Right now I currently have the NumberOfDaysBetweenPurchases per ItemNumber by AccountNumber. I'm trying to CONCATENATE the ItemNumber|AVERAGENumberOfDaysBetweenPurchases
I have two issues. 1, I cannot find a way to get the average for all of the Days between Orders. 2, I cannot get this to display without Ordering/Grouping by Account Number or Purchase Date. So it always displays by breaking out millions of rows for each time the product was ordered by a customer.
Here is what I'm using to get the NumberOfDaysBetweenPurchases:
datediff(day, lag(OrderDate,1) over (partition by AccountNumber
order by OrderDate), OrderDate) as [NumOfDaysBetweenOrdersByAccountNum]
How do I consolidate the ItemNumbers so that they only show up once along with the Average Number of Days Between Orders by Account Number? I'd like it to show up like this:
ItemNumber | AvgNumberOfDaysBetweenOrdersByAccountNumber
12345 6
452234 45
5235 3
Here's an example of what my current info looks like (millions of rows):
ItemNumber | NumberDays(...) | OrderDate | AccountNumber
123 0 ---- 101010
123 1 ---- 101010
123 4 ---- 101010
123 7 ---- 101010
123 8 ---- 101010
From what I can understand of your question, try this.
WITH cte AS (
SELECT ItemNumber, ItemNumber, AccountNumber,
datediff(day, lag(OrderDate,1) over (partition by AccountNumber order by OrderDate), OrderDate) as [NumOfDaysBetweenOrdersByAccountNum]
)
SELECT
ItemNumber
, AVG(NumberOfDaysBetweenOrdersByAccountNum)
FROM
cte
GROUP BY
ItemNumber
Related
I have a table with user shopping data as shown below
I want an output similar to running total but instead I want the running total of the count of unique categories that the user has shopped for by date.
I know I have to make use of ROWS PRECEDING AND FOLLOWING in the count function but I am not able to user count(distinct category) in a window function
Dt category userId
4/10/2022 Grocery 123
4/11/2022 Grocery 123
4/12/2022 MISC 123
4/13/2022 SERVICES 123
4/14/2022 RETAIl 123
4/15/2022 TRANSP 123
4/20/2022 GROCERY 123
Desired output
Dt userID number of unique categories
4/10/2022 123 1
4/11/2022 123 1
4/12/2022 123 2
4/13/2022 123 3
4/14/2022 123 4
4/15/2022 123 5
4/20/2022 123 5
Consider below approach
select Dt, userId,
( select count(distinct category)
from t.categories as category
) number_of_unique_categories
from (
select *, array_agg(lower(category)) over(partition by userId order by Dt) categories
from your_table
) t
if applied to sample data in your question - output is
I have a table like this, with column names as Date of Sale and insurance Salesman Names -
Date of Sale | Salesman Name | Sale Amount
2021-03-01 | Jack | 40
2021-03-02 | Mark | 60
2021-03-03 | Sam | 30
2021-03-03 | Mark | 70
2021-03-02 | Sam | 100
I want to do a group by, using the date of sale. The next column should display the cumulative count of the sellers who have made the sale till that date. But same sellers shouldn't be considered again.
For example,
The following table is incorrect,
Date of Sale | Count(Salesman Name) | Sum(Sale Amount)
2021-03-01 | 1 | 40
2021-03-02 | 3 | 200
2021-03-03 | 5 | 300
The following table is correct,
Date of Sale | Count(Salesman Name) | Sum(Sale Amount)
2021-03-01 | 1 | 40
2021-03-02 | 3 | 200
2021-03-03 | 3 | 300
I am not sure how to frame the SQL query, because there are two conditions involved here, cumulative count while ignoring the duplicates. I think the OVER clause along with the unbounded row preceding may be of some use here? Request your help
Edit - I have added the Sale Amount as a column. I need the cumulative sum for the Sales Amount also. But in this case , all the sale amounts should be considered unlike the salesman name case where only unique names were being considered.
