I have a table with:
ID (id client), date_start (subscription of SaaS), date_end (could be a date value or be NULL).
So I need a cumulative count of active clients month by month.
any idea on how to write that in Postgres and achieve this result?
Starting from this, but I don't know how to proceed
select
date_trunc('month', c.date_start)::date,
count(*)
from customer
Please check next solution:
select
subscrubed_date,
subscrubed_customers,
unsubscrubed_customers,
coalesce(subscrubed_customers, 0) - coalesce(unsubscrubed_customers, 0) cumulative
from (
select distinct
date_trunc('month', c.date_start)::date subscrubed_date,
sum(1) over (order by date_trunc('month', c.date_start)) subscrubed_customers
from customer c
order by subscrubed_date
) subscribed
left join (
select distinct
date_trunc('month', c.date_end)::date unsubscrubed_date,
sum(1) over (order by date_trunc('month', c.date_end)) unsubscrubed_customers
from customer c
where date_end is not null
order by unsubscrubed_date
) unsubscribed on subscribed.subscrubed_date = unsubscribed.unsubscrubed_date;
share SQL query
You have a table of customers. With a start date and sometimes an end date. As you want to group by date, but there are two dates in the table, you need to split these first.
Then, you may have months where only customers came and others where only customers left. So, you'll want a full outer join of the two sets.
For a cumulative sum (also called a running total), use SUM OVER.
with came as
(
select date_trunc('month', date_start) as month, count(*) as cnt
from customer
group by date_trunc('month', date_start)
)
, went as
(
select date_trunc('month', date_end) as month, count(*) as cnt
from customer
where date_end is not null
group by date_trunc('month', date_end)
)
select
month,
came.cnt as cust_new,
went.cnt as cust_gone,
sum(came.cnt - went.cnt) over (order by month) as cust_active
from came full outer join went using (month)
order by month;
Related
I am attempting to pull 10 random records from each month of this year using this query here but I get an error "ERROR: relation "c1" does not exist
"
Not sure where I'm going wrong - I think it may be I'm using Mysql syntax instead, but how do I resolve this?
My desired output is like this
Month
Another header
2021-01
random email 1
2021-01
random email 2
total of ten random emails from January, then ten more for each month this year (til November of course as Dec yet to happen)..
With CTE AS
(
Select month,
email,
Row_Number() Over (Partition By month Order By FLOOR(RANDOM()*(1-1000000+1))) AS RN
From (
SELECT
DISTINCT(TO_CHAR(DATE_TRUNC('month', timestamp ), 'YYYY-MM')) AS month
,CASE
WHEN
JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'name') = 'email'
THEN
JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'value')
END AS email
FROM form_submits_y2 fs
WHERE fs.website_id IN (791)
AND month LIKE '2021%'
GROUP BY 1,2
ORDER BY 1 ASC
)
)
SELECT *
FROM CTE C1
LEFT JOIN
(SELECT RN
,month
,email
FROM CTE C2
WHERE C2.month = C1.month
ORDER BY RANDOM() LIMIT 10) C3
ON C1.RN = C3.RN
ORDER By month ASC```
You can't reference an outer table inside a derived table with a regular join. You need to use left join lateral to make that work
I did end up finding a more elegant solution to my query here via this source from github :
SELECT
month
,email
FROM
(
Select month,
email,
Row_Number() Over (Partition By month Order By FLOOR(RANDOM()*(1-1000000+1))) AS RN
From (
SELECT
TO_CHAR(DATE_TRUNC('month', timestamp ), 'YYYY-MM') AS month
,CASE
WHEN JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'name') = 'email'
THEN JSON_EXTRACT_PATH_TEXT(json_extract_array_element_text (form_data,0),'value')
END AS email
FROM form_submits_y2 fs
WHERE fs.website_id IN (791)
AND month LIKE '2021%'
GROUP BY 1,2
ORDER BY 1 ASC
)
) q
WHERE
RN <=10
ORDER BY month ASC
I am working with members data. I have the responsible Coach, the coachee entry, exit status and date. Because some coachees might graduate/leave during a month I want to calculate a daily number and then get a monthly average of active members for each coach. That means that I need to take in the account all coachees from previous months, that are still active that current month. This is my data:
I am thinking of creating a variable first where I can get the daily active member count for each coach. This is my first approach:
with all_years as (
select y.year, m.month, d.day
from generate_series(2019, 2022) as y(year)
cross join generate_series(1, 12) as m(month)
cross join generate_series(1, 31) as d(day) --<<*not sure how to adjust for days with less than 31 days??*
select ay.*, coach, coachee, entry_status, entry_date, exit_reason, exit_date, sum(count) over (partition by ay.coach order by ay.year, ay.month, ay.day)
from all_years ay
left join table t
on --.... *not sure what I can join on in this case*;
I am open to an easier approach, this logic is just an idea.
You can cross join the list of distinct coaches with all dates to generat combinations, then bring the table with a left join:
select d.dt, c.coach, count(t.coach) no_coachees
from (select distinct coach from mytable) c
cross join generate_series('2019-01-01'::date, '2022-12-31'::date, '1 day':: interval) d(dt)
left join mytable t on t.coach = c.coach and t.entry_date <= d.dt and t.exit_date > d.dt
group by d.dt, c.coach
Then you can use another level of aggregation to get the monthly average:
select date_trunc('month', d.dt) d_month, coach, avg(no_coachees) avg_coaches
from (
select d.dt, c.coach, count(t.coach) no_coachees
from (select distinct coach from mytable) c
cross join generate_series('2019-01-01'::date, '2022-12-31'::date, '1 day':: interval) d(dt)
left join mytable t on t.coach = c.coach and t.entry_date <= d.dt and t.exit_date > d.dt
group by d.dt, c.coach
) t
group by date_trunc('month', d.dt), coach
I'm trying to make a query on PostgreSQL that gives me the top 10 jobs that take more time each month (excluding current month), I have made this query so far but it gives me duplicates on the job name. How can I filter these?
