I have two tables:
Orders
======
id total_price created_on
1 100 2021-01-22
2 200 2021-01-23
Items
=====
id order_id
11 1
12 1
13 2
I want to create a query to get revenue by date. For this i'm going to sum up total price in order and grouping it up by date. Along with revenue, I also want to get total numbers of orders and items for that date. Here's a query that I wrote:
SELECT
count(orders.id) as orders,
sum(orders.total_price) as billing,
DATE(CREATED_ON) as created_on
FROM
orders
WHERE orders.deleted_on IS NULL
group by Date(orders.created_on);
Now I found 2 problems:
The count of orders is coming incorrect. Not sure what. i'm doing wrong here.
How can I calculate the count of items also in same query ?
I'm learning sql and this seems a big difficult to get my head around. Thanks for your help.
As Items.order_id is foreign key to Order.id as a result we need to join both tables first.
SELECT count(order_id) AS orders,sum(total_price) AS billing,Orders.created_on as created_on FROM Orders,(select order_id from Items) as new WHERE Orders.id=new.order_id GROUP BY created_on;
This is tricky, because when you combine the items you might multiple the revenue. One method is to aggregate the items before joining to orders:
SELECT DATE(o.Created_On) as created_on_date,
COUNT(*) as num_orders,
SUM(i.num_items) as num_items,
SUM(o.total_price) as billing
FROM orders o LEFT JOIN
(SELECT i.order_id, COUNT(*) as num_items
FROM items i
GROUP BY i.order_id
) i
ON i.order_id = o.id
WHERE o.deleted_on IS NULL
GROUP BY DATE(o.created_on);
Note: This uses a LEFT JOIN because you have not specified that all orders have items. If all do then an INNER JOIN would suffice.
Related
I have two tables, let's say OrderPlaced and OrderDelivered.
The OrderPlaced table looks like this:
In a single order we can have multiple products(which is defined by sku in the table) and each product can have multiple quantity.
The OrderDelivered table looks like this:
So technically 3 products have not been delivered. Orderid 1000 - product S101, Orderid 1001 - product S102(as 3 quantity required, but 2 delivered) and Orderid 1002 - product S100.
I am trying to write a SQL query that can give me the OrderId and sku those have not been delivered. For now I have written something like
select OrderPlaced.orderid,OrderPlaced.sku
from OrderPlaced
left join OrderDelivered
on OrderPlaced.Orderid = OrderDelivered.orderid and OrderPlaced.sku = OrderDelivered.sku
where OrderDelivered.sku is NULL;
This is giving me Orderid 1000 - product S101 and Orderid 1002 - product S100, but Orderid 1001 - product S102 is missing. I understand I have to do a check on qty as well, but couldn't think how to do that. I would really appreciate it if someone can help me with that part.
Add up the deliveries per order and sku and then outer join the delivered quantities to the order table so you can compare the quantities.
select
p.orderid,
p.sku,
p.qty as ordered,
coalesce(d.sum_qty, 0) as delivered
from orderplaced p
left join
(
select orderid, sku, sum(qty) as sum_qty
from orderdelivered
group by orderid, sku
) d on d.orderid = p.orderid and d.sku = p.sku
where p.qty > coalesce(d.sum_qty, 0)
order by p.orderid, p.sku;
Your query works for any items that have not been delivered at all, this is your WHERE OrderDelivered.sku IS NULL. But you can also have a scenario in which fewer items are delivered than ordered, and importantly, you can have multiple records related to your deliveries even if they refer to the same order and sku (two rows with 1 qty each).
