i have a table of employees with empnum,name, age , date of join.
I need to find out count of records for the last 90 days , group by age.
How can a write a query in TSQL.
SELECT age , count(*)
from table1
where date >= DATEADD(dd,-90,GETUTCDATE())
Group by age
You can apply filter, followed by group by.
SELECT age, COUNT(*) as CountOfEmployees
FROM employees
WHERE dateOfJoin < CAST(DATEADD(dd,-90,GETDATE()) AS DATE)
group by age
It would be incorrect to save AGE, usually, it is something like DateOfBirth and you calculate the age from there.
SELECT DATEDIFF(year, DateOfBirth, getdate()), COUNT(*) as CountOfEmployees
FROM employees
WHERE CAST(DATEADD(dd,-90,GETDATE()) AS DATE) < dateOfJoin
group by DATEDIFF(year, DateOfBirth, getdate())
Related
i WanT a query to find the number of days between the longest and least tenured employee still working for the company. The output should include the number of employees with the longest-tenure, the number of employees with the least-tenure, and the number of days between both the longest-tenured and least-tenured hiring dates.
this is what i have so far,i am having trouble getting the difference to appear in output
select a.count, date_tenure
from
(
select distinct hire_date ,current_date - hire_date as date_tenure, count(id) over (partition by hire_date) as count, rank() over (order by current_date-hire_date) as rank_asc,
rank() over (order by current_date-hire_date desc) as rank_desc
from employees
where termination_date is null
order by 2 desc) a
where rank_desc = 1
or rank_asc = 1
table : employees
id
hire_date
termination_date
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 am trying to pull unique active users before a date.
So specifically, I have a date range (let's say August - November) where I want to know the cumulative unique active users on or before a day within a month.
So, the pseudocode would look something like this:
SELECT COUNT(DISTINCT USERS) FROM USER_DB
WHERE
Month = [loop through months 8-11]
AND
DAY <= [day in loop of 1:31]
The output I desire is something Like this
step-by-step demo: db<>fiddle
SELECT
mydate,
SUM( -- 3
COUNT(DISTINCT username) -- 1, 2
) OVER (ORDER BY mydate) -- 3
FROM t
GROUP BY mydate -- 2
GROUP BY your date and count the users
Because you don't want to count ALL user accesses, but only one access per user and day, you need to add the DISTINCT
This is a window function. This one aggregates all counts which where previously done cumulatively.
If you want to get unique user over ALL days (count a user only on its first access) you can filter the users with a DISTINCT ON clause first:
demo: db<>fiddle
SELECT DISTINCT ON (username)
*
FROM t
ORDER BY username, mydate
This yields:
SELECT
mydate,
SUM(
COUNT(*)
) OVER (ORDER BY mydate)
FROM (
SELECT DISTINCT ON (username)
*
FROM t
ORDER BY username, mydate
) s
GROUP BY mydate
I need to select the rows for which the difference between max(date) and the date just before max(date) is smaller than 366 days. I know about SELECT MAX(date) FROM table to get the last date from now, but how could I get the date before?
I would need a query of this kind:
SELECT code, MAX(date) - before_date FROM troncon WHERE MAX(date) - before_date < 366 ;
NB : before_date does not refer to anything and is to be replaced by a functionnal stuff.
Edit : Example of the table I'm testing it on:
CREATE TABLE troncon (code INTEGER, ope_date DATE) ;
INSERT INTO troncon (code, ope_date) VALUES
('C086000-T10001', '2014-11-11'),
('C086000-T10001', '2014-11-11'),
('C086000-T10002', '2014-12-03'),
('C086000-T10002', '2014-01-03'),
('C086000-T10003', '2014-08-11'),
('C086000-T10003', '2014-03-03'),
('C086000-T10003', '2012-02-27'),
('C086000-T10004', '2014-08-11'),
('C086000-T10004', '2013-12-30'),
('C086000-T10004', '2013-06-01'),
('C086000-T10004', '2012-07-31'),
('C086000-T10005', '2013-10-01'),
('C086000-T10005', '2012-11-01'),
('C086000-T10006', '2014-04-01'),
('C086000-T10006', '2014-05-15'),
('C086000-T10001', '2014-07-05'),
('C086000-T10003', '2014-03-03');
Many thanks!
The sub query contains all rows joined with the unique max date, and you select only ones which there differente with the max date is smaller than 366 days:
select * from
(
SELECT id, date, max(date) over(partition by code) max_date FROM your_table
) A
where max_date - date < interval '366 day'
PS: As #a_horse_with_no_name said, you can partition by code to get maximum_date for each code.