Given the sample data, what would be the most efficient way to do the following:
ID event_type event_id event_date quantity
123 B 0 2022-12-31 3
123 A 1 2023-01-01 2
123 A 2 2023-01-02 3
123 C 3 2023-01-03 8
123 A 4 2023-01-04 3
123 A 5 2023-01-05 1
123 B 6 2023-01-06 1
123 C 8 2023-01-07 5
Sum the quantity for all the Bs that happen before some A, and all the Cs that happen after some A?
Meaning in this case, for B we will sum up only the first line and for C we will sump up both cases.
ID event_type quantity
123 B 3
123 C 15
Sum the quantity for all the Bs that happen before all the As and all the Cs that happen exclusively after all As?
ID event_type quantity
123 B 3
123 C 8
For the second case, I can look at the min and max date of event A and then compare it against the dates of C and B. I am not sure about the first case when events can be followed by one another.
Related
TableA
ID
Counter
Value
1
1
10
1
2
28
1
3
34
1
4
22
1
5
80
2
1
15
2
2
50
2
3
39
2
4
33
2
5
99
TableB
StartDate
EndDate
2020-01-01
2020-01-11
2020-01-02
2020-01-12
2020-01-03
2020-01-13
2020-01-04
2020-01-14
2020-01-05
2020-01-15
2020-01-06
2020-01-16
TableC (output)
ID
Counter
StartDate
EndDate
Val
1
1
2020-01-01
2020-01-11
10
2
1
2020-01-01
2020-01-11
15
1
2
2020-01-02
2020-01-12
28
2
2
2020-01-02
2020-01-12
50
1
3
2020-01-03
2020-01-13
34
2
3
2020-01-03
2020-01-13
39
1
4
2020-01-04
2020-01-14
22
2
4
2020-01-04
2020-01-14
33
1
5
2020-01-05
2020-01-15
80
2
5
2020-01-05
2020-01-15
99
1
1
2020-01-06
2020-01-16
10
2
1
2020-01-06
2020-01-16
15
I am attempting to come up with some SQL to create TableC. What TableC is, it takes the data from TableB, in chronological order, and for each ID in tableA, it finds the next counter in the sequence, and assigns that to the Start/End date combination for that ID, and when it reaches the end of the counter, it will start back at 1.
Is something like this even possible with SQL?
Yes this is possible. Try to do the following:
Calculate maximal value for Counter in TableA using SELECT MAX(Counter) ... into max_counter.
Add identifier row_number to each row in TableB so it will be able to find matching Counter value using SELECT ROW_NUMBER() OVER() ....
Establish relation between row number in TableB and Counter in TableA like this ... FROM TableB JOIN TableA ON (COALESCE(NULLIF(TableB.row_number % max_counter = 0), max_counter)) = TableA.Counter.
Then gather all these queries using CTE (Common Table Expression) into one query as official documentation shows.
Consider below approach
select id, counter, StartDate, EndDate, value
from tableA
join (
select *, mod(row_number() over(order by StartDate) - 1, 5) + 1 as counter
from tableB
)
using (counter)
if applied to sample data in your question - output is
I could not find keywords to describe in the title.
I have a problem and I just can explain with example, I have a table like this
user_id | transaction_id | bonus_id | created_at
1. 1 4 2021-05-01
1 3 65 2021-05-01
1 4 4 2021-05-02
1 1 5 2021-05-02
1. 3 76. 2021-05-03
1 2 5 2021-05-03
Due to a mistake I made in php here, transaction id 3 and bonus id 65 but the bonus id 4 that should be
I need to replace all transactions from transaction type 1 to the next transaction type 1 with the bonus id of the first transaction_type_1.
but of course I have to do this for every user. How can I do that?
Is there a way to find the solution so that I need for 2 days, there are 2 UD's because there are June 24 2 times and for the rest there are single days.
