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
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 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 have a table called retail which stores items and their price along with date of purchase. I want to find out total monthly count of unique items sold.
This is the sql query I tried
select date_trunc('month', date) as month, sum(count(distinct(items))) as net_result from retail group by month order by date;
But I get the following error
ERROR: aggregate function calls cannot be nested
Now I searched for similar stackoverflow posts one of which is postgres aggregate function calls may not be nested and but I am unable to replicate it to create the correct sql query.
What am I doing wrong?
From your description, it doesn't seem like you need to nest the aggregate functions, the count(distinct item) construction will give you a count of distinct items sold, like so:
select date_trunc('month', date) as month
, count(distinct items) as unique_items_sold
, count(items) as total_items_sold
from retail
group by "month"
order by "month" ;
If you had a column called item_count (say if there was row in the table for each item sold, but a sale might include, say, three widgets)
select date_trunc('month', date) as month
, count(distinct items) as unique_items_sold
, sum(item_count) as total_items_sold
from retail
group by "month"
order by "month" ;
Use subqueries:
Select month, sum(citems) as net_result
from
(select
date_trunc('month', date) as month,
count(distinct(items)) as citems
from
retail
group by month
order by date
)
I am suspect your group by statement will throw an Error because your month column are condition column and you cannot put in the same level in your query so put your full expression instead.
select
month,
sum(disct_item) as net_results
from
(select
date_trunc('month', date) as month,
count(distinct items) as disct_item
from
retail
group by
date_trunc('month', date)
order by
date) as tbl
group by
month;
You cannot make nested aggregate so you wrap first count to subquery and after that in outer you make sum to do the operation.
Let's say I have an orders table with customer_id, order_total, and order_date columns. I'd like to build a report that shows all customers who haven't placed an order in the last 30 days, with a column for the total amount their last order was.
This gets all of the customers who should be on the report:
select customer, max(order_date), (select order_total from orders o2 where o2.customer = orders.customer order by order_date desc limit 1)
from orders
group by 1
having max(order_date) < NOW() - '30 days'::interval
Is there a better way to do this that doesn't require a subquery but instead uses a window function or other more efficient method in order to access the total amount from the most recent order? The techniques from How to select id with max date group by category in PostgreSQL? are related, but the extra having restriction seems to stop me from using something like DISTINCT ON.
demo:db<>fiddle
Solution with row_number window function (https://www.postgresql.org/docs/current/static/tutorial-window.html)
SELECT
customer, order_date, order_total
FROM (
SELECT
*,
first_value(order_date) OVER w as last_order,
first_value(order_total) OVER w as last_total,
row_number() OVER w as row_count
FROM orders
WINDOW w AS (PARTITION BY customer ORDER BY order_date DESC)
) s
WHERE row_count = 1 AND order_date < CURRENT_DATE - 30
Solution with DISTINCT ON (https://www.postgresql.org/docs/9.5/static/sql-select.html#SQL-DISTINCT):
SELECT
customer, order_date, order_total
FROM (
SELECT DISTINCT ON (customer)
*,
first_value(order_date) OVER w as last_order,
first_value(order_total) OVER w as last_total
FROM orders
WINDOW w AS (PARTITION BY customer ORDER BY order_date DESC)
ORDER BY customer, order_date DESC
) s
WHERE order_date < CURRENT_DATE - 30
Explanation:
In both solutions I am working with the first_value window function. The window function's frame is defined by customers. The rows within the customers' groups are ordered descending by date which gives the latest row first (last_value is not working as expected every time). So it is possible to get the last order_date and the last order_total of this order.
The difference between both solutions is the filtering. I showed both versions because sometimes one of them is significantly faster
The window function style is creating a row count within the frames. Every first row can be filtered later. This is done by adding a row_number window function. The benefit of this solution comes out when you are trying to filter the first two or three data sets. You simply have to change the filter from WHERE row_count = 1 to WHERE row_count = 2
But if you want only one single row per group you just need to ensure that the expected row per group is ordered to be the first row in the group. Then the DISTINCT ON function can delete all following rows. DISTINCT ON (customer) gives the first (ordered) row per customer group.
Try to join table on itself
select o1.customer, max(order_date),
from orders o1
join orders o2 on o1.id=o2.id
group by o1.customer
having max(o1.order_date) < NOW() - '30 days'::interval
Subqueries in select is a bad idea, because DB will execute a query for each row
If you use postgres you can also try to use CTE
https://www.postgresql.org/docs/9.6/static/queries-with.html
WITH t as (
select id, order_total from orders o2 where o2.customer = orders.customer
order by order_date desc limit 1
) select o1.customer, max(order_date),
from orders o1
join t t.id=o2.id
group by o1.customer
having max(order_date) < NOW() - '30 days'::interval
Let's say I have a table Sales
SaleID int
UserID int
Field1 varchar(10)
Created Datetime
and right now I have loaded and viewing the record with SaleID = 23
What's the right way to find out, using a stored procedure, what's the PREVIOUS and NEXT SalesID value off the current SaleID = 23, that belongs to me (UserID = 1)?
I could do a
SELECT TOP 1 *
FROM Sales
WHERE SaleID > 23 AND UserID = 1
and the same for SaleID < 23 but that's 2 SQL calls.
Is there a better way?
I'm using the SQL Server 2012.
You can get the previous/next SaleID (or any other field) by using the LAG() and LEAD() functions introduced in SQL Server 2012.
For example:
SELECT *,
LAG(SaleID) OVER (PARTITION BY UserID ORDER BY SaleID) Prev,
LEAD(SaleID) OVER (PARTITION BY UserID ORDER BY SaleID) Next
FROM Sales S
SqlFiddle
If you omit the PARTIITION BY clause in the LAG() or LEAD() functions in the answer of thepirat000's, you can find the related previous or next records according to the SaleID column.
Here is the SQL query
SELECT *,
LAG(SaleID) OVER (ORDER BY SaleID) Prev,
LEAD(SaleID) OVER (ORDER BY SaleID) Next
FROM Sales S
The PARTITION BY clause enables you to use these functions within a grouping based on UserID as in the thepirat000's code
If you want the next and previous records only for a single row, or at least for a small set of item following query can also help in terms of performance (as an answer to Eager to Learn's comment)
select
(select top 1 t.SaleID from Sales t where t.SaleID < tab1.SaleID) as prev_id,
SaleID as current_id,
(select top 1 t.SaleID from Sales t where t.SaleID > tab1.SaleID) as next_id
from Sales where SaleID = 2