I need to show how many active customers we had and the end of the year. Therefore I need to get always last year_month from the previous year. Working with PostgreSQL.
Here my SQL to get the customer base on monthly (year_month) view.
select *
from (
with data as (
select
a.brand,
a.d,
a.activations,
t.terminations,
a.activations-t.terminations count
from (select c.brand, dd.year_month d,
COALESCE(case when dd.year_month is not null then count(c.customer_number) else 0 end, 0) as activations
from generate_series(current_date - interval '8 years', current_date, '1 day') d
left join dim_date dd on dd."date" = d.d
left join r_contracts_report c on to_date(c.service_start_date, 'dd.mm.yyy') = d
where c.contract_status in ('aktiv', 'Kündigung vorgemerkt', 'gekündigt')
and c.contract in ('3048', '3049', '3050', '3055', '3056')
group by dd.year_month,
brand) a,
(select c.brand, dd.year_month d,
COALESCE(case when dd.year_month is not null then count(c.customer_number) else 0 end, 0) as terminations
from generate_series(current_date - interval '8 years', current_date, '1 day') d
left join dim_date dd on dd."date" = d.d
left join r_contracts_report c on to_date(c.termination_date, 'dd.mm.yyy') = d
where c.contract_status in ('aktiv', 'Kündigung vorgemerkt', 'gekündigt')
and c.contract in ('3048', '3049', '3050', '3055', '3056')
group by dd.year_month,
brand) t
where a.d = t.d
and a.brand = t.brand)
select
d.d year_month,
d.brand,
sum(count) over (order by d.d asc rows between unbounded preceding and current row) eop
from data d
where d.brand = '3'
) as foo
Using after "as foo" the following where clause I get the customer base for the last 12 months:
WHERE year_month >= to_char ((current_date - INTERVAL '12 months'), 'YYYY-MM')
And result looks like this:
But I always want to have only the December of the previous year. In this case it would be '2021-12'.
...
where year_month = '2021-12'
or automatically for the previous year:
...
where year_month = (extract(year from current_date) - 1)::text || '-12'
But this is a really inefficient way to get this data.
Related
I have a dataset of sales. To summarize, the structure is
client_id
date_purchase
There might be several purchases done by the same customer on different dates. There can also be several purchases done on the same date (by different or the same customer).
My goal is to get the number of customers, for any given day, that made 2 or more purchases between that day and 90 days prior.
That is, the expected output is
date_purchase
number_of_customers
2022-12-19
200
2022-12-18
194
(...)
Please note this calculates, for any given date, the number of customer with 2+ purchases between that date and 90 days prior.
I know it has something to do with a window function. But so far I have not found a way to calculate, for every window of 90 days, how many customers have done 2+ purchases.
I've tried several window functions with no success:
partition by date_purchase
range between interval '90 days' preceding and current row
So far I can't get to calculate correctly the number for each date.
Window function doesn't seem to be relevant here because there is no relationship between the rows of the same window. A simple query or a self-join query should provide the expected result.
Assuming that client_id and date_purchase are two columns of my_table :
1. Query for a given date reference_date :
SELECT a.reference_date AS date_purchase, count(*) AS number_of_customers
FROM ( SELECT reference_date , client_id
FROM my_table
WHERE date_purchase <= reference_date AND date_purchase >= reference_date - INTERVAL '90 days'
GROUP BY client_id
HAVING count(*) >= 2
) AS a
2. Query for a given interval of dates reference_date => reference_date + INTERVAL '20 days' :
SELECT a.date AS date_purchase, count(*) AS number_of_customers
FROM ( SELECT ref.date, t.client_id
FROM my_table AS t
INNER JOIN generate_series(reference_date, reference_date + INTERVAL '20 days', '1 day') AS ref(date)
ON t.date_purchase <= ref.date AND t.date_purchase >= ref.date - INTERVAL '90 days'
GROUP BY ref.date, t.client_id
HAVING count(*) >= 2
) AS a
GROUP BY a.date
ORDER BY a.date
3. Query for all the date_purchase in mytable :
SELECT a.date AS date_purchase, count(*) AS number_of_customers
FROM ( SELECT ref.date, t.client_id
FROM my_table AS t
INNER JOIN (SELECT DISTINCT date_purchase AS date FROM my_table) AS ref
ON t.date_purchase <= ref.date AND t.date_purchase >= ref.date - INTERVAL '90 days'
GROUP BY ref.date, t.client_id
HAVING count(*) >= 2
) AS a
GROUP BY a.date
ORDER BY a.date
I have a pickupDate and returnDate in my OrderHistory table. I want to extract the sum of rental days of all OrderHistory entries, grouped/ordered by month. A cte seems to be the solution but I don´t get how to implement it in my query since the cte´s i saw were refering to themselves where it says "FROM cte".