I am showing the expected output here:
Primary key UD Date
-------------------------------------------
1 123 2015-06-24 00:00:00.000
6 456 2015-06-24 00:00:00.000
2 123 2015-06-25 00:00:00.000
3 658 2015-06-26 00:00:00.000
4 598 2015-06-27 00:00:00.000
5 156 2015-06-28 00:00:00.000
No of times Number of days
-----------------------------
4 1
2 2
The logic is 4 users are there who used the application on 1 day and there are 2 userd who used the application on 2 days
You can use two levels of aggregation:
select cnt, count(*)
from (select date, count(*) as cnt
from t
group by date
) d
group by cnt
order by cnt desc;
I have a table with 1 result per day like this :
id | item_id | date | amount
-------------------------------------
1 1 2019-01-01 1
2 1 2019-01-02 2
3 1 2019-01-03 3
4 1 2019-01-04 4
5 1 2019-01-05 5
6 2 2019-01-01 1
7 2 2019-01-01 2
8 2 2019-01-01 3
9 2 2019-01-01 4
10 2 2019-01-01 5
11 3 2019-01-01 1
12 3 2019-01-01 2
13 3 2019-01-01 3
14 3 2019-01-01 4
15 3 2019-01-01 5
First I was trying to average the column amount for each day.
SELECT
x.item_id AS id,avg(x.amount) AS result
FROM
(SELECT
il.item_id, il.amount,
ROW_NUMBER() OVER (PARTITION BY il.item_id ORDER BY il.date DESC) rn
FROM
item_prices il) x
WHERE
x.rn BETWEEN 1 AND 50
GROUP BY
x.item_id
The result is going to be the following if calculated on 2019-01-05
item_id | average
1 3
2 3
3 3
or, if calculated 2019-01-04
item_id | average
1 2.5
2 2.5
3 2.5
My goal is to run the Average query , every day that would update the average automatically and insert it in 5th column "average" :
id | item_id | date | amount | average
5 1 2019-01-05 5 3
10 2 2019-01-05 5 3
15 3 2019-01-05 5 3
Issue is that every example i can find with Insert the Select they only update one row and they are over another table there is also the most recent date issue...
Can someone point me in the right direction?
Perhaps you want to see running average every day. Storing the value as a separate column is bound to cause problems especially when the rows are updated/deleted, the column also needs to be updated and hence will require complex triggers.
Simply create a View and run whenever you want to check the average directly from that View.
CREATE OR REPLACE VIEW v_item_prices AS
SELECT t.*,avg(t.amount) OVER ( PARTITION BY item_id order by date)
AS average FROM item_prices t
order by item_id,date
DEMO
I have a list of codes by area and type. I need to get the unique codes for each type, which I can do with a simple SELECT query with a GROUP BY. I now need to know which area does not have one of the codes. So how do I run a query to group by unique values and tell me how records do not have one of the values?
ID Area Type Code
1 10 A 123
2 10 A 456
3 10 B 789
4 10 B 987
5 10 C 654
6 10 C 321
7 20 A 123
8 20 B 789
9 20 B 987
10 20 C 654
11 20 C 321
12 30 A 137
13 30 A 456
14 30 B 579
15 30 B 789
16 30 B 987
17 30 C 654
18 30 C 321
I can run this query to group them by type and get get the unique codes:
SELECT tblExample.Type, tblExample.Code
FROM tblExample
GROUP BY tblExample.Type, tblExample.Code
This gives me this:
Type Code
A 123
A 137
A 456
B 579
B 789
B 987
C 321
C 654
Now I need to know which areas do not have a given code. For example, Code 123 does not appear for Area 10 and code 137 does not appear for codes 10 and 20. How do I write a query to give me that areas are missing a code? The format of the output doesn't matter, I just need to get the results. I'm thinking the results could be in one column or spread out in multiple columns:
Type Code Missing Areas or Missing1 Missing2
A 123 30 30
A 137 10, 20 10 20
A 456 20 20
B 579 10, 20 10 20
B 789
B 987
C 321
C 654
You can get a list of the missing code/areas by first generating all combinations and then filtering out the ones that exist:
select t.type, c.code
from (select distinct type from tblExample) t cross join
(select distinct code from tblExample) c left join
tblExample e
on t.type = e.type and c.code = e.code
where e.type is null;