE WHEN DATEADD(MONTH,-6,GETDATE()) <= A.StarDate) THEN 1 ELSE 0 END) as New_Acct
FROM Customer C
LEFT JOIN Account A ON C.AccountID = A.AccountID
GROUP BY CustomerID
You can then use that in a sub-query to find what you want
eg
SELECT *
FROM (
SELECT C.CustomerID,
COUNT(C.AccountID) as Total_Acc,
SUM(CASE WHEN DATEADD(MONTH,-6,GETDATE()) <= A.StarDate) THEN 1 ELSE 0 END) as New_Acct
FROM Customer C
LEFT JOIN Account A ON C.AccountID = A.AccountID
GROUP BY CustomerID
) SUB
WHERE Total_Acc >= 4 and New_Acct >= 1
The program I'll be importing this query in doesn't allow case
statements.
For your stated goal of finding customers with at least 4 accounts and at least 1 account that has been opened in the last 6 months you don't need the count of recent accounts anyway. It is sufficient to get the latest account date opened and see if that was in the last 6 months.
SELECT c.CustomerId
FROM Customer c
JOIN Accounts a
ON c.AccountId = a.AccountId
GROUP BY c.CustomerId
HAVING COUNT(*) >= 4
AND MAX(a.StartDate) >= DATEADD(MONTH, -6, GETDATE())
Related
I have two tables – activity and purchase
Activity table:
user_id date videos_watched
1 2020-01-02 3
1 2020-01-04 5
1 2020-01-07 5
Purchase table:
user_id purchase_date
1 2020-01-01
2 2020-02-02
What I would like to do is to get a 30 day rolling average since purchase on how many videos has been watched.
The base query is like this:
SELECT
DATEDIFF(DAY, p.purchase_date, a.date) AS day_since_purchase,
AVG(A.VIDEOS_VIEWED)
FROM PURCHASE P
LEFT OUTER JOIN ACTIVITY A ON P.USER_ID = A.USER_ID AND
A.DATE >= P.PURCHASE_DATE AND A.DATE <= DATEADD(DAY, 30, P.PURCHASE_DATE)
GROUP BY 1;
However, the Activity table only has records for each day a video has been logged. I would like to fill in the blanks for days a video has not been viewed.
I have started to look into using a CTE like this:
WITH cte AS (
SELECT date('2020-01-01') as fdate
UNION ALL
SELECT CAST(DATEADD(day,1,fdate) as date)
FROM cte
WHERE fdate < date('2020-04-01')
) select * from cte
cross join purchases p
left outer join activity a
on p.user id = a.user_id
and a.fdate = p.purchase_date
and a.date >= p.purchase_date and a.date <= dateadd(day, 30, p.purchase_date)
The end goal is to have something like this:
days_since_purchase videos_watched
1 3
2 0 --CTE coalesce inserted value
3 0
4 5
Been trying for the last couple of hours to get it right, but still can't really get the hang of it.
If you want to fill in the gaps in the result set, then I think you should be generating integers rather than dates:
WITH cte AS (
SELECT 1 as day_since_purchase
UNION ALL
SELECT 1 + day_since_purchase
FROM cte
WHERE day_since_purchase < 4
)
SELECT cte.day_since_purchase, COALESCE(avg_videos_viewed, 0)
FROM cte LEFT JOIN
(SELECT DATEDIFF(DAY, p.purchase_date, a.date) AS day_since_purchase,
AVG(A.VIDEOS_VIEWED) as avg_videos_viewed
FROM purchases p JOIN
activity a
ON p.user id = a.user_id AND
a.fdate = p.purchase_date AND
a.date >= p.purchase_date AND
a.date <= dateadd(day, 30, p.purchase_date)
GROUP BY 1
) pa
ON pa.day_since_purchase = cte.day_since_purchase;
You can use a recursive query to generate the 30 days following each purchase, then bring the activity table:
with cte as (
select
purchase_date,
client_id,
0 days_since_purchase,
purchase_date dt
from purchases
union all
select
purchase_date,
client_id,
days_since_purchase + 1
dateadd(day, days_since_purchase + 1, purchase_date)
from cte
where days_since_purchase < 30
)
select
c.days_since_purchase,
avg(colaesce(a. videos_watch, 0)) avg_ videos_watch
from cte c
left join activity a
on a.client_id = c.client_id
and a.fdate = c.purchase_date
and a.date = c.dt
group by c.days_since_purchase
Your question is unclear on whether you have a column in the activity table that stores the purchase date each row relates to. Your query has column fdate but not your sample data. I used that column in the query (without such column, you might end up counting the same activity in different purchases).
I am trying to write a query that returns:
The total amount of transactions that occurred before a date range, for a particular customer.
The total amount of transactions that occurred within a date range, for a particular customer.