In this case you will need to sum up all the deliveries per placed order id, sku and quantity (GROUP BY clause in the query below) check if that sum (or 0 if nothing is found) differs from the placed order (HAVING clause). You could use such a query:
SELECT OrderPlaced.orderid, OrderPlaced.sku,
OrderPlaced.qty - COALESCE(SUM(OrderDelivered.qty), 0) AS qty_missing,
CASE
WHEN SUM(OrderDelivered.qty) IS NULL
THEN 'Yes'
ELSE 'No'
END AS is_missing_completely
FROM OrderPlaced
LEFT
JOIN OrderDelivered
ON OrderPlaced.Orderid = OrderDelivered.orderid
AND OrderPlaced.sku = OrderDelivered.sku
GROUP BY OrderPlaced.orderid, OrderPlaced.sku, OrderPlaced.qty
HAVING OrderPlaced.qty != COALESCE(SUM(OrderDelivered.qty), 0)
Here's a live demo on dbfiddle
I would create two aggregated representations of your ordered and delivered products, and then outer join them to get the differences. If you are using MySql 8 you can represent these as a CTE, otherwise just use two equivalent sub-queries
with op as (
select OrderId, Sku, Sum(qty) Qty
from OrderPlaced
group by OrderId, Sku
), od as (
select OrderId, Sku, Sum(qty) Qty
from OrderDelivered
group by OrderId, Sku
)
select op.OrderId, op.Sku, op.Qty - Coalesce(od.qty,0) notDelivered
from op
left join od on od.orderid = op.orderid and od.sku = op.sku
where op.Qty - Coalesce(od.qty,0)>0;
Example DB<>Fiddle
I have one Parent table(Order) and one child table(Item). One user can order multiple orders in one day and one order may have multiple Item.
My table structure like,
I would like to get result like, in one how many orders and Items have ordered by particular user.
I need result like
Thank you.
Try to use distinct count for the count columns, and grouping by user_id is enough as :
select o.user_id as "User Id",
count(distinct o.id_order) as "Count(Order)",
count(distinct i.id_item) as "Count(Item)",
max("date") as "Date"
from orders o
join item i on o.id_order = i.id_order
group by user_id;
User Id Count(Order) Count(Item) Date
------- ------------ ----------- ----------
1 3 7 22.11.2018
Rextester Demo
You have to use INNER JOIN for user,order and item table. also use GROUP BY clause for group each date and order.
SELECT user_id,
count(o.id_order),
count(item.id_item)
FROM USER
INNER JOIN
`ORDER` o ON user.id=o.id_order
INNER JOIN item i ON o.id_order=o.id_order
GROUP BY o.Date, o.id_order
I want to know how many customers placed more than 1 order, grouped by day.
But I want to exclude orders that have been cancelled.
I have a customer table with customers
I have a customer_order table with orders (when an order is cancelled
it stays in the customer_order table)
I have an order_item table (where original orders are, and also
cancelled orders, cancelled orders get a new credit order, and the
original order id appears in the id_credit_order row of the credit
order)
I want something like this:
date | no of customers with 1 order | no of customers with 2 orders | no of customers with 3 order | etc.
But I want no count if the original order has been cancelled!
I have now this query, but its definitely not enough, does someone know how to get my result? thanks!
SELECT DATE(co.date_order), COUNT(co.id_customer)
FROM customer_order co
GROUP BY DATE(co.date_order)
ORDER BY DATE(co.date_order) DESC;
The question is slightly misleading, as you first ask for the number of customers with more than one order, then you ask for the number of customer with each of 1, 2, 3... orders.
Here's something that will give you the numbers, but unpivoted. You'll need to put the right column name in for o.id
Select -- outer query takes each order count and counts how many customers have that many
co.date_order,
co.customer_order_count,
count(*) as customer_count
From (
Select -- inner query counts how many valid orders each customer has
o.date_order,
o.id_customer,
count(*) as customer_order_count
From
customer_order o
Where
o.id_credit_order is null and -- rule out credit orders
not exists ( -- rule out orders with related credit orders
select
'x'
from
customer_order c
where
c.id_credit_order = o.id -- column name isn't mentioned in the question
)
Group By
o.date_order,
o.id_customer
) co
Group By
co.date_order,
co.customer_order_count
Order By
co.date_order desc,
co.customer_order_count
Try using a HAVING clause.
