I have this query:
SELECT
COUNT(Request.ID) AS count,
ClaimHandlingStatusID AS statusId
FROM
Request
GROUP BY
ClaimHandlingStatusID
ORDER BY
ClaimHandlingStatusID
which returns a result like this:
count statusId
-----------------
5 -1
5 1
2321 5
27008 6
95288 8
However, I would like to only show the most recent top 500 of request.ID (the Request table has a createddate column). So that the query will only show the top 500 RequestId, and thereafter show how many of these 500 have the different statusId.
Here are some queries I have tried (that do not work):
SELECT COUNT(Request.ID) AS count, ClaimHandlingStatusID AS statusId
FROM Request
WHERE Request.ID = (SELECT TOP 500 (ID) FROM Request
ORDER BY CreatedDate desc)
GROUP BY ClaimHandlingStatusID
ORDER BY ClaimHandlingStatusID
SELECT TOP 500
ID, COUNT(*) Total,
ClaimHandlingStatusID AS statusId
FROM Request
GROUP BY ClaimHandlingStatusID
ORDER BY ClaimHandlingStatusID
Desired outcome would be something like:
count statusId
------------------
50 -1
50 1
100 5
150 6
150 8
Thanks for any help!
We can use SUM() as an analytic function to find the total rolling count, then restrict to only records whose total is less than or equal to 500:
WITH cte AS (
SELECT COUNT(*) AS count, ClaimHandlingStatusID AS statusId,
SUM(count) OVER (ORDER BY ClaimHandlingStatusID) AS total
FROM Request
GROUP BY ClaimHandlingStatusID
)
SELECT count, statusId
FROM cte
WHERE total <= 500
ORDER BY statusId;
Related
Currently I'm doing this:
select
ProductID = ProductID = ROW_NUMBER() OVER (PARTITION BY PRODUCTID ORDER BY PRODUCtID),
TransactionDate,
TransactionAmount
from ProductsSales
order by ProductID
The results are like this:
ProductID
TransactionDate
TransactionAmount
1
2022-11-06
30
2
2022-11-12
30
3
2022-11-28
30
2
2022-11-03
10
3
2022-11-10
10
4
2022-11-15
10
3
2022-11-02
50
The duplicated IDs are being inserted sequential, but what I need it to be like this:
ProductID
TransactionDate
TransactionAmount
1
2022-11-06
30
1.1
2022-11-12
30
1.2
2022-11-28
30
2
2022-11-03
10
2.1
2022-11-10
10
2.2
2022-11-15
10
3
2022-11-02
50
Is this possible?
Assuming your PRODUCTID field is numeric already, then this should work:
WITH _ProductIdSorted AS
(
SELECT
CONCAT
(
PRODUCTID,
'.',
ROW_NUMBER() OVER (PARTITION BY PRODUCTID ORDER BY TransactionDate) - 1
) AS ProductId,
TransactionDate,
TransactionAmount
FROM ProductsSales
)
SELECT
REPLACE(ProductId, '.0', '') AS ProductId,
TransactionDate,
TransactionAmount
FROM _ProductIdSorted;
By the way, just the same as the ORDER BY clause in your query, the one my answer uses is a nondeterminsitic sort. It seems, based on your Post, it doesn't matter to you the order which the rows are sorted within the partition though.
In Snowflake I have this original query which, for a given consumer_ID, produces a list of unique store IDs.
SELECT
t.consumer_id
, t.business_id
, t.store_id
, t.campaign_id
FROM campaigns_mini AS t
QUALIFY ROW_NUMBER() OVER (PARTITION BY t.consumer_id, t.store_id ORDER BY t.campaign_id) = 1
The original purpose was to provide a list that does not duplicate store_id for a given consumer_id. Suppose now I also need to ensure this list does not duplicate business_id as well for a given consumer_ID. Is there an easy way to modify the above?
SELECT
t.consumer_id
, t.business_id
, t.store_id
, t.campaign_id
FROM campaigns_mini AS t
QUALIFY ROW_NUMBER() OVER
(PARTITION BY t.consumer_id
,t.store_id
,t.business_id
ORDER BY t.campaign_id) = 1
The partition by clause forms windows by the combination of all the expressions in the clause.
This will deduplicate by the combination of consumer_id, store_id, and business_id. If this is not what you need, please update with sample input and output to clarify.
So if I make up some data:
WITH campaigns_mini(consumer_id, business_id, store_id, campaign_id) as (
select * from values
(1,10,100,1000),
(1,10,100,1001),
(1,10,101,1002),
(2,20,200,2000)
)
and use your exist SQL
SELECT
t.consumer_id
,t.business_id
,t.store_id
,t.campaign_id
FROM campaigns_mini AS t
QUALIFY ROW_NUMBER() OVER (PARTITION BY t.consumer_id, t.store_id ORDER BY t.campaign_id) = 1
I get
CONSUMER_ID
BUSINESS_ID
STORE_ID
CAMPAIGN_ID
1
10
101
1002
1
10
100
1000
2
20
200
2000
we get the Store not repeated for the Consumer, but as you note you don't want the business repeated ether..
