I have table A and table B. Each row in table A represents every time a user sends a message. Each row in table B represents every time a user buys a gift.
Goal: for each time a user sends a message, calculate how many gifts they've purchased within 7 days before the timestamp they sent the message. Some users never send messages and some never purchased gifts. If the user in table A didn't have gift purchased within 7 days, the count should be 0.
Table A:
user_id
time
12345
2021-09-04 09:43:55
12345
2021-09-03 00:39:30
12345
2021-09-02 03:26:07
12345
2021-09-05 15:48:34
23456
2021-09-09 09:06:22
23456
2021-09-08 08:06:21
00001
2021-09-03 15:38:15
00002
2021-09-03 15:38:15
Table B:
user_id
time
12345
2021-09-01 09:43:55
12345
2021-08-03 00:42:30
12345
2021-09-03 02:16:07
00003
2021-09-05 15:48:34
23456
2021-09-03 09:06:22
23456
2021-09-10 08:06:21
Expected output:
user_id
time
count
12345
2021-09-04 09:43:55
2
12345
2021-09-03 00:39:30
1
12345
2021-09-02 03:26:07
1
12345
2021-09-05 15:48:34
2
23456
2021-09-09 09:06:22
1
23456
2021-09-08 08:06:21
1
00001
2021-09-03 15:38:15
0
00002
2021-09-03 15:38:15
0
Query I tried:
SELECT A.user_id, A.time, coalesce(count(*), 0) as count
FROM A
LEFT JOIN B ON A.user_id = B.user_id AND B.time >= A.time - INTERVAL '7 days' AND B.time < A.time
GROUP BY 1,2
The count returned doesn't match the expected result however, not sure if I'm doing the join and conditions correctly.
You need to count the values from the possibly NULL columns i.e. from table B in order to get the correct counts of non-existent matches. i.e. being more specific in COUNT(*) to COUNT(b.column_from_b_table). See modification with working demo fiddle below:
SELECT
A.user_id,
A.time,
coalesce(count(B.user_id), 0) as count
FROM A
LEFT JOIN B ON A.user_id = B.user_id AND
B.time >= A.time - INTERVAL '7 days' AND
B.time < A.time
GROUP BY 1,2;
user_id
time
count
1
2021-09-03T15:38:15.000Z
0
12345
2021-09-05T15:48:34.000Z
2
23456
2021-09-08T08:06:21.000Z
1
12345
2021-09-04T09:43:55.000Z
2
12345
2021-09-03T00:39:30.000Z
1
23456
2021-09-09T09:06:22.000Z
1
2
2021-09-03T15:38:15.000Z
0
12345
2021-09-02T03:26:07.000Z
1
View on DB Fiddle
Let me know if this works for you.
Related
I have a table that has wholesale data and retail data.
the data is structured as
Channel
Serial#
Date
WS-Build
12345
1/1/2019
WS-Dealer
34567
1/5/2021
Retail
12345
1/1/2020
Retail
34567
3/5/2021
I would like the output to match on serial#
Each serial # will appear twice in the table. I am trying to get a count of # of units sold via builder or dealer.
Serial#
Channel
WholesaleDate
Retail Date
12345
WS-Build
1/1/2019
1/1/2020
34567
WS-Dealer
1/5/2021
3/5/2021
How can i achieve that by joining on the same table?
Try join by serial and channel
select t1.serial#, t2.WholesaleDate, t2."Retail Date", (*) from table1 t1
join table2 t2 on t1.serial# = t2.serial# and t1.channel = t2.channel
group by t1.serial#, , t2.WholesaleDate, t2."Retail Date";
As long as the retail is after the sale you can do
but i don't get where the counts come in
SELECT
t1."Serial#",t1."Channel", t1."Date" as WholesaleDate, t2."Date" as "Retail Date"
FROM tab1 t1 JOIN tab1 t2 ON t1."Serial#" = t2."Serial#" AND t1."Date" < t2."Date"
Serial#
Channel
wholesaledate
Retail Date
12345
WS-Build
2019-01-01 00:00:00
2020-01-01 00:00:00
34567
WS-Dealer
2021-05-01 00:00:00
2021-05-03 00:00:00
SELECT 2
fiddle
I have a table t with:
DATE
LOCATION
PRODUCT_ID
AMOUNT
2021-10-29
1
123
10
2021-10-30
1
123
9
2021-10-31
1
123
8
2021-10-29
1
456
100
2021-10-30
1
456
90
2021-10-31
1
456
80
2021-10-29
2
123
18
2021-10-30
2
123
17
2021-11-29
2
456
18
I need to find the AMOUNT of each PRODUCT_ID for each combination of LOCATION + PRODUCT_ID.
