I got a test from my lecturer, I have to make one table with 3 columns inside: prodName, Qty, and totSalesToDate. Column Qty shows how many products have been sold in the input date, and totSalesToDate indicates products have been sold during the beginning of a month until the input date. Here is the example result table:
prodName | Qty | totSalesToDate
Car | 2 | 10
Bicycle | 8 | 22
Truck | 1 | 7
Motor-cycle | 3 | 12
I have to make this table using stored procedure (TSQL) with no subqueries. So far, the queries I made is:
create procedure SalesReport #date varchar(10)
as
select p.prodName, sum(s.Qty) as Qty
from PeriodTime pt full join Sales s on pt.Time = s.Time full join Product p on s.prodID = p.prodID
where #date = pt.Date
group by p.prodName
union
select p.prodName, sum(s.Qty) as totSalesToDate
from PeriodTime pt full join Sales s on pt.Time = s.Time full join Product p on s.prodID = p.prodID
where pt.Date between '2010060' and #date and p.prodName is not null
group by p.prodName
go
But the result I get is like this:
prodName | Qty
Car | 2
Car | 10
Bicycle | 8
Bicycle | 22
Truck | 1
Truck | 7
Motor-cycle | 3
Motor-cycle | 12
Anybody can help? I've been googling around but still cannot find the answer. Thanks.
How about
create procedure SalesReport #date varchar(10)
as
select p.prodName,
SUM(CASE WHEN #date = pt.Date THEN s.Qty ELSE 0 END) as Qty,
SUM(CASE WHEN pt.Date between '2010060' and #date THEN s.Qty ELSE 0.0 END) AS totSalesToDate
from PeriodTime pt full join Sales s on pt.Time = s.Time full join Product p on s.prodID = p.prodID
group by p.prodName
go
Related
id | acct_num | name | orderdt
1 1006A Joe Doe 1/1/2021
2 1006A Joe Doe 1/5/2021
EXPECTED OUTPUT
id | acct_num | name | orderdt | id1 | acct_num1 | NAME1 | orderdt1
1 1006A Joe Doe 1/1/2021 2 1006A Joe Doe 1/5/2021
My query is the following:
Select id,
acct_num,
name,
orderdt
from order_tbl
where acct_num = '1006A'
and orderdt >= '1/1/2021'
If you always have one or two rows you could do it like this (I'm assuming the latest version of SQL Server because you said TSQL):
NOTE: If you have a known max (eg 4) this solution can be converted to support any number by changing the modulus and adding more columns and another join.
WITH order_table_numbered as
(
SELECT ID, ACCT_NUM, NAME, ORDERDT,
ROW_NUMBER() AS (PARTITION BY ACCT_NUM ORDER BY ORDERDT) as RN
)
SELECT first.id as id, first.acct_num as acct_num, first.num as num, first.order_dt as orderdt,
second.id as id1, second.acct_num as acct_num1, second.num as num1, second.order_dt as orderdt1
FROM order_table_numbered first
LEFT JOIN order_table_numbered second ON first.ACCT_NUM = second.ACCT_NUM and (second.RN % 2 = 0)
WHERE first.RN % 2 = 1
If you have an unknown number of rows I think you should solve this on the client OR convert the groups to XML -- the XML support in SQL Server is not bad.
The code below gives me the following results
Early: 7738
Late: 6586
On Time: 1720
How would I take this a step further and add a third column that finds the percentages?
Here is a link to the ERD and database set-up: https://www.postgresqltutorial.com/postgresql-sample-database/
WITH
t1
AS
(
SELECT *, DATE_PART('day', return_date - rental_date) AS days_rented
FROM rental
),
t2
AS
(
SELECT rental_duration, days_rented,
CASE WHEN rental_duration > days_rented THEN 'Early'
WHEN rental_duration = days_rented THEN 'On Time'
ELSE 'Late'
END AS rental_return_status
FROM film f, inventory i, t1
WHERE f.film_id = i.film_id AND t1.inventory_id = i.inventory_id
)
SELECT rental_return_status, COUNT(*) AS total_films_rented
FROM t2
GROUP BY 1
ORDER BY 2 DESC;
You can use a window function with one CTE table (instead of 2):
WITH raw_status AS (
SELECT rental_duration - DATE_PART('day', return_date - rental_date) AS days_remaining
FROM rental r
JOIN inventory i ON r.inventory_id=i.inventory_id
JOIN film f on f.film_id=i.film_id
)
SELECT CASE WHEN days_remaining > 0 THEN 'Early'
WHEN days_remaining = 0 THEN 'On Time'
ELSE 'Late' END AS rental_status,
count(*),
(100*count(*))/sum(count(*)) OVER () AS percentage
FROM raw_status
GROUP BY 1;
rental_status | count | percentage
---------------+-------+---------------------
Early | 7738 | 48.2298678633757168
On Time | 1720 | 10.7205185739217153
Late | 6586 | 41.0496135627025679
(3 rows)
Disclosure: I work for EnterpriseDB (EDB)
Use a window function to get the sum of the count column (sum(count(*)) over ()), then just divide the count by that (count(*)/sum(count(*)) over ()). Multiply by 100 to make it a percentage.
psql (12.1 (Debian 12.1-1))
Type "help" for help.
testdb=# CREATE TABLE faket2 AS (
SELECT 'early' AS rental_return_status UNION ALL
SELECT 'early' UNION ALL
SELECT 'ontime' UNION ALL
SELECT 'late');
SELECT 4
testdb=# SELECT
rental_return_status,
COUNT(*) as total_films_rented,
(100*count(*))/sum(count(*)) over () AS percentage
FROM faket2
GROUP BY 1
ORDER BY 2 DESC;
rental_return_status | total_films_rented | percentage
----------------------+--------------------+---------------------
early | 2 | 50.0000000000000000
late | 1 | 25.0000000000000000
ontime | 1 | 25.0000000000000000
(3 rows)
I have data:
id | price | date
1 | 25 | 2019-01-01
2 | 35 | 2019-01-01
1 | 27 | 2019-02-01
2 | 37 | 2019-02-01
Is it possible to write such query which will return only first row from window? something like LIMIT 1 but for the window OVER( date )?