If we change to using business_id instead of store_id we see we get less rows:
SELECT
t.consumer_id
,t.business_id
,t.store_id
,t.campaign_id
FROM campaigns_mini AS t
QUALIFY ROW_NUMBER() OVER (PARTITION BY t.consumer_id, t.business_id ORDER BY t.campaign_id) = 1
ORDER BY 1;
CONSUMER_ID
BUSINESS_ID
STORE_ID
CAMPAIGN_ID
1
10
100
1000
2
20
200
2000
So if we want "no repeating business_id AND no repeating stores" using the Qualify Greg's has proposed will not help, as we are keeping the first for the distinct set of consumer,business, & store:
QUALIFY ROW_NUMBER() OVER (PARTITION BY t.consumer_id, t.business_id, t.store_id ORDER BY t.campaign_id) = 1
which gives:
CONSUMER_ID |BUSINESS_ID |STORE_ID |CAMPAIGN_ID
1 |10 |100 |1000
1 |10 |101 |1002
2 |20 |200 |2000
So the next thing is to think why not keep the only the first of the two sets:
QUALIFY ROW_NUMBER() OVER (PARTITION BY t.consumer_id, t.store_id ORDER BY t.campaign_id) = 1
AND ROW_NUMBER() OVER (PARTITION BY t.consumer_id, t.business_id ORDER BY t.campaign_id) = 1
which for this data works!
CONSUMER_ID
BUSINESS_ID
STORE_ID
CAMPAIGN_ID
1
10
100
1000
2
20
200
2000
but then for this data:
WITH campaigns_mini(consumer_id, business_id, store_id, campaign_id) as (
select * from values
(1,10,100,1000),
(1,10,101,1001),
(1,20,101,1002)
)
there is only one row with business 20, for store 101, but the first 101 store is on campaign 1001, so both those rows are discarded.
CONSUMER_ID
BUSINESS_ID
STORE_ID
CAMPAIGN_ID
1
10
100
1000
So if we use two layers to do the prune, for this data:
select * from (
SELECT
t.consumer_id
,t.business_id
,t.store_id
,t.campaign_id
FROM campaigns_mini AS t
QUALIFY ROW_NUMBER() OVER (PARTITION BY t.consumer_id, t.business_id ORDER BY t.campaign_id) = 1
)
QUALIFY ROW_NUMBER() OVER (PARTITION BY consumer_id, store_id ORDER BY campaign_id) = 1
works:
CONSUMER_ID
BUSINESS_ID
STORE_ID
CAMPAIGN_ID
1
10
100
1000
1
20
101
1002
but if your flip those orders of QUALIFY you are back to just one row..
so as a general problem it cannot be safely solve for all data cases with this pattern...
I have a table that contains Transactions of Customers.
I should Find Customers That had have at least 2 transaction with amount>20000 in Three consecutive days each month.
For example , Today is 2022/03/12 , I should Gather Data Of Transactions From 2022/02/13 To 2022/03/12, Then check These Data and See If a Customer had at least 2 Transaction With Amount>=20000 in Three consecutive days.
For Example, Consider Below Table:
Id
CustomerId
Transactiondate
Amount
1
1
2022-01-01
50000
2
2
2022_02_01
20000
3
3
2022_03_05
30000
4
3
2022_03_07
40000
5
2
2022_03_07
20000
6
4
2022_03_07
30000
7
4
2022_03_07
30000
The Out Put Should be : CustomerId =3 and CustomerId=4
I write query that Find Customer For Special day , but i don't know how to find these customers in one month with out using loop.
the query for special day is:
With cte (select customerid, amount, TransactionDate,Dateadd(day,-2,TransactionDate) as PrevDate
From Transaction
Where TransactionDate=2022-03-12)
Select CustomerId,Count(*)
From Cte
Where
TransactionDate>=Prevdate and TransactionDate<=TransactionDate
And Amount>=20000
Group By CustomerId
Having count(*)>=2
Hi there are many options how to achieve this.