SELECT DATE(co.date_order), COUNT(co.id_customer)
FROM customer_order co
WHERE co.Cancelled = 0
GROUP BY DATE(co.date_order)
HAVING COUNT(co.id_customer) >= 1
ORDER BY DATE(co.date_order) DESC;
Give this a try. Change the WHERE to reflect how you cancel orders.
SELECT DATE(co.date_order), COUNT(co.id_customer)
FROM customer_order co
WHERE co.cancelled = 0
GROUP BY DATE(co.date_order)
HAVING COUNT(co.id_customer) > 0
ORDER BY DATE(co.date_order) DESC;
This is my query:
SELECT `products`.*, SUM(orders.total_count) AS revenue,
SUM(orders.quantity) AS qty, ROUND(AVG(product_reviews.stars)) as avg_stars
FROM `products`
LEFT JOIN `orders`
ON (`products`.`id` = `orders`.`product_id`) AND
(`orders`.`status` = 'delivered' OR `orders`.`status` = 'new')
LEFT JOIN product_reviews
ON (products.id = product_reviews.product_id)
GROUP BY `products`.`ID`
ORDER BY products.ID DESC
LIMIT 10
OFFSET 0
When I have this second left join, my first left joins data, revenue and qty from orders table gives me values that are not true at all (way too high, many doubles?)
From this question.
I got the direction that I am getting a semi-cartesian product, so two reviews for a product is doubling the quantities, and I believe this is my problem.
How can this be solved?
The problem is that the product_reviews and orders table can have more that one row per product id. One way you can fix this is to use a subquery:
SELECT `products`.*,
o.revenue,
o.qty,
ROUND(avg_stars) as avg_stars
FROM `products`
LEFT JOIN
(
select `product_id`,
sum(total_count) revenue,
sum(quantity) qty
from `orders`
where `status` in ('delivered', 'new')
group by `product_id`
) o
ON `products`.`id` = o.`product_id`
LEFT JOIN
(
select product_id, avg(stars) avg_stars
from product_reviews
group by product_id
) pr
ON (products.id = pr.product_id)
ORDER BY products.ID DESC
LIMIT 10
OFFSET 0
Its not easy to solve this without seeing your table schemas,
I would suggest you look at your Aggregations and Group By statements first, then look at your column default values, how are you handling empty values, also look at DISTINCT in the Aggregation functions.
If all else fails and a "optimized" solution is not vital and your data volumes are low do a Sub Select only on the tables for which you require the values, within the Sub Select on 1 table you have a much narrower row scope and it will yield the correct result.
I would suggest that you supply your table schemas here.
One approach to avoid that problem is to use correlated subquery in the SELECT list, rather than a left join.
SELECT p.*
, SUM(o.total_count) AS revenue
, SUM(o.quantity) AS qty
, ( SELECT ROUND(AVG(r.stars))
FROM `product_reviews` r
WHERE r.product_id = p.id
) AS avg_stars
FROM `products` p
LEFT
JOIN `orders` o
ON o.product_id = p.id
AND o.status IN ('delivered','new')
GROUP BY p.id
ORDER BY p.id DESC
LIMIT 10
OFFSET 0
This isn't the only approach, and it's not necessarily the best approach, especially with large sets But given that the subquery will run a maximum of 10 times (given the LIMIT clause), performance should be reasonable (given an appropriate index on product_reviews(product_id,stars).