SELECT job, month, duration
FROM (
SELECT
month,
job,
duration,
ROW_NUMBER() OVER (PARTITION BY month ORDER BY duration DESC) AS RN
FROM
run_history
WHERE
owner = 'john'
) x
WHERE RN <= 10
AND month < TO_CHAR(CURRENT_DATE, 'yyyymm')
Sounds like there can be multiple rows per (owner, month, job) and you want to work with the maximum duration per month for each job.
If so, aggregate computing max(duration) first, then use row_number() on top of it:
SELECT job, month, max_duration
FROM (
SELECT month, job, max(duration) AS max_duration
, row_number() OVER (PARTITION BY month ORDER BY max(duration) DESC NULLS LAST) AS rn
FROM run_history
WHERE owner = 'john'
AND month < to_char(CURRENT_DATE, 'yyyymm')
GROUP BY month, job
) sub
WHERE rn <= 10
ORDER BY month DESC, rn;
Aside: consider integer or date instead of text for the column month: cleaner and more efficient.
I have written two queries that help in finding the minimum and maximum sales quantities for different products. Now, I need to merge these two queries using natural join to output one single table.
Query 1:
with max_quant_table as
(with maxquant_table as
(select distinct month,prod as prod, sum(quant) as quant from sales group by month,prod)
select month as month,prod as MOST_POPULAR_PROD, quant as MOST_POP_TOTAL_Q
from maxquant_table)
select t2.* from
(select month, max(MOST_POP_TOTAL_Q) maxQ FROM max_quant_table group by month order by month asc)
t1 join max_quant_table t2 on t1.month = t2.month and (t2.MOST_POP_TOTAL_Q =maxQ)
Query 2:
with min_quant_table as
(with minquant_table as
(select distinct month,prod as prod, sum(quant) as quant from sales group by month,prod)
select month as month,prod as LEAST_POPULAR_PROD, quant as LEAST_POP_TOTAL_Q
from minquant_table)
select t2.* from
(select month, min(LEAST_POP_TOTAL_Q) minQ FROM min_quant_table group by month order by month asc)
t1 join min_quant_table t2 on t1.month = t2.month and (t2.LEAST_POP_TOTAL_Q = minQ)
You are over complicating things. You don't need to join those two query (and should really stay away from a natural join), you only need to combine them. min() and max() can be used inside the same query, there is no need to run two queries to evaluate both.
You also don't need to nest CTE definitions, you can just write one after the other.
So something like this:
with quant_table as (
select month, prod, sum(quant) as sum_q
from sales
group by month, prod
), min_max as (
select month, max(sum_q) as max_q, min(sum_q) as min_q
from quant_table
group by month
)
select t1.*
from quant_table t1
join min_max t2
on t2.month = t1.month
and t1.sum_q in (t2.min_q, t2.max_q)
order by month, prod;
The condition and t1.sum_q in (t2.min_q, t2.max_q) could also be written as and (t2.max_q = t1.sum_q or t2.min_q = t1.sum_q).
The above can further be simplified by combining group by with window functions and do the calculation of the sum, min and max in a single query:
with min_max as (
select month, prod,
sum(quant) as sum_q,
max(sum(quant)) over (partition by month) as max_q,
min(sum(quant)) over (partition by month) as min_q
from sales
group by month, prod
)
select month, prod, sum_q
from min_max
where sum_q in (max_q, min_q)
order by month, prod;
I'm trying to find the # users who did action A or action B on a monthly basis.
Table: User
- id
- "creationDate"
Table: action_A
- user_id (= user.id)
- "creationDate"
Table: action_B
- user_id (= user.id)
- "creationDate"
The general idea of what I was trying to do was that I'd find the list of users who did action A in Month X and the list of users who did action B in Month X, then count how many ids are there for every month based on a generate_series of monthly dates.
I tried the following, however, the query times out when running and I'm not sure if there's any way to optimize it (or if it is even correct).
SELECT monthseries."Month", count(*)
FROM
(SELECT to_char(DAY::date, 'YYYY-MM') AS "Month"
FROM generate_series('2014-01-01'::date, CURRENT_DATE, '1 month') DAY) monthseries
LEFT JOIN
(SELECT to_char("creationDate", 'YYYY-MM') AS "Month",
id
FROM action_A) did_action_A ON monthseries."Month" = did_action_A."Month"
LEFT JOIN
(SELECT to_char("creationDate", 'YYYY-MM') AS "Month",
id
FROM action_B) did_action_B ON monthseries."Month" = did_action_B."Month"
GROUP BY monthseries."Month"
Any comments/ help would be immensely helpful!
If you want to count distinct users:
select to_char(month, 'YYYY-MM') as "Month", count(*)
from
generate_series(
'2014-01-01'::date, current_date, '1 month'
) monthseries (month)
left join (
(
select distinct date_trunc('month', "creationDate") as month, id
from action_a
) a
full outer join (
select distinct date_trunc('month', "creationDate") as month, id
from action_b
) b using (month, id)
) s using (month)
group by 1
order by 1