I think that easies (from perfomance maybe not) is using LAG function:
WITH lagged_days AS (
SELECT
ISNULL(LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
,*
FROM Transaction
), valid_cust_base as (
SELECT
*
FROM lagged_days
WHERE DATEPART(MONTH, lagged) = DATEPART(MONTH, Transactiondate)
AND datediff(day, Transactiondate, lagged_dt) <= 3
AND Amount >= 20000
)
SELECT
CustomerID
FROM valid_cust_base
GROUP BY CustomerID
HAVING COUNT(*) >= 2
First I have created lagged TransactionDate over customer (I assume that id is incremental). Then I have Selected only transactions within one month, with amount >= 20000 and where date difference between transaction is less then 4 days. Then just select customers who had more than 1 transaction.
In LAG First value is always missing per Customer missing, but you still need to be able say: 1st and 2nd transaction are within 3 days. Thats why I am replacing first NULL value with LEAD. It doesn't matter if you use:
ISNULL(LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
OR
ISNULL(LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
The main goal is to have for each transaction closest TransactionDate.
Company_Name Amount Cumulative Total
---------------------------------------------
Company 6 100 100
Company 6 200 300
Company 6 150 450
Company 7 700 700
Company 7 1100 1800
Company 7 500 2300
How can I do cumulative sum group by company as shown in this example?
First, you need a column that specifies the ordering, because SQL tables represent unordered sets. Let me assume you have such a column.
Then the function is sum() as a window function:
select t.*,
sum(amount) over (partition by company order by <ordering col>)
from t;
Note: This does not return 0 for the "first" row for each company, so it really is a cumulative sum. For your logic, you need an additional conditional:
select t.*,
(case when row_number() over (partition by company order by <ordering col>) = 1
then 0
else sum(amount) over (partition by company order by <ordering col>)
end)
from t;
I'm trying to calculate the Bounce Rate of pages in SQL Server in a table with Audit Data from Sharepoint.
ItemId UserId DocLocation Occurred
1 1 Home.aspx 2016-08-02 13:39:41
1 2 Home.aspx 2016-08-02 13:40:07
2 1 Other.aspx 2016-08-02 13:40:16
3 1 Items.aspx 2016-08-02 13:40:17
2 2 Other.aspx 2016-08-02 13:40:11
ItemId is the id of the page, DocLocation the location of the page and Occurred when the user goes into the page.
To calculate the bounce rate we have to divide the number of bounces between the total number of visits.
A Bounce happens when an user leaves the page in less than 5 seconds.
This should be the results for that table:
ItemId Bounces Visits BounceRate(Bounces/Visits)
1 1 2 0.5
2 1 2 0.5
3 0 1 0
I want to count a bounce calculating how much passes since the user performs the check until the user makes a visit to another page. If that time is less than 5 seconds, it would be counted as a bounce.
I'm making a stored procedure that execute the query to show the bounce rate of each page, but this doesn´t work.
SELECT
SUM(CASE
WHEN (DATEDIFF(second, #Occurred,
(SELECT TOP 1 a.Occurred
FROM [AuditPages] a
WHERE a.UserId = #userId
AND a.Occurred > #occurred
ORDER BY a.Occurred ASC))) < 30
THEN 1.0
ELSE 0.0
END) / COUNT(#itemId)
Someone knows how i can calculate this Bounce Rate?
Thanks for all the answers.
I like using row_number for this type of sequenced problem. The query below gives the desired result. I find performance with CTEs can sometimes be problematic with larger tables and you may need to convert to a temp table. You might consider using milliseconds if there is a chance you would want to use 4.5 seconds or such in the future.
declare #bounce_seconds int = 5;
with audit_cte as (
select *, ROW_NUMBER() over (partition by UserId order by Occurred) row_num
from AuditPages
--order by UserId,row_num
)
select a.ItemId, sum(a.bounce) Bounces, count(1) Visits, sum(a.bounce)/convert(float, count(1)) BounceRate
from (
select a1.ItemId, datediff(s,a1.Occurred, a2.Occurred) elapsed, case when datediff(s,a1.Occurred, a2.Occurred) < #bounce_seconds then 1 else 0 end bounce
from audit_cte a1
left join audit_cte a2
on a2.UserId = a1.UserId
and a2.row_num = a1.row_num + 1
--order by a1.UserId, a1.row_num
) a
group by a.ItemId
order by a.ItemId;
SELECT ItemId,COUNT(1) VISITS,SUM(BOUNCE_IND) BOUNCE, cast(SUM(BOUNCE_IND) as decimal(5,2))/cast(COUNT(1) as decimal(5,2)) BOUNCE_RATE
FROM (
Select
UserID,
ItemID,
DocLocation,
Occurred as Entry_time,
Lead(Occurred,1) Over (Partition by Userid order by Occurred) Exit_time,
CASE WHEN DATEDIFF(ss,Occurred,Lead(Occurred,1) Over (Partition by Userid order by Occurred)) <= 5 THEN 1 ELSE 0 END BOUNCE_IND
FROM Web_Data_Sample
) TBL GROUP BY ItemId