I got 2 tables like Customers and Orders, in table Customers I got columns id, name, in table Orders I got columns id, customer_id, order_date.
Now I need to make one select that will return me each Customer's id, name and the last order_date.
I tried to make like this:
select
Customers.id,
Customers.name,
(select Orders.order_date from Orders where Orders.customer_id = Customer.id order by order_date desc) as last_order_date
from
Customers
But it get the wrong index and takes forever to execute.
Whats the best way to make this select in PostgreSQL?
Thanks in advanced.
If not restricting by customer_id, then the query will end up having to scan the entire orders table.
SELECT c.id
,c.name
,MAX(o.order_date) AS last_order_date
FROM Customers c
LEFT OUTER JOIN Orders o ON (o.customer_id = c.id)
GROUP BY c.id, c.name
Related
I have a table and want to calculate the percentage of total by store_id which each (category_id, store_id) subtotal represents. My code is below:
WITH
example_table (name, store_id)
AS
(
select name, store_id
from category
join film_category using (category_id)
join film using (film_id)
join inventory using (film_id)
join rental using (inventory_id)
)
SELECT name, store_id, cast(count(*) as numeric)/(SELECT count(*) FROM example_table)
FROM example_table
GROUP BY name, store_id
ORDER BY name, store_id
This code actually works, as in, it doesn't throw an error, only they're not the results I'm looking for. Here each of the subtotals is divided by the total across both stores and all 16 names. Instead, I want the subtotals divided by their respective store totals or divided by their respective name totals.
I'm wondering how to perform calculations on those subtotals in general.
Thanks in advance,
I believe you need to explore the possibilities of using aggregate functions combined with an OVER(PARTITION BY ...) e.g.
SELECT DISTINCT
name, store_id, store_id_count, name_count
FROM (
select name, store_id
, count(*) over(partition by store_id) as store_id_count
, count(*) over(partition by name) as name_count
from category
join film_category using (category_id)
join film using (film_id)
join inventory using (film_id)
join rental using (inventory_id)
) AS example_table
When using aggregate function with the over clause you get the wanted counts on each row of the result, and it seems that in this case you need this. Note that select distinct has been used simply to reduce the final number of rows returned, you might still need to use a group by but I am not sure if you do.
Once you have the needed values within the derived table (aliases as example_table) then it should be a simple matter of some arithmetic in the overall select clause.
SELECT customer.customer_id, first_name, last_name, SUM(amount)
FROM customer
INNER JOIN payment
ON customer.customer_id = payment.customer_id
GROUP BY customer.customer_id
ORDER BY customer.customer_id;
This query is giving correct answer but when I am writing
SELECT payment.customer_id, first_name, last_name, SUM(amount)
FROM customer
INNER JOIN payment
ON customer.customer_id = payment.customer_id
GROUP BY payment.customer_id
ORDER BY customer.customer_id;
It's showing up errors.
I guess that customer_id is a primary key of customer table and therefore you can select other columns from customer table when grouping by it - see https://www.postgresql.org/docs/current/sql-select.html#SQL-GROUPBY:
When GROUP BY is present, or any aggregate functions are present, it
is not valid for the SELECT list expressions to refer to ungrouped
columns except within aggregate functions or when the ungrouped column
is functionally dependent on the grouped columns, since there would
otherwise be more than one possible value to return for an ungrouped
column. A functional dependency exists if the grouped columns (or a
subset thereof) are the primary key of the table containing the
ungrouped column.
I have 3 tables users, orders and comments every tables has 10087250,24949600 and 26532000 much records, I made this query to counts comments on every order but it is taking more than half an hour to execute, how to speed up this query.
Note: there is already index on foreig_key columns.
select users.user_name, orders.id, count(comments.order_id)
from orders
inner join users on users.id=orders.user_id
inner join comments on orders.id=comments.order_id
group by comments.order_id, users.user_name, orders.id
limit 2;
For the first - probably yuo need ORDER BY clause to use it with LIMIT
If you need most commented pair you can ORDER BY count DESC
The second things comments.order_id = orders.id. Why do you use both for GROUP?
group by comments.order_id, users.user_name, orders.id
May be you can help something like this:
WITH grouped AS (
SELECT order_id AS id, count(*)
FROM comments
GROUP BY 1
ORDER BY 2 DESC
LIMIT 2
)
SELECT u.user_name, g.id, g.count
FROM grouped AS g
JOIN orders AS o ON
o.id = g.id
JOIN users AS u ON
u.id = o.user_id
This allows to avoid join all tables before filtering and grouping
You can try to use temporary tables before aggregating the records. This might help to reduce the query time. Something like this...
CREATE TEMPORARY TABLE temp_table(
...
);
INSERT INTO temp_table
SELECT users.user_name, orders.id, comments.order_id
FROM orders INNER JOIN users ON users.id = orders.user_id INNER JOIN comments ON orders.id = comments.order_id;
SELECT user_name, id, count(order_id) FROM temp_table group by order_id, user_name, id;
I think you need to reduce a unneccessary join between orders and comments tables. All you want to get from table comments is how many comments of an order, so you need to do denormalization.
It means you need to add a comments_count column into orders table, and when every a comment is added to an order, just increase it or decrease it if a comment of order is deleted.
After you add new comments_count column, you need to update comments_count for each order.
Then you can just load orders table and you already have comments count for each order.
I have a list of Matter data in Table1 that I need to query, as well as get the most recent Invoice Number in Table2 that is tied to the original Matter. I'm having extreme difficulty in joining these tables together and only getting one result for each Matter as I only want the most recent Invoice #.
Any and all help would be greatly appreciated.
Table1
Table2
RESULT
The following assigns numbers to each invoice row in order of date, and selects only the most recent. Note that this assumes InvoiceDate is stored as a date,datetime, or something else that will sort chronologically, and that in the event of two invoices for the same date, returning either will be fine. If you need to return both invoices in the event of ties, replace row_number with rank.
Select * from Table1 a
inner join
(Select *
, row_number() over (partition by MatterID order by InvoiceDate desc) as RN
from Table2) b
on a.MatterID = b.MatterID and b.RN = 1
I'm working on a query that will eventually be used as the record source for a report.
I have a customers and orders table. I want to show customer_id, order_id, and order_date in a query, but I only want to show data associated with the earliest order date for each customer. Basically, I need to show the order_id field without including it in the group by clause. If I include it in the group by clause, I get a lot more records than I want. Based on my research, the code below will work in mysql, but not ms access.
Select customer.customer_id, order.order_id, min(order.order_dt)
From customer inner join order on customer.customer_id = order.customer_id
Group by customer.customer_id
I've tried grouping by order_id in a sub query and ordering by customer then date, then using the first function in the outer query. Unfortunately, the first function doesn't work as advertised.
Any help is greatly appreciated!
Does this work for you? It should bring up the earliest orders by order date for each customer. If there is more than one order on the earliest order date for a customer, all of those orders will be shown, though, so keep it in mind.
SELECT c.customer_id, o.order_id, o.order_dt
FROM customers AS c INNER JOIN (orders AS o INNER JOIN (SELECT customer_ID, MIN([order_dt]) AS MinOrder_dt FROM Orders GROUP BY customer_id) AS d ON (o.Customer_ID = d.customer_id) AND (o.[order_dt] = d.MinOrder_dt)) ON c.customer_id = o.customer_id;
I am deriving a table with just the customer_id and the min order_dt and joining customers and orders to that to only bring up the oldest orders.