If you were returning all product ids, or a significant percentage of them, then using an inline view might give better performance (avoiding the nested loops execution of the correlated subquery in the select list)
SELECT p.*
, SUM(o.total_count) AS revenue
, SUM(o.quantity) AS qty
, s.avg_stars
FROM `products` p
LEFT
JOIN `orders` o
ON o.product_id = p.id
AND o.status IN ('delivered','new')
LEFT
JOIN ( SELECT ROUND(AVG(r.stars)) AS avg_stars
, r.product_id
FROM `product_reviews` r
GROUP BY r.product_id
) s
ON s.product_id = p.id
GROUP BY p.id
ORDER BY p.id DESC
LIMIT 10
OFFSET 0
Just to be clear: the issue with the original query is that every order for a product is getting matched to every review for the product.
I apologize if my use of the term "semi-cartesian" was misleading or confusing.
The idea that I meant to convey by that was that you had two distinct sets (the set of orders for a product, and the set of reviews for a product), and that your query was generating a "cross product" of those two distinct sets, basically "matching" every order to every review (for a particular product).
For example, given three rows in reviews for product_id 101, and two rows in orders for product_id 101, e.g.:
REVIEWS
pid stars text
--- ----- --------------
101 4.5 woo hoo perfect
101 3 ehh
101 1 totally sucked
ORDERS
pid date qty
--- ----- ---
101 1/13 100
101 1/22 7
Your original query is essentially forming a result set with six rows in it, each row from order being matched to all three rows from reviews:
id date qty stars text
--- ---- ---- ---- ------------
101 1/13 100 4.5 woo hoo perfect
101 1/13 100 3 ehh
101 1/13 100 1 totally sucked
101 1/22 7 4.5 woo hoo perfect
101 1/22 7 3 ehh
101 1/22 7 1 totally sucked
Then, when the SUM aggregate on qty gets applied, the values returned are way bigger than you expect.
I have 3 tables:
Orders
- id
- customer_id
Details
- id
- order_id
- product_id
- ordered_qty
Parcels
- id
- detail_id
- batch_code
- picked_qty
Orders have multiple Details rows, a detail row per product.
A detail row has multiple parcels, as 10'000 ordered qty may come from 6 different batches, so goods from batches are packed and shipped separately. The picked quantity put in each parcel for a detail row should then be the same as the ordered_qty.
... hope that makes sense.
Im struggling to write a query to provide summary information of all of this.
I need to Group By customer_id to provide a row of data per customer.
That row should contain
Their total number of orders
Their total ordered_qty of goods across all orders
Their total picked_qty of goods across all orders
I can get the first one with:
SELECT customer_id, COUNT(*) as number_of_orders
FROM Orders
GROUP BY Orders.customer_id
But when I LEFT JOIN the other two tables and add the
SELECT ..... SUM(Details.ordered_qty) AS total_qty_ordered,
SUM(Parcels.picked_qty) AS total_qty_picked
.. then I get results that dont seem to add up for the quantities, and the COUNT(*) seems to include the additional lines from the JOIN which obviously then isn't giving me the number of Orders anymore.
Not sure what to try next.
===== EDIT =======
Here's the query I tried:
SELECT
customer_id,
COUNT(*) as number_of_orders,
SUM(Details.ordered_qty) AS total_qty_ordered,
SUM(Parcels.picked_qty) AS total_qty_picked
FROM Orders
LEFT JOIN Details ON Details.order_id=Order.id
LEFT JOIN Parcels ON Parcels.detail_id=Detail.id
GROUP BY Orders.customer_id
try COUNT(distinct Orders.order_id) as number_of_orders,
as in
SELECT
customer_id,
COUNT(distinct Orders.order_id) as number_of_orders,
SUM(Details.ordered_qty) AS total_qty_ordered,
(select SUM(Parcels.picked_qty)
FROM Parcels WHERE Parcels.detail_id=Detail.id ) AS total_qty_picked
FROM Orders
LEFT JOIN Details ON Details.order_id=Order.id
GROUP BY Orders.customer_id
EDIT: added an other select with subselect
Is there any particular reason you feel the need to combine all these in one query? Simplify by breaking it up in to separate queries, and if you want a single call to get the results, put the queries in a stored procedure, using temp tables.