I'm trying to create a query. I have two tables
customer (customer_id)
rental (rental_date (timestamp), customer_id)
SELECT to_char( rental_date, 'Month') AS month,
(count(Distinct customer.customer_id)/
(count (distinct rental.customer_id) * 100)
) AS percentage
FROM RENTAL,customer
GROUP BY month;
But the result is zero.
When all "numbers" involved in an operation are integers, the result will be an integer too.
Try this way:
SELECT
to_char( rental_date, 'Month') AS month,
(
count(distinct customer.customer_id)::float /
(count(distinct rental.customer_id)::float * 100::float)
)
as percentage
FROM
RENTAL,customer
GROUP BY month;
Related
I have a query like this:
SELECT array_agg(candles) as candles FROM ( SELECT * FROM ... ) AS candles
UNION ALL
SELECT array_agg(trades) as trades FROM ( SELECT * FROM ... ) AS trades
UNION ALL
SELECT ...
But then I'll get rows that contain arrays, but the order of the rows doesn't necessarily match the query order.
For example, it is possible that the output will have the trades row before the candles row.
How can I get the rows in a predictable order?
Edit:
updated the query based on the answer but getting an error:
SELECT a FROM
(
SELECT 1 as o, array_agg(candles) as a
FROM (
SELECT ts, open, high, low, close, midpoint, volume
FROM exchange.binance.candles
WHERE instrument = 'BTCUSDT' AND ts >= '2022-04-01 00:00:00' AND ts < '2022-04-01 01:00:00'
ORDER BY ts) AS candles
UNION ALL
SELECT 2 as o, array_agg(trades)
FROM (
SELECT ts, price, quantity, direction
FROM exchange.binance.trades
WHERE instrument = 'BTCUSDT' AND ts >= '2022-04-01 00:00:00' AND ts < '2022-04-01 01:00:00'
ORDER BY ts) AS trades
UNION ALL
SELECT 3 as o, array_agg(kvwap)
FROM (
SELECT ts, price, "interval"
FROM exchange.binance.kvwap
WHERE instrument = 'BTCUSDT' AND "interval" IN ('M5', 'H1', 'H4') AND ts >= '2022-04-01 00:00:00' AND ts < '2022-04-01 01:00:00'
ORDER BY ts) AS kvwap
)
ORDER BY o;
the error is:
[42601] ERROR: subquery in FROM must have an alias Hint: For example, FROM (SELECT ...) [AS] foo. Position: 15
Add a column for ordering to each subquery, but don't include it in the output:
SELECT a FROM (
SELECT 1 as o, array_agg(candles) as a FROM ( SELECT * FROM ... ) c group by 1
UNION ALL
SELECT 2, array_agg(trades) FROM ( SELECT * FROM ... ) t group by 1
UNION ALL
SELECT ...
) x
ORDER BY o
Note that with UNION only the first subquery's column names are relevant - the entire union uses column names from the first subquery - so don't bother providing aliases for the others.
I'm trying to write a query that checks customer retention.
This is my query:
with users_per_month as (
select count(distinct user_id) as count_active_users,
array_agg(distinct user_id) as active_users,
date_trunc('month', user_id) as month
from app_logs
group by month
),
users_per_4_month as (
select month,
active_users,
lead(active_users) over (order by month) as lead_1,
lead(active_users, 2) over (order by month) as lead_2,
lead(active_users, 3) over (order by month) as lead_3,
lead(active_users, 4) over (order by month) as lead_4
from users_per_month
)
select *
from users_per_4_month;
But I get users in a subsequent month who were not in the first month.
like user_id 3 in March (lead_3)
this is the result:
any help will be helpful, tnx :)
It works :)
with per_month as (
select to_char(a1.device_timestamp, 'yyyy-mm') as month,
array_agg(distinct a1.user_id) as active_users
from facetune2_usage_app_background a1
group by month
),
m2 as (
select month,
active_users,
lead(active_users) over (order by month) as january_users,
lead(active_users, 2) over (order by month) as february_users,
lead(active_users, 3) over (order by month) as march_users,
lead(active_users, 4) over (order by month) as april_users
from per_month
),
m3 as (
select month,
cardinality(active_users) as num_users,
(select count(*)
from (select unnest(active_users) intersect select unnest(january_users)) t) as january_retained,
(select count(*)
from (select unnest(active_users)
intersect
select unnest(february_users)) t) as febrary_retained,
(select count(*)
from (select unnest(active_users) intersect select unnest(march_users)) t) as march_retained,
(select count(*)
from (select unnest(active_users) intersect select unnest(april_users)) t) as april_retained
from m2
)
select month,
num_users,
'100' as "0",
january_retained * 100 / num_users as "1",
febrary_retained * 100 / num_users as "2",
march_retained * 100 / num_users as "3",
april_retained * 100 / num_users as "4"
from m3
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 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;
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