The total amount of payments that occurred before a date range, for a particular customer.
The total amount of payments that occurred within a date range, for a particular customer.
To that end, I've come up with the following query.
declare #StartDate DATE = '2016-08-01'
declare #EndDate DATE = '2016-08-31'
declare #BillingCategory INT = 0
select c.Id, c.Name, c.StartingBalance,
(select coalesce(sum(Amount), 0) from Transactions t where t.CustomerId = c.Id and t.[Date] < #StartDate) xDebits,
(select coalesce(sum(Amount), 0) from Transactions t where t.CustomerId = c.Id and t.[Date] >= #StartDate and t.[Data] <= #EndDate) Debits,
(select coalesce(sum(Amount), 0) from Payments p where p.CustomerId = c.Id and p.[Date] < #StartDate) xCredits,
(select coalesce(sum(Amount), 0) from Payments p where p.CustomerId = c.Id and p.[Date] >= #StartDate and p.[Date] <= #EndDate) Credits
from customers c
where c.BillingCategory in (0,1,2,3,4,5)
This query seems to give the results I want. I used the subqueries because I couldn't seem to figure out how to accomplish the same thing using JOINs. But I have a few questions.
Does this query retrieve the transaction and payment data for every single customer before filtering it according to my WHERE condition? If so, that seems like a big waste. Can that be improved?
I'd also like to add a GROUP BY to total each payment and transaction column by BillingCategory. But how can you add a GROUP BY clause here when the SELECTed columns are limited to aggregate functions if they are not in the GROUP BY clause?
The Transactions and Payments tables both have foreign keys to the Customers table.
Sample data (not real)
Customers:
Id Name BillingCategory
----- ------- ---------------
1 'ABC' 0
2 'DEF' 1
3 'GHI' 0
Transactions:
Id CustomerId Date Amount
----- ---------- ------------ ------
1 2 '2016-08-01' 124.90
2 2 '2016-08-04' 37.23
3 1 '2016-08-27' 450.02
Payments:
Id CustomerId Date Amount
----- ---------- ------------ ------
1 1 '2016-09-01' 50.00
2 1 '2016-09-23' 75.00
3 2 '2016-09-01' 100.00
You could build your sums seperately for Transactions and Payments in a CTE and then join them together:
WITH
CustomerTransactions AS
(
SELECT CustomerId,
SUM(CASE WHEN [Date] < #StartDate THEN 1 ELSE 0 END * COALESCE(Amount, 0)) AS xDebits,
SUM(CASE WHEN [Date] >= #StartDate THEN 1 ELSE 0 END * COALESCE(Amount, 0)) AS Debits
FROM Transactions
GROUP BY CustomerId
),
CustomerPayments AS,
(
SELECT CustomerId,
SUM(CASE WHEN [Date] < #StartDate THEN 1 ELSE 0 END * COALESCE(Amount, 0)) AS xCredits,
SUM(CASE WHEN [Date] >= #StartDate THEN 1 ELSE 0 END * COALESCE(Amount, 0)) AS Credits
FROM Payments
GROUP BY CustomerId
)
SELECT C.Id, c.Name, c.StartingBalance,
COALESCE(T.xDebits, 0) AS xDebits,
COALESCE(T.Debits, 0) AS Debits,
COALESCE(P.xCredits, 0) AS xCredits,
COALESCE(P.Credits, 0) AS Credits
FROM Custormers C
LEFT OUTER JOIN CustomerTransactions T ON T.CustomerId = C.Id
LEFT OUTER JOIN CustomerPayments P ON P.CustomerId = C.Id
WHERE C.BillingCategory IN(0, 1, 2, 3, 4, 5);
You can do with sub-queries to be more efficient. Pre-query grouped by each customer for only those customers who qualify by the categories in question. These sub-queries will always result in an at-most, 1 record per customer so you don't get a Cartesian result. Get that for your debits and credits and re-join back to your master list of customers with a left-join in case one side or the other (debits/credits) may not exist.
