Postgres Query Optimization without adding an extra index - postgresql

Question

I was trying to optimize this query differently, but before that, Can we make any slight change in this query to reduce the time without adding any index?
Postgres version: 13.5
Query:
SELECT
orders.id as order_id,
orders.*, u1.name as user_name,
u2.name as driver_name,
u3.name as payment_by_name, referrals.name as ref_name,
array_to_string(array_agg(orders_payments.payment_type_name), ',') as payment_type_name,
array_to_string(array_agg(orders_payments.amount), ',') as payment_type_amount,
array_to_string(array_agg(orders_payments.reference_code), ',') as reference_code,
array_to_string(array_agg(orders_payments.tips), ',') as tips,
array_to_string(array_agg(locations.name), ',') as location_name,
(select
SUM(order_items.tax) as tax from order_items
where order_items.order_id = orders.id and order_items.deleted = 'f'
) as tax,
(select
SUM(orders_surcharges.surcharge_tax) as surcharge_tax from orders_surcharges
where orders_surcharges.order_id = orders.id
)
FROM