If a PRODUCT_ID has no entry for that day the AMOUNT is NULL.
So the result should look like:
DATE
LOCATION
PRODUCT_ID
AMOUNT
2021-10-31
1
123
8
2021-10-31
1
456
80
2021-10-31
2
123
NULL
2021-11-30
2
456
NULL
Sadly EXASOL has no LAST_DAY() or EOMONTH() function. How can I solve this?
You can get to the last day of the month using a date_trunc function in combination with date_add:
case
when t.date = date_add('day', -1, date_add('month', 1, date_trunc('month', t.date)))
then 'Y' else 'N' end as end_of_month
That being said, if you group your table for all combinations of locations and products, you will not get NULLs for products without sales on the last day of the month as shown in your output table.
When you group your data, any value that does not exist will simply not show up in your output table. If you want to force nulls to show up, you can create a new table that contains all combinations of products, locations, and hard-coded end of month dates.
Then, you can left join your old table with this new hard-coded table by date, location, and product. This method will give you the NULL values you expect.
There are two tables.
In the first I have columns:
id - a person
time - the time of receiving the bonus (timestamp)
money - size of bonus
And the second:
id
time - time of getting a rank (timestamp)
range - military rank (int)
The task is to withdraw the amount and number of bonuses received by people in the rank of captain (range = 7) with aggregation by day.
I have no ideas how to do a table with this data. I can summarize data by all days such as
SELECT DISTINCTROW Payment.user_id AS user_id, Sum(IIf(IsNull(Payment.money),0,Payment.money)) AS [Sum - money], Count(Payment.money) AS [Count - Payment], Format(Payment.time, "Short Date") as day
FROM Payment
GROUP BY Payment.user_id, Format (Payment.time, "Short Date")
Having ((Count(Payment.money) > 0));
Can you help me with second part and summarize them? thanks
For example: first table (Payment):
user_id time money
a 01.01.10 00:00:00 15,00
a 01.01.10 10:00:00 2,00
a 03.01.10 00:00:00 3,00
c 04.01.10 00:00:00 4,00
c 04.01.10 00:05:00 5,00
d 06.01.10 00:00:00 6,00
e 07.01.10 00:00:00 7,00
e 08.01.10 00:00:00 8,00
The second one:
user_id time range
a 01.01.10 00:00:00 6
a 01.01.10 09:00:00 7
a 04.01.10 00:00:00 8
b 04.01.10 00:00:00 4
c 04.01.10 00:05:00 7
d 06.01.10 00:00:00 5
e 07.01.10 00:00:00 6
f 08.01.10 00:00:00 6
g 08.01.10 00:00:00 7
I expected:
user_id time sum
a 01.01.10 2
a 03.01.10 3
c 04.01.10 5
Here is one possible method using joins:
select t1.user_id, datevalue(p.time) as [time], sum(p.money) as [sum]
from
(
(select t.user_id, t.time from rank t where t.range = 7) t1
inner join payment p on t1.user_id = p.user_id
)
left join
(select t.user_id, t.time from rank t where t.range > 7) t2 on p.user_id = t2.user_id
where
p.time >= t1.time and (t2.user_id is null or p.time < t2.time)
group by
t1.user_id, datevalue(p.time)
I have assumed that your second table is called rank (this was not stated in your question).
Here, the subquery t1 obtains the set of users with range = 7 (captain), and the subquery t2 obtains the set of users with range > 7. I then select all records with a payment date greater than or equal to the date of promotion to captain, but less than any subsequent promotion (if it exists).
This yields the following result:
+---------+------------+------+
| user_id | time | sum |
+---------+------------+------+
| a | 01/01/2010 | 2.00 |
| a | 03/01/2010 | 3.00 |
| c | 04/01/2010 | 5.00 |
+---------+------------+------+
Unless I have misunderstood, I would argue that your expected result is incorrect as the payment below occurs before user_id = c achieved the rank of captain:
c 04.01.10 00:00:00 4,00
c 04.01.10 00:05:00 7
I have a created_date (timestamp) on 1 of my tables, that also has the duration column of a project, and I need to join with another table that only has first_day_of_month column that has the first day of each month, and other relevant information.
