(SELECT user_id, EXTRACT(MONTH FROM created_at) AS month, EXTRACT(DAY FROM created_at) AS day
FROM marketing_automation_mail_logs
GROUP BY user_id, month, day) q1
INNER JOIN
(SELECT user_id, EXTRACT(MONTH FROM created_at) AS month, EXTRACT(DAY FROM created_at) AS day
FROM referral_link_share_intents
GROUP BY user_id, month, day) q2
ON q1.user_id = q2.user_id
WHERE q1.month = q2.month AND q1.day = q2.day
I am using this query to join two tables but it shows me the syntax error near INNER JOIN. I don’t understand where I am going wrong.
use this
select * from (
SELECT user_id, EXTRACT(MONTH FROM created_at) as month, EXTRACT(DAY from created_at) as day from marketing_automation_mail_logs
group by user_id, month, day) q1
INNER JOIN
(SELECT user_id, EXTRACT(MONTH FROM created_at) as month, EXTRACT(DAY from created_at) as day FROM referral_link_share_intents
GROUP BY user_id, month, day) q2
ON q1.user_id = q2.user_id
WHERE q1.month = q2.month AND q1.day = q2.day
Related
In CockroachDB, I want to have such this query on a specific month for its every day:
select count(*), sum(amount)
from request
where code = 'code_string'
and created_at >= '2022-07-31T20:30:00Z' and created_at < '2022-08-31T20:30:00Z'
the problem is that I want it on my local date. What should I do?
My goal is:
"month, day, count, sum" as result columns for a month.
UPDATE:
I have found a suitable query for this purpose:
select count(amount), sum(amount), extract(month from created_at) as monthTime, extract(day from created_at) as dayTime
from request
where code = 'code_string' and created_at >= '2022-07-31T20:30:00Z' and created_at < '2022-08-31T20:30:00Z'
group by dayTime, monthTime
Thanks to #histocrat for easier answer :) by replacing
extract(month from created_at) as monthTime, extract(day from created_at) as dayTime
by this:
date_part('month', created_at) as monthTime, date_part('day', created_at) as dayTime
To group results by both month and day, you can use the date_part function.
select month, day, count(*), sum(things)
from request
where code = 'code_string'
group by date_part('month', created_at) as month, date_part('day', created_at) as day;
Depending on what type created_at is, you may need to cast or convert it first (for example, group by date_part('month', created_at::timestamptz)).
I need the monthly new user count and the total count of users until that month end in Oracle SQL. Can calculate monthly new users, but struggling to count total for that month.
SELECT COUNT(*) AS REGISTERED_USERS, EXTRACT(MONTH FROM ADD_DATE) AS MN, EXTRACT(YEAR FROM ADD_DATE) AS YR
FROM USERS
WHERE EXTRACT(YEAR FROM ADD_DATE) = 2020
GROUP BY EXTRACT(MONTH FROM ADD_DATE), EXTRACT(YEAR FROM ADD_DATE)
ORDER BY EXTRACT(MONTH FROM ADD_DATE);
You want a running total. You get this with SUM OVER.
SELECT yr, mn, new_users, total_users
FROM
(
SELECT
EXTRACT(YEAR FROM add_date) AS yr,
EXTRACT(MONTH FROM add_date) AS mn,
COUNT(*) AS new_users,
SUM(COUNT(*)) OVER (ORDER BY EXTRACT(YEAR FROM add_date), EXTRACT(MONTH FROM add_date)) AS total_users
FROM users
GROUP BY EXTRACT(YEAR FROM add_date), EXTRACT(MONTH FROM add_date)
)
WHERE yr = 2020
ORDER BY yr, mn;
You can use the SUM analytical function with COUNT aggregate function and running the analytical function on add_date by month as follows:
SELECT EXTRACT(YEAR FROM DT) yr, EXTRACT(MONTH FROM DT) mn, new_users, total_users
FROM
(
SELECT
TRUNC(ADD_DATE, 'MON') AS DT,
COUNT(*) AS new_users,
SUM(COUNT(*)) OVER (ORDER BY TRUNC(ADD_DATE, 'MON')) AS total_users
FROM users
GROUP BY TRUNC(ADD_DATE, 'MON')
)
WHERE EXTRACT(YEAR FROM DT) = 2020
ORDER BY YR, MN;
I am working with a default oracle scott database with additional table PROJECT, where there are there are 5 columns: projno, projname, budget, start_date, end_date.
