i need a sql query that can show something like this :
My Data :
| id | Purchase Number | Qty |
|:---- |:------:| -----:|
| 1 | A | 3 |
| 2 | B | 2 |
| 3 | C | 4 |
For example i need to take 6 Qty
I want the result will be like this :
| id | Purchase Number | Qty |
|:---- |:------:| -----:|
| 1 | A | 3 |
| 2 | B | 2 |
| 3 | C | 1|
I've read similar thread but cant find what i need
You can use a cumulative sum:
select id, purchase_number,
(case when running_qty < 6 then qty
else 6 - (running_qty - qty)
end)
from (select t.*,
sum(qty) over (order by id) as running_qty
from t
) t
where running_qty - qty < 6;
Here is a db<>fiddle (which uses Postgres but this is standard SQL).
Related
Let's say I have the following table:
| sku | id | value | count |
|-----|----|-------|-------|
| A | 1 | 1 | 2 |
| A | 1 | 2 | 2 |
| A | 3 | 3 | 3 |
I want to select rows that don't have the same count for the same id. So my desired outcome is:
| sku | id | value | count |
|-----|----|-------|-------|
| A | 3 | 3 | 3 |
I need something that works with Postgres 10
A simple method is window functions:
select t.*
from (select t.*, count(*) over (partition by sku, id) as cnt
from t
) t
where cnt = 1;
This assumes you really mean the sku/id combination.
Suppose I have a table sorted by date as so:
+-------------+--------+
| DATE | VALUE |
+-------------+--------+
| 01-09-2020 | 5 |
| 01-15-2020 | 5 |
| 01-17-2020 | 5 |
| 02-03-2020 | 8 |
| 02-13-2020 | 8 |
| 02-20-2020 | 8 |
| 02-23-2020 | 5 |
| 02-25-2020 | 5 |
| 02-28-2020 | 3 |
| 03-13-2020 | 3 |
| 03-18-2020 | 3 |
+-------------+--------+
I want to group by changes in value within that given date range, and add a value that increments each time as an added column to denote that.
I have tried a number of different things, such as using the lag function:
SELECT value, value - lag(value) over (order by date) as count
GROUP BY value
In short, I want to take the table above and have it look like:
+-------------+--------+-------+
| DATE | VALUE | COUNT |
+-------------+--------+-------+
| 01-09-2020 | 5 | 1 |
| 01-15-2020 | 5 | 1 |
| 01-17-2020 | 5 | 1 |
| 02-03-2020 | 8 | 2 |
| 02-13-2020 | 8 | 2 |
| 02-20-2020 | 8 | 2 |
| 02-23-2020 | 5 | 3 |
| 02-25-2020 | 5 | 3 |
| 02-28-2020 | 3 | 4 |
| 03-13-2020 | 3 | 4 |
| 03-18-2020 | 3 | 4 |
+-------------+--------+-------+
I want to eventually have it all in one small table with the earliest date for each.
+-------------+--------+-------+
| DATE | VALUE | COUNT |
+-------------+--------+-------+
| 01-09-2020 | 5 | 1 |
| 02-03-2020 | 8 | 2 |
| 02-23-2020 | 5 | 3 |
| 02-28-2020 | 3 | 4 |
+-------------+--------+-------+
Any help would be very appreciated
you can use a combination of Row_number and Dense_rank functions to get the required results like below:
;with cte
as
(
select t.DATE,t.VALUE
,Dense_rank() over(partition by t.VALUE order by t.DATE) as d_rank
,Row_number() over(partition by t.VALUE order by t.DATE) as r_num
from table t
)
Select t.Date,t.Value,d_rank as count
from cte
where r_num = 1
You can use a lag and cumulative sum and a subquery:
SELECT value,
SUM(CASE WHEN prev_value = value THEN 0 ELSE 1 END) OVER (ORDER BY date)
FROM (SELECT t.*, LAG(value) OVER (ORDER BY date) as prev_value
FROM t
) t
Here is a db<>fiddle.
You can recursively use lag() and then row_number() analytic functions :
WITH t2 AS
(
SELECT LAG(value,1,value-1) OVER (ORDER BY date) as lg,
t.*
FROM t
)
SELECT t2.date,t2.value, ROW_NUMBER() OVER (ORDER BY t2.date) as count
FROM t2
WHERE value - lg != 0
Demo
and filter through inequalities among the returned values from those functions.
I want to calculate
(1) total sales amount
(2) number of distinct stores per product
in one query, if possible. Suppose we have data:
+-----------+---------+-------+--------+
| store | product | month | amount |
+-----------+---------+-------+--------+
| Anthill | A | 1 | 1 |
| Anthill | A | 2 | 1 |
| Anthill | A | 3 | 1 |
| Beetle | A | 1 | 1 |
| Beetle | A | 3 | 1 |
| Cockroach | A | 1 | 1 |
| Cockroach | A | 2 | 1 |
| Cockroach | A | 3 | 1 |
| Anthill | B | 1 | 1 |
| Beetle | B | 2 | 1 |
| Cockroach | B | 3 | 1 |
+-----------+---------+-------+--------+
I have tried this with no luck:
select
[product]
,[month]
,[amount]
,cnt_distinct_stores = count(distinct(stores))
from dbo.temp
group by
[product]
,[month]
order by 1,2
Would there be possible any combination of GROUP BY clause with window functions like SUM(amount) OVER(partition by [product],[month] ORDER BY [month] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
Try
SELECT product,
SUM(amount),
COUNT(DISTINCT store)
FROM dbo.temp
GROUP BY product
I've posted several topics and every query had some problems :( Changed table and examples for better understanding
I have a table called PROD_COST with 5 fields
(ID,Duration,Cost,COST_NEXT,COST_CHANGE).