declare #StartDate DATE = '2016-08-01'
declare #EndDate DATE = '2016-08-31'
declare #BillingCategory INT = 0
select
c.ID,
c.Name,
c.StartingBalance,
coalesce( AllDebits.xDebits, 0 ) DebitsPrior,
coalesce( AllDebits.Debits, 0 ) Debits
coalesce( AllCredits.xCredits, 0 ) CreditsPrior,
coalesce( AllCredits.Credits, 0 ) Credits
from
customers c
LEFT JOIN
( select t.CustomerID,
sum( case when t.[Date] < #StartDate then Amount else 0 end ) xDebits,
sum( case when t.[Date] >= #StartDate then Amount else 0 end ) Debits
from
customers c1
JOIN Transactions t
on c1.CustomerID = t.CustomerID
where
c1.BillingCategory in (0,1,2,3,4,5)
group by
t.CustomerID ) AllDebits
on c.CustomerID = AllDebits.CustomerID
LEFT JOIN
( select p.CustomerID,
sum( case when p.[Date] < #StartDate then Amount else 0 end ) xCredits,
sum( case when p.[Date] >= #StartDate then Amount else 0 end ) Credits
from
customers c1
JOIN Payments p
on c1.CustomerID = p.CustomerID
where
c1.BillingCategory in (0,1,2,3,4,5)
group by
p.CustomerID ) AllCredits
on c.CustomerID = AllCredits.CustomerID
where
c.BillingCategory in (0,1,2,3,4,5)
COMMENT ADDITION
With respect to Thomas's answer, yes they are close. My version also adds the join to the customer table for the specific billing category and here is why. I don't know the size of your database, how many customers, how many transactions. If you are dealing with a large amount that DOES have performance impact, Thomas's version is querying EVERY customer and EVERY transaction. My version is only querying the qualified customers by the billing category criteria you limited.
Again, not knowing data size, if you are dealing with 100k records may be no noticeable performance. If you are dealing with 100k CUSTOMERS, could be a totally different story.
#JonathanWood, correct, but my version has each internal subquery inclusive of the cus
Below is my table schema:- Appointments
--------------------------------------
| schID | appointment_date | amount | location |
--------------------------------------
I want to fire a single query where I can get the sum of amount, total appointment_date this year i.e 2016 and remaining appointment_date this year i.e 2016.
So I wrote the below query to calculate the above fields:-
SELECT sum(a.amount) as total,
count(distinct a.appointment_date) as total_appointment,
count(distinct a2.appointment_date) as remaining appointments
from Appointments a
LEFT JOIN Appointments a2 ON a.schID = a2.schID
WHERE a2.appointment_date > GETDATE() AND year(a.appointment_date) = 2016
group by a.location
The above query doesnt return value as per requirement :(
The database belongs to SQL Server.
You can use conditional aggregation for this:
SELECT sum(amount) as total,
count(appointment_date) as total_appointment,
count(DISTINCT CASE
WHEN appointment_date > GETDATE() AND YEAR(appointment_date) = 2016
THEN DATE(appointment_date)
END) as remaining appointments
from Appointments a
group by a.location
You shouldn't need a join for this type of query:
SELECT sum(a.amount) as total, count(a.appointment_date) as total_appointment,
sum(case when a.appointment_date > getdate() then 1 else 0
end) as remaining appointments
from Appointments a
where year(a.appointment_date) = year(GETDATE() );
If you need the breakdown by location, then include location in both the select and group by clauses.
I am currently working on aggregating the sum qty of "OUT" and "OUT+IN".
Current query is the following:
Select
a.Date
,a.DepartmentID
from
(Select
dris.Date
,dris.RentalItemKey
,dris.WarehouseKey
,ISNULL((Select TOP 1 dris.Date where OutQty=1 order by Date DESC),(Select ri.ReceiveDate from RentalItem ri where ri.RentalItemKey=dris.RentalItemKey)) as LastOutDate
,(Select d.DepartmentKey from Department d where d.Department=i.Department)as DepartmentID
, (CASE WHEN OutQty=1 OR (RepairQty=1 AND RentedQty=1) THEN 'IN' ELSE 'OUT' END) as Status
from DailyRentalItemStatus dris
inner join Inventory i on i.InventoryKey=dris.InventoryKey
where dris.Date='2014-08-02'
and i.ICode='3223700'
and i.Classification IN ('ITEM', 'ACCESSORY')
and i.AvailFor='RENT'
and i.AvailFrom='WAREHOUSE'
and dris.Warehouse='TORONTO')a
and I would like the result to be the following:
Date WarehouseID DepartmentID ICode Owned NotRedundant Out
2014-08-02 001T A00G 3223700 30 30 19
Where Owned is is The items with status as "OUT+IN", out is "OUT" and Not Redundant as where the lastout date is within the last 2 years from the date.
Help would be greatly appreciated.
I think this is close to what you're looking for. Your Not Redundant description, is hard to understand. Which dates are you comparing. The same trick for OUT may be used for that though.
My query also assumes that you always have a department connecting to the inventory table and that there's always a rentalitem.receivedate.