I tried something like this:
SELECT
SUM((EXTRACT (DAY FROM("OrderHistory"."returnDate")-("OrderHistory"."pickupDate")))) as traveltime
, to_char("OrderHistory"."pickupDate"::date, 'YYYY-MM') as M
FROM
"OrderHistory"
GROUP BY
M
ORDER BY
M
But the outcome doesn´t split bookings btw two months (e.g. pickupDate=27th march 2022 and returnDate=03rd of april 2022) but will assign the whole 7 days to the month of march, since the returndate is in it. It should show 4 days in march and 3 in april.
Sorry for the probably very stupid question but I am a beginner. (my code is written in postgresql btw)
PostgreSQL naming conventions
Are PostgreSQL column names case-sensitive?
use legal, lower-case names exclusively so double-quoting is not
needed.
Final result in db fiddle
Add daterange column.
alter table order_history add column date_ranges daterange;
update order_history
with a(m_begin, m_end, pickup_date) as
(select date_trunc('month', pickup_date)::date,
(date_trunc('month', pickup_date) + interval '1 month - 1 day')::date,
pickup_date from order_history)
update order_history set date_ranges =
daterange(a.m_begin, a.m_end,'[]') from a
where a.pickup_date = order_history.pickup_date;
then final query:
WITH A AS(
select
pickup_date,
return_date,
return_date - pickup_date as total,
case when return_date <# date_ranges then (return_date - pickup_date)
else ( date_trunc('month', pickup_date) + interval '1 month - 1 day')::date - pickup_date
end partial_mth
from order_history),
b as (SELECT *, a.total - partial_mth parital_not_mth FROM a)
select *,
case when to_char(pickup_date,'YYYY-MM') = to_char(return_date,'YYYY-MM')
then
sum(partial_mth) over(partition by to_char(pickup_date,'YYYY-MM')) +
sum(parital_not_mth) over (partition by to_char(return_date,'YYYY-MM'))
else sum(partial_mth) over(partition by to_char(pickup_date,'YYYY-MM'))
end
from b;
After trying different things I think I found the best answer to my question, that I want to share with the community:
WITH hier as (
SELECT
"OrderHistory"."pickupDate" as start_date
, "OrderHistory"."returnDate" as end_date
, to_char("OrderHistory"."pickupDate"::date, 'YYYY-MM') as M
FROM
"OrderHistory"
GROUP BY
1, 2, 3
ORDER BY
3
), calendar as (
select date '2022-01-01' + (n || ' days')::interval calendar_date
from generate_series(0, 365) n
)
select
to_char(calendar_date::date, 'YYYY-MM')
, count(*) as tage_gebucht
from calendar
inner join hier on calendar.calendar_date between start_date and end_date
where calendar_date between '2022-01-01' and '2022-12-31'
group by 1
order by 1;
I think this is the simplest solution I came up with.
I have a query that returns all dates between 01/01/2011 and 12/31/2041 (excluding Saturdays and sundays). It's working fine, but when I try to put the filter "TRIM(TO_CHAR(dt, 'DAY')) NOT IN ('SATURDAY', 'SUNDAY')" in the WITH, It only returns one row. Any suggestions? Please keep in mind that i'm brand new to PostgreSQL.
WITH RECURSIVE bd(dt,rn) AS
(
SELECT
TO_DATE('01/01/2011', 'MM/DD/YYYY') AS dt,
1 AS rn
UNION
SELECT
dt + 1, rn + 1
FROM
bd
WHERE
dt BETWEEN TO_DATE('01/01/2011', 'MM/DD/YYYY') AND TO_DATE('12/31/2041', 'MM/DD/YYYY') - 1
)
SELECT
dt, rn
FROM
bd
WHERE TRIM(TO_CHAR(dt, 'DAY')) NOT IN ('SATURDAY', 'SUNDAY')
No need for a recursive query. This can be done much easier using generate_series()
select t.dt::date
from generate_series(date '2011-01-01', date '2014-12-31', interval '1 day') as t(dt)
where extract(isodow from t.dt) not in (6,7);
I want to be able to generate groups of row by days, weeks, month or depending on the interval I set
Following this solution, it works when granularity is by month. But trying the interval of 1 week, no records are being returned.