I want to select month with the highest number of projects in a specific year.
In instruction to my exercise it is said that it must be done with correlated subquery.
I know how to do it with uncorrelated subquery:
SELECT EXTRACT(month FROM end_date) as "Month", COUNT(*) as "No of projects"
FROM proj
WHERE EXTRACT(year FROM end_date) = 2016
GROUP BY EXTRACT(month FROM end_date)
HAVING COUNT(*) = (SELECT MAX(COUNT(*))
FROM proj
WHERE EXTRACT(year FROM end_date) = 2016
GROUP BY EXTRACT(month FROM end_date))
Here is my try with correlated subquery - it doesn't work:
SELECT (EXTRACT(month FROM end_date)), COUNT(*) as "liczba"
FROM proj p
WHERE EXTRACT(year FROM end_date) = 2016
GROUP BY EXTRACT(month FROM end_date)
HAVING COUNT(*) = MAX (SELECT(COUNT(EXTRACT(month FROM proj.end_date)))
FROM proj
WHERE EXTRACT(month FROM proj.end_date) = EXTRACT(month FROM p.end_date)
AND EXTRACT(year FROM proj.end_date) = 2016)
I have SELECT:
SELECT month, year, ROUND(AVG(q_overall) OVER (rows BETWEEN 10000 preceding and current row),2) as avg
FROM (
SELECT EXTRACT(Month FROM date) as month, EXTRACT(Year FROM date) as year, ROUND(AVG(q_overall),1) as q_overall
FROM fb_parsed
WHERE business_id = 1
GROUP BY year, month
ORDER BY year, month) a
output:
month year avg
-----------------
12 2012 5
1 2013 4.5
2 2013 4.1
4 2013 4.8
5 2013 4.7
And I have to append this table with missing values (in this example with 3-rd month in 2013 year). The avg must be same as in previous row, that means I need to append this table with:
3 2013 4.1
Can I do this with SELF JOINS and generate_series, or with some UNION select?
You can simplify your select. It doesn't need a subquery:
SELECT EXTRACT(Month FROM date) as month,
EXTRACT(Year FROM date) as year,
ROUND(AVG(q_overall), 1) as q_overall,
ROUND(AVG(AVG(q_overall)) OVER (rows BETWEEN 10000 preceding and current row), 2)
FROM fb_parsed
WHERE business_id = 1
GROUP BY year, month;
The windows function needs an order by. I assume you really intend:
SELECT EXTRACT(Month FROM date) as month,
EXTRACT(Year FROM date) as year,
ROUND(AVG(q_overall), 1) as q_overall,
ROUND(AVG(AVG(q_overall)) OVER (ORDER BY year, month)), 2)
FROM fb_parsed
WHERE business_id = 1
GROUP BY year, month;
Then, to fill in the values you can use generate_series():
SELECT EXTRACT(Month FROM ym.date) as month,
EXTRACT(Year FROM ym.date) as year,
ROUND(AVG(AVG(q_overall)) OVER (ORDER BY year, month)), 2)
FROM (SELECT generate_series(date_trunc('month', min(date)),
date_trunc('month', max(date)),
interval '1 month') as date
FROM fb_parsed
) ym LEFT JOIN
fb_parsed p
ON EXTRACT(year FROM ym.date) = EXTRACT(year FROM p.date) AND
EXTRACT(month FROM ym.date) = EXTRACT(month FROM p.date) AND
p.business_id = 1
GROUP BY year, month;
I think this will do what you want.