;WITH LastOut as
(Select Max(Date) as LastOutDate, rentalItemKey
from DailyRentalItemStatus
WHERE OutQty=1
)
Select
dris.Date
,dris.WarehouseKey as WarehouseID
,d.DepartmentKey as DepartmentID
, i.Icode
--,ISNULL((Select TOP 1 dris.Date where OutQty=1 order by Date DESC),(Select ri.ReceiveDate from RentalItem ri where ri.RentalItemKey=dris.RentalItemKey)) as LastOutDate
, Count(1) as Owned
, Sum(CASE WHEN NOT (OutQty=1 OR (RepairQty=1 AND RentedQty=1)) THEN 1 ELSE 0 END) as OUT
, Sum(CASE WHEN DateAdd(yy, 2,dris.[date]) >= ISNULL(lastout.lastoutdate, ri.ReceiveDate) then 1 else 0 end) as NonRedundent
from DailyRentalItemStatus dris
inner join Inventory i on i.InventoryKey=dris.InventoryKey
INNER JOIN Department d ON d.Department=i.Department
INNER JOIN RentalItem ri ON ri.RentalItemKey=dris.RentalItemKey
LEFT OUTER JOIN LastOUT ON LastOut.rentalItemKey=dris.RentalItemKey
where dris.Date='2014-08-02'
and i.ICode='3223700'
and i.Classification IN ('ITEM', 'ACCESSORY')
and i.AvailFor='RENT'
and i.AvailFrom='WAREHOUSE'
and dris.Warehouse='TORONTO'
Group BY dris.Date, d.DepartmentKey, Dris.WarehouseKey , i.icode
I am trying to count the number of users who have had at least two sessions within 7 days of OR ten in 30 days of all dates.
My data is as follow:
Date UserID SessionID
1/1/2013 Bob1234 1
2/1/2013 Bob1234 2
2/2/2013 Bob1234 3
2/3/2013 Cal5678 4
Which would result in the following table (only select dates shown)
Date CountActiveUsers
1/1/2013 1
1/15/2013 0
2/2/2013 1
2/3/2013 2
The real data set has values for all dates in a continuous data range and the results table should have an entry for every date.
SessionIDs are unique and a UserID always refers to the same person.
So far I have two queries that do something close-ish. The first returns the count of sessions in the past week by user:
SELECT Count(
d.[SessionID]
) As SessionPastWeek
,m.[UserID]
,m.[Date]
FROM [Cosmos].[dbo].[Sessions_tbl] as m
Inner Join [Cosmos].[dbo].[Sessions_tbl] as d
on m.[UserID2] = d.[UserID] AND
--Between does not work here for some reason
d.[Date] <= m.[Date] AND
d.[Date] > DATEADD(d,-7,m.[date])
Group By m.[UserID]
,m.[Date]
The other is from the following link which count the number of active users in a given date
Active Users SQL query
I am in SQL Server 2012
I am having trouble combining the two.
Edit for clarification: the query I need likely won't have any getdate() or similar as I need to know how many users fit the 'active' criteria on Jan 1, today, and all the dates inbetween.
Thanks for any help!
I think you just need to add a HAVING clause:
HAVING COUNT(d.[SessionID]) >= 2
On your 10 in 30 query, just change your DATEADD() to have 30 days, and change the HAVING clause to be >= 10.
SELECT COUNT(d.[SessionID]) AS SessionPastPeriod
, m.[UserID]
, m.[Date]
FROM Sessions_tbl AS m
INNER JOIN Sessions_tbl as d
ON m.UserID = d.UserID
AND d.[Date] <= m.[Date]
AND d.[Date] > DATEADD(d,-7,m.[Date])
GROUP BY m.UserID
, m.[Date]
HAVING COUNT(d.[SessionID]) >= 2
I hope this helps.
You are too close.
SELECT Count(d.[SessionID]) As SessionPastWeek
,m.[UserID]
,m.[Date]
FROM [Cosmos].[dbo].[Sessions_tbl] as m
Inner Join [Cosmos].[dbo].[Sessions_tbl] as d on m.[UserID2] = d.[UserID]
--Between does not work here for some reason
where --ADD where clause
d.[Date] <= getdate() AND
d.[Date] > DATEADD(d,-7,getdate())
Group By m.[UserID],m.[Date]
having Count(d.[SessionID])>1 --The magical clause for you.
select count(*)
from (
select UserID
, sum(case when Date between dateadd(day, -7, getdate()) and getdate()
then 1 end) as LastWeek
, sum(case when Date between dateadd(day, -30, getdate()) and getdate()
then 1 end) as Last30Days
from Sessions_tbl
group by
UserID
) SubQueryAlias
where LastWeek >= 2
or Last30Days >= 10
The following query works:
Select
Count(UserID) As CountUsers
,[Date]
From(
SELECT COUNT(d.[SessionID]) AS SessionPastPeriod
, m.[Date]
, m.UserID
FROM [Sessions_tbl] AS m
INNER JOIN [Sessions_tbl] as d
ON m.UserID = d.UserID
AND d.[Date] <= m.[Date]
AND d.[Date] > DATEADD(d,-7,m.[Date])
GROUP BY
m.UserID
,m.[Date]
HAVING COUNT(d.[SessionID]) >= 2) SQ
Group By [Date]