One approach uses a self join and aggregation:
WITH cte AS (
SELECT t1.SaleDate,
COUNT(CASE WHEN t2.Salesman IS NULL THEN 1 END) AS cnt,
SUM(t1.SaleAmount) AS amt
FROM yourTable t1
LEFT JOIN yourTable t2
ON t2.Salesman = t1.Saleman AND
t2.SaleDate < t1.SaleDate
GROUP BY t1.SaleDate
)
SELECT
SaleDate,
SUM(cnt) OVER (ORDER BY SaleDate) AS NumSalesman,
SUM(amt) OVER (ORDER BY SaleDate) AS TotalAmount
FROM cte
ORDER BY SaleDate;
The logic in the CTE is that we try to find, for each salesman, an earlier record for the same salesman. If we can't find such a record, then we assume the record in question is the first appearance. Then we aggregate by date to get the counts per day, and finally take a rolling sum of counts in the outer query.
The best way to do this uses window functions to determine the first time a sales person appears. Then, you just want cumulative sums:
select saledate,
sum(case when seqnum = 1 then 1 else 0 end) over (order by saledate) as num_salespersons,
sum(sum(sales)) over (order by saledate) as running_sales
from (select t.*,
row_number() over (partition by salesperson order by saledate) as seqnum
from t
) t
group by saledate
order by saledate;
Note that this in addition to being more concise, this should have much, much better performance than a solution that uses a self-join.
I'm looking for some assistance: I am looking to get this into a report but not sure how to achieve this.
Here is the data stored in the table:
Product | Quantity | Status | Line
Product1 1 Active 1000
Product2 2 Active 2000
Product1 2 Active 3000
Product1 1 InDev 4000
Product2 2 Active 5000
I am grouping by Product and Status and summing up Quantity.
But looking to also retrieve the lowest line number for row in the group.
My expected result would be like below:
Product | Quantity | Status | Line
Product1 3 Active 1000
Product2 4 Active 2000
Product1 1 InDev 5000
Any help would be greatly appreciated
This can be done if you group by Product, Status and aggregate:
select Product, sum(Quantity) Quantity, Status, min(Line) Line
from tablename
group by Product, Status
You can use window function :
select *
from (select t.*, row_number() over (partition by product, status order by line) as seq,
sum(qty) over (partition by product, status) as sum_qty
from table t
) t
where seq = 1;
If table has only available columns (in question) then you can do aggregation :
select product, sum(qty), status, min(line) as line
from table t
group by product, status
order by line;
I am on Oracle 12c and need help with the simple query.
Here is the sample data of what I currently have:
Table Name: customer
Table DDL
create table customer(
customer_id varchar2(50),
name varchar2(50),
activation_dt date,
space_occupied number(50)
);
Sample Table Data:
customer_id name activation_dt space_occupied
abc abc-001 2016-09-12 20
xyz xyz-001 2016-09-12 10
Sample Data Output
The query I am looking for will provide the following:
customer_id name activation_dt space_occupied
abc abc-001 2016-09-12 20
xyz xyz-001 2016-09-12 10
Total_Space null null 30
Here is a slightly hack-y approach to this, using the grouping function ROLLUP(). Find out more.
SQL> select coalesce(customer_id, 'Total Space') as customer_id
2 , name
3 , activation_dt
4 , sum(space_occupied) as space_occupied
5 from customer
6 group by ROLLUP(customer_id, name, activation_dt)
7 having grouping(customer_id) = 1
8 or (grouping(name) + grouping(customer_id)+ grouping(activation_dt)) = 0;
CUSTOMER_ID NAME ACTIVATIO SPACE_OCCUPIED
------------ ------------ --------- --------------
abc abc-001 12-SEP-16 20
xyz xyz-001 12-SEP-16 10
Total Space 30
SQL>
ROLLUP() generates intermediate totals for each combination of column; the verbose HAVING clause filters them out and retains only the grand total.
What you want is a bit unusual, as if customer_id is integer, then you have to cast it to string etc, but it this is your requirement, then if be achieved this way.