Table 1
id project_id created_date duration
1 12345 01/01/2015 10
2 12345 20/10/2015 11
3 12345 10/04/2016 13
4 12345 10/08/2016 15
Table 2
project_id month_start_date
12345 01/01/2015
12345 01/02/2015
12345 01/03/2015
12345 01/04/2015
...
12345 01/08/2016
Expected result
project_id month_start_date duration
12345 01/01/2015 10
12345 01/02/2015 10
...
12345 01/10/2015 11
12345 01/11/2015 11
...
12345 01/04/2016 13
12345 01/05/2016 13
12345 01/06/2016 13
...
12345 01/08/2016 15
I want to be able to present the data listed in my second table historically. So, basically I want the query to return the same duration related to the month_start_date, so that values will repeat until another dateadd(month,datediff(month,0,created_date),0) = first_day_of_month is met... and so forth.
This is my query:
select table2.project_name,
table2.month_start_date,
table1.duration,
table1.created_date
from table1 left outer join table2
on table1.project_id=table2.project_id
where dateadd(month,datediff(month,0,table1.created_date),0)<=table2.month_start_date
group by table2.project_name,table2.month_start_date,table1.duration,table1.created_date
order by table2.month_start_date asc
but I get repeated records on this:
Result I'm getting
project_id month_start_date duration
12345 01/01/2015 10
12345 01/02/2015 10
...
12345 01/10/2015 10
12345 01/10/2015 11
...
12345 01/04/2016 10
12345 01/04/2016 11
12345 01/04/2016 13
...
12345 01/08/2016 10
12345 01/08/2016 11
12345 01/08/2016 13
12345 01/08/2016 15
Can anyone help?
Thank you!
I'd use CROSS/OUTER APPLY operator.
Here is one possible variant. For each row in your calendar table Table2 (for each month) the inner correlated subquery inside the CROSS APPLY finds one row from Table1. It will be the row with the same project_id and the first row with created_date before the month_start_date plus 1 month.
SELECT
Table2.project_id
,Table2.month_start_date
,Durations.duration
FROM
Table2
CROSS APPLY
(
SELECT TOP(1) Table1.duration
FROM Table1
WHERE
Table1.project_id = Table2.project_id
AND Table1.created_date < DATEADD(month, 1, Table2.month_start_date)
ORDER BY Table1.created_date DESC
) AS Durations
;
Make sure that Table1 has index on (project_id, created_date) include (duration). Otherwise, performance would be poor.
I have the below table having student information.
S_ID Group_ID Date Score
12345 1 1/1/2015 1
12345 1 2/1/2015 2
12345 1 3/1/2015 4
12345 1 4/1/2015 5
12345 1 9/1/2015 3
12345 1 10/1/2015 8
12345 2 1/1/2015 2
12345 2 2/1/2015 4
12345 2 3/1/2015 6
I want to generate a new table based for few students after adding a sequence column as shown below
S_ID Group_ID Date Score Sequence
12345 1 1/1/2015 1 1
12345 1 2/1/2015 2 2
12345 1 3/1/2015 4 3
12345 1 4/1/2015 5 4
12345 1 9/1/2015 3 3
12345 1 10/1/2015 8 4
12345 2 1/1/2015 2 2
12345 2 2/1/2015 4 3
12345 2 3/1/2015 6 4
Rules:
Sequence should be generated for each combination of S_ID, Group_I
For the first record, sequence number will be same as the Score
2nd record onwards, this will be 1 + the previous sequence number
if the difference between the date of the previous row and current row is
more than 100 days, sequence number will be restarted (same as the
Score for that record)
This is a large table and I am looking for the most optimized SQL. Any help would be greatly appreciated
The trick here is to find where the sequence numbers start over. This is for new students, groups, and when the previous date has too big a gap. For the latter, you can use lag() to calculate a "new dates start flag" and then aggregate this to get a grouping.
select t.*,
(first_value(score) over (partition by s_id, group_id, grp order by date) +
row_number() over (partition by s_id, group_id, grp order by date) - 1
) as sequence
from (select t.*,
sum(case when prev_date is null or prev_date < date - 100
then 1 else 0
end) over (partition by s_id, group_id order by date) as grp
from (select t.*,
lag(date) over (partition by s_id, group_id order by date) as prev_date
from t
) t
) t;