I need extra field called "groups" for aggregation.
Duration = number of days the price is valid (1 day=1row).
Cost = product price in this day.
-Cost_next = lead(cost,1,0).
Cost_change = Cost_next - Cost.
example:
+----+---------+------+-------------+-------+
|ID |Duration | Cost | Cost_change | Groups|
+----+---------+------+-------------+-------+
| 1 | 1 | 10 | -1,5 | 1 |
| 2 | 1 | 8,5 | 3,7 | 2 |
| 3 | 1 | 12.2 | 0 | 2 |
| 4 | 1 | 12.2 | -2,2 | 3 |
| 5 | 1 | 10 | 0 | 3 |
| 6 | 1 | 10 | 3.2 | 4 |
| 7 | 1 | 13.2 | -2,7 | 5 |
| 8 | 1 | 10.5 | -1,5 | 5 |
| 9 | 1 | 9 | 0 | 5 |
| 10 | 1 | 9 | 0 | 5 |
| 11 | 1 | 9 | -1 | 5 |
| 12 | 1 | 8 | 1.5 | 6 |
+----+---------+------+-------------+-------+
Now i need to group("Groups" field) by Cost_change. It can be positive,negative or 0 values.
Some kind guy advised me this query:
select id, COST_CHANGE, sum(GRP) over (order by id asc) +1
from
(
select *, case when sign(COST_CHANGE) != sign(isnull(lag(COST_CHANGE)
over (order by id asc),COST_CHANGE)) and Cost_change!=0 then 1 else 0 end as GRP
from PROD_COST
) X
But there is a problem: If there are 0 values between two positive or negative values than it groups it separately, for example:
+-------------+--------+
| Cost_change | Groups |
+-------------+--------+
| 9.262 | 5777 |
| -9.262 | 5778 |
| 9.262 | 5779 |
| 0.000 | 5779 |
| 9.608 | 5780 |
| -11.231 | 5781 |
| 10.000 | 5782 |
+-------------+--------+
I need to have:
+-------------+--------+
| Cost_change | Groups |
+-------------+--------+
| 9.262 | 5777 |
| -9.262 | 5778 |
| 9.262 | 5779 |
| 0.000 | 5779 |
| 9.608 | 5779 | -- Here
| -11.231 | 5780 |
| 10.000 | 5781 |
+-------------+--------+
In other words, if there's 0 values between two positive ot two negative values than they should be in one group, because Sequence: MINUS-0-0-MINUS - no rotation. But if i had MINUS-0-0-PLUS, than GROUPS should be 1-1-1-2, because positive valus is rotating with negative value.
Thank you for attention!
I'm Using Sql Server 2012
I think the best approach is to remove the zeros, do the calculation, and then re-insert them. So:
with pcg as (
select pc.*, min(id) over (partition by grp) as grpid
from (select pc.*,
(row_number() over (order by id) -
row_number() over (partition by sign(cost_change)
order by id
) as grp
from prod_cost pc
where cost_change <> 0
) pc
)
select pc.*, max(groups) over (order by id)
from prod_cost pc left join
(select pcg.*, dense_rank() over (order by grpid) as groups
from pcg
) pc
on pc.id = pcg.id;
The CTE assigns a group identifier based on the lowest id in the group, where the groups are bounded by actual sign changes. The subquery turns this into a number. The outer query then accumulates the maximum value, to give a value to the 0 records.
I've been struggling with the following SQL query.
My resultset is now:
| Id | Customer | Sales |
| 1 | 1 | 10 |
| 2 | 1 | 20 |
| 3 | 2 | 30 |
| 4 | 2 | 40 |
What I'd like to do is to add additional column that shows the smallest sale for that customer:
| Id | Customer | Sales | SmallestSale |
| 1 | 1 | 10 | 10 |
| 2 | 1 | 20 | 10 |
| 3 | 2 | 30 | 30 |
| 4 | 2 | 40 | 30 |
As the select query to get those three columns is now rather complex I'd like to avoid subqueries.
Any ideas?
Mika
Assuming your RDBMS supports windowed aggregates
SELECT Id,
Customer,
Sales,
MIN(Sales) OVER (PARTITION BY Customer) AS SmallestSale
FROM YourTable
select s.Id, s.Customer, s.Sales, sm.SmallestSale
from Sales s
inner join (
select Customer, min(sales) as SmallestSale
from Sales
group by Customer
) sm on s.Customer = sm.Customer