Final query:
SELECT EXTRACT(Month FROM ym.date) as month,
EXTRACT(Year FROM ym.date) as year,
ROUND(AVG(AVG(q_overall)) OVER (ORDER BY EXTRACT(Year FROM ym.date), EXTRACT(Month FROM ym.date)), 2)
FROM
(SELECT generate_series(date_trunc('month', min(date)),
date_trunc('month', max(date)),
interval '1 month') as date
FROM fb_parsed WHERE business_id = 1 AND site = 'facebook')
ym LEFT JOIN
fb_parsed p
ON EXTRACT(year FROM ym.date) = EXTRACT(year FROM p.date) AND
EXTRACT(month FROM ym.date) = EXTRACT(month FROM p.date) AND
p.business_id = 1 AND site = 'facebook'
GROUP BY year, month;
Can I do this with SELF JOINS and generate_series?
Yep, you're close, but your current query does a Cumulative Average. The tricky part is the fill the gaps with the previous value (If PostgreSQL supported the IGNORE NULLS option of LAST_VALUE this would be easier...)
SELECT month,
year,
MAX(q_overall) -- assign the value to all rows within the same group
OVER (PARTITION BY grp)
FROM
(
SELECT all_months.month, all_months.year, p.q_overall,
-- assign a new group number whenever there's a value in q_overall
SUM(CASE WHEN q_overall IS NULL THEN 0 ELSE 1 END)
OVER (ORDER BY all_months.month, all_months.year
ROWS UNBOUNDED PRECEDING) AS grp
FROM
( -- create all months with min and max date
SELECT generate_series(date_trunc('month', min(date)),
date_trunc('month', max(date)),
interval '1 month') as date
FROM fb_parsed
) AS all_months
LEFT JOIN
( -- do the average per month calculation
SELECT EXTRACT(Month FROM date) as month,
EXTRACT(Year FROM date) as year,
ROUND(AVG(q_overall),1) as q_overall
FROM fb_parsed
WHERE business_id = 1
GROUP BY year, month
) AS p
ON EXTRACT(year FROM ym.date) = all_months.month
AND EXTRACT(month FROM ym.date) = all_months.year
) AS dt
Edit:
Oops, this was overly complicated, the question asked for a Cumulative Average and then NULLs will not change the result and there's no need to fill the gaps
I'm looking for a query that will Sum Reactivation Revenue from a given date on. Currently I have the following query;
SELECT advertisable, EXTRACT(YEAR from day), EXTRACT(MONTH from day), ROUND(SUM(cost)/1e6) FROM adcube dac
WHERE advertisable_eid IN
(SELECT advertisable FROM adcube dac
GROUP BY advertisable HAVING SUM(cost)/1e6 > 100)
GROUP BY advertisable, EXTRACT(YEAR from day), EXTRACT(MONTH from day)
ORDER BY advertisable, EXTRACT(YEAR from day), EXTRACT(MONTH from day)
From this i then export to excel and check accounts thay have stopped spending for 4 months and then reactivated. I then track the new revenue from the new reactivtion month.
Is it possible to get an SQL query to do this without need of Excel?
Thanks
Assuming the four months is actually present in the data, you can do this using window functions. You can find N things in a row by taking the difference between two row_numbers(). Here is the idea:
with t as (
SELECT advertisable, EXTRACT(YEAR from day) as yy, EXTRACT(MONTH from day) as mon,
ROUND(SUM(cost)/1e6) as val
FROM adcube dac
WHERE advertisable_eid IN (SELECT advertisable
FROM adcube dac
GROUP BY advertisable
HAVING SUM(cost)/1e6 > 100
)
GROUP BY advertisable, EXTRACT(YEAR from day), EXTRACT(MONTH from day)
)
select advertisable, min(yy * 10000 + mon) as yyyymm
from (select t.*,
(row_number() over (partition by advertisable order by yy, mon) -
row_number() over (partition by advertisable, val order by yy, mon)
) as grp
from t
)
group by advertisable, grp, val
having count(*) >= 4 and val = 0;