SELECT customer_id,
name,
activation_dt,
space_occupied
FROM
(SELECT 1 AS seq,
customer_id,
name,
activation_dt,
space_occupied
FROM customer
UNION ALL
SELECT 2 AS seq,
'Total_Space' AS customer_id,
NULL AS name,
NULL AS activation_dt,
sum(space_occupied) AS space_occupied
FROM customer
)
ORDER BY seq
Explanation:
Inner query:
First part of union all; I added 1 as seq to give 1
hardcoded with your resultset from customer.
Second part of union
all: I am just calculating sum(space_occupied) and hardcoding other
columns, including 2 as seq
Outer query; Selecting the data
columns and order by seq, so Total_Space is returned at last.
Output
+-------------+---------+---------------+----------------+
| CUSTOMER_ID | NAME | ACTIVATION_DT | SPACE_OCCUPIED |
+-------------+---------+---------------+----------------+
| abc | abc-001 | 12-SEP-16 | 20 |
| xyz | xyz-001 | 12-SEP-16 | 10 |
| Total_Space | null | null | 30 |
+-------------+---------+---------------+----------------+
Seems like a great place to use group by grouping sets seems like this is what they were designed for. Doc link
SELECT coalesce(Customer_Id,'Total_Space') as Customer_ID
, Name
, ActiviatioN_DT
, sum(Space_occupied) space_Occupied
FROM customer
GROUP BY GROUPING SETS ((Customer_ID, Name, Activation_DT, Space_Occupied)
,())
The key thing here is we are summing space occupied. The two different grouping mechanisms tell the engine to keep each row in it's original form and 1 records with space_occupied summed; since we group by () empty set; only aggregated values will be returned; along with constants (coalesce hardcoded value for total!)
The power of this is that if you needed to group by other things as well you could have multiple grouping sets. imagine a material with a product division, group and line and I want a report with sales totals by division, group and line. You could simply group by () to get grand total, (product_division, Product_Group, line) to get a product line (product_Divsion, product_group) to get a product_group total and (product_division) to get a product Division total. pretty powerful stuff for a partial cube generation.
I'm not sure if this is possible - I'm having real trouble getting my head around it.
This is for a product schedule, showing how much we are expecting to deliver on a given date. Data is imported into this schedule weekly which creates a new entry.
For example, if the schedule for the day currently totals 10, and you import 15, a new row is inserted with Qty 5, bringing the sum to 15.
The data I have is like so:
Product | Delivery Required Date | Qty
Prod1 | 1/1/13 | 10
Prod1 | 1/1/13 | -10
Prod1 | 1/1/13 | 10
Prod1 | 1/1/13 | -10
Prod1 | 1/1/13 | 25
I want to design a query which shows the variance between the previous schedule, and the current schedule.
For example, the query will sum all of the rows "Qty", excluding the last entry - and compare it to the last entry. In the data above, the variance is 25 (Existing total was 0, latest entry is 25, 0+25 =25).
Is this possible?
Thanks
I suspect there'a better answer using Common Table Expressions, but a quick & ugly solution might be
select sum(case when EntryNo <> MAX(EntryNo) then Qty else 0 end) as 'sumLessLast'
from MyTable
If MyTable has a million rows in it you'll want a better solution.
SqlServer 2005 and 2008:
;with r1 as (
select DeliveryReqDate, sum(Qty) as TotalQty
from TableName
group by DeliveryReqDate)
, r2 as (
select DeliveryReqDate, Qty
, row_number() over (partition by DeliveryReqDate order by EntryNo desc) rn
from TableName)
select r1.DeliveryReqDate, r1.TotalQty, r2.Qty as LastQty
, r1.TotalQty - r2.Qty as TotalButLastQty
from r1
join r2 on r2.DeliveryReqDate = r1.DeliveryReqDate and r2.rn = 1
SqlServer 2012
;with r1 as (
select DeliveryReqDate, Qty
, sum(Qty) over (partition by DeliveryReqDate) as TotalQty
, row_number() over (partition by DeliveryReqDate order by EntryNo desc) rn
from TableName)
select DeliveryReqDate, TotalQty, Qty as LastQty
, TotalQty - Qty as TotalButLastQty
from r1
where rn = 1
I'm not sure that I completely understand logic regarding the accounting of product and date, but I hope you can adapt above queries to your needs.