I expect next result:
id | price | date
1 | 25 | 2019-01-01
1 | 27 | 2019-02-01
Or ignore whole window if first window row has NULL:
id | price | date
1 | NULL | 2019-01-01
2 | 35 | 2019-01-01
1 | 27 | 2019-02-01
2 | 37 | 2019-02-01
result:
1 | 27 | 2019-02-01
Order the rows by date and id, and take only the first row per date.
Then remove those where the price is NULL.
SELECT *
FROM (SELECT DISTINCT ON (date)
id, price, date
FROM mytable
ORDER BY date, id
) AS q
WHERE price IS NOT NULL;
#Laurenz let me to provide a bit more explanation
select distinct on (<fldlist>) * from <table> order by <fldlist+>;
is equal to much more complex query:
select * from (
select row_number() over (partition by <fldlist> order by <fldlist+>) as rn,*
from <table>)
where rn = 1;
And here <fldlist> should be the beginning part (or equal) of <fldlist+>
As Myon on IRC said:
if you want to use a window function in WHERE, you need to put it into a subselect first
So the target query is:
select * from (
select
*
agg_function( my_field ) OVER( PARTITION BY other_field ) as agg_field
from sometable
) x
WHERE agg_field <condition>
In my case I have next query:
SELECT * FROM (
SELECT *,
FIRST_VALUE( p.price ) over( PARTITION BY crate.app_period ORDER BY st.DEPTH ) AS first_price,
ROW_NUMBER() over( PARTITION BY crate.app_period ORDER BY st.DEPTH ) AS row_number
FROM st
LEFT JOIN price p ON <COND>
LEFT JOIN currency_rate crate ON <COND>
) p
WHERE p.row_number = 1 AND p.first_price IS NOT null
Here I select only first rows from the group and where price IS NOT NULL
I am new at postgresql and am having trouble wrapping my mind around why I am getting the results that I see.
I perform the following query
SELECT
name AS region_name,
COUNT(tripsq1.id) AS trips,
COUNT(DISTINCT user_id) AS unique_users,
COUNT(case when consumed_at = start_at then tripsq1.id end) AS first_day,
(SUM(case when consumed_at = start_at then tripsq1.id end)::NUMERIC(6,4))/COUNT(tripsq1.id)::NUMERIC(6,4) AS percent_on_first_day
FROM promotionsq1
INNER JOIN couponsq1
ON promotion_id = promotionsq1.id
INNER JOIN tripsq1
ON couponsq1.id = coupon_id
INNER JOIN regionsq1
ON regionsq1.id = region_id
WHERE promotion_name = 'TestPromo'
GROUP BY region_name;
and get the following result
region_name | trips | unique_users | first_day | percent_on_first_day
-------------------+-------+--------------+-----------+-----------------------
A | 3 | 2 | 1 | 33.3333333333333333
B | 1 | 1 | 0 |
C | 1 | 1 | 1 | 2000.0000000000000000
The first rows percentage gets calculated correctly while the third rows percentage is 20 times what it should be. The percent_on_first_day should be 100.00 since it is 100.0 * 1/1.
Any help would be greatly appreciated
I'm suspecting that the issue is because of this code:
SUM(case when consumed_at = start_at then tripsq1.id end)
This tells me you are summing the ids, which is meaningless. You probably want:
SUM(case when consumed_at = start_at then 1 end)
sorry for the bad title, I don't know how to describe my problem.
I have the following table:
| ItemID | Date |
-------------------------
| 1 | 01.01.10 |
| 1 | 03.01.10 |
| 1 | 05.01.10 |
| 1 | 06.01.10 |
| 1 | 10.01.10 |
| 2 | 05.01.10 |
| 2 | 10.01.10 |
| 2 | 20.01.10 |
Now I want to GROUP BY ItemID and for the date I want to get the value, which excesses 60%. What I mean is, that for item 1 I've five rows, so each have a percentage of 20% and for item 2 I've three row, so each have a percentage of 33,33%. So for item 1 I need the 3rd and for item 2 the 2nd value, so that the result looks like that.
| ItemID | Date |
-------------------------
| 1 | 06.01.10 |
| 2 | 10.01.10 |
Is there a easy way so get this data? Maybe using OVER?
Thank you
Torben
with NumItems as
( select itemID, count(*) as numOfItems from table group by itemID)
),
rowNums as
(
select itemID,Date, row_number() over (partition by ItemID order by date asc) as rowNum
from table
)
select itemID, min(Date) from
rowNums a inner join NumItems b on a.itemID = b.ItemID
where cast(b.rowNum as float) / cast(numOfItems as float) >= 0.6
group by itemID
that should do it although I am certain It can be writter with only one table scan. That should work nice though.
The provided the script contained a few errors. Below is a working one:
with NumItems as
(
select itemID, count(*) as numOfItems from table group by itemID
),
rowNums as
(
select itemID, Date, row_number() over (partition by ItemID order by date asc) as rowNum
from table
)
select a.itemID, min(a.Date) from
rowNums a inner join NumItems b on a.itemID = b.ItemID
where cast(a.rowNum as float) / cast(numOfItems as float) >= 0.6
group by a.itemID