This is the rows on my table
This is the current query I have for per month interval, which works perfectly.
SELECT *
FROM (
SELECT day::date
FROM generate_series(timestamp '2018-09-01'
, timestamp '2018-12-01'
, interval '1 month') day
) d
LEFT JOIN (
SELECT date_trunc('month', created_date)::date AS day
, SUM(escrow_amount) AS profit, sum(total_amount) as revenue
FROM (
select distinct on (order_id) order_id, escrow_amount, total_amount, create_time from order_item
WHERE created_date >= date '2018-09-01'
AND created_date <= date '2018-12-01'
-- AND ... more conditions
) t2 GROUP BY 1
) t USING (day)
ORDER BY day;
Result from this query
And this is the per week interval query. I will reduce the range to two months for brevity.
SELECT *
FROM (
SELECT day::date
FROM generate_series(timestamp '2018-09-01'
, timestamp '2018-11-01'
, interval '1 week') day
) d
LEFT JOIN (
SELECT date_trunc('week', created_date)::date AS day
, SUM(escrow_amount) AS profit, sum(total_amount) as revenue
FROM (
select distinct on (order_id) order_id, escrow_amount, total_amount, create_time from order_item
WHERE created_date >= date '2018-09-01'
AND created_date <= date '2018-11-01'
-- AND ... more conditions
) t2 GROUP BY 1
) t USING (day)
ORDER BY day;
Take note that I have records from October, but the result here doesn't show anything for October dates.
Any idea what I am missing here?
Results from your first query are not truncated to the begin of the week.
date_trunc('2018-09-01'::date, 'week')::date
is equal to
'2018-08-27'::date
so your join using day is not working
'2018-09-01'::date <> '2018-08-27'::date
Your query should look more like that:
SELECT *
FROM (
SELECT day::date
FROM generate_series(date_trunc('week',timestamp '2018-09-01') --series begin trunc
, timestamp '2018-11-01'
, interval '1 week') day
) d
LEFT JOIN (
SELECT date_trunc('week', created_date::date)::date AS day
, SUM(escrow_amount) AS profit, sum(total_amount) as revenue
FROM (
select distinct on (order_id) order_id, escrow_amount, total_amount, create_time from order_item
WHERE created_date::date >= date '2018-09-01'
AND created_date::date <= date '2018-11-01'
-- AND ... more conditions
) t2 GROUP BY 1
) t USING (day)
WHERE day >= '2018-09-01' --to skip days from begining of the week to the begining of the series before trunc
ORDER BY day;
I have a custom query in my Java application that looks like that:
select
to_char(search.timestamp,'Mon') as mon,
COUNT(DISTINCT(search.ip_address))
from
searches
WHERE
searches.city = 1
group by 1;
which should return all months that occur within the database, and number of distinct IP addresses within each month. However, at this point, some months do not have any entries, and they are missing in the SQL query result. How can I make sure that all of the months are displayed there, even if their count is 0?
Got it working with:
select
to_char (gs.m,'Mon') as mon,
count (distinct search.ip_address)
from
generate_series (
date_trunc('month', current_date - interval '11 month'),
current_date,
'1 month'
) gs (m)
left join searches
on date_trunc('month', search.timestamp) = gs.m AND search.city = 1
group by gs.m
order by gs.m;
select
to_char (gs.m,'Mon') as mon,
count (distinct(search.ip_address))
from
searches
right join
generate_series (
date_trunc('month', current_date - interval '1 year'),
current_date,
'1 month'
) gs (m) on date_trunc('month', search.timestamp) = gs.m
where searches.city = 1
group by gs.m
order by gs.m;
Something like this (untested):
select
months.mon
, COUNT(DISTINCT(searchs.ip_address))
from
(select
to_char(searches.timestamp,'Mon') as mon
from
searches
group by 1
) months
left join searches
on to_char(searchs.timestamp,'Mon') = months.mon
and searches.city = 1
group by 1;
And if you wanted the years in there, too, try something like this (untested):
select
months.mon
, COUNT(DISTINCT(searchs.ip_address))
from
(select
extract(year from searches.timestamp) as yr
, to_char(searches.timestamp,'Mon') as mon
, to_char(yr,'9999') || mon yrmon
from
searches
group by 1
) months
left join searches
on to_char(extract(year from searches.timestamp),'9999' ||
to_char(searchs.timestamp,'Mon') = months.yrmon
and searches.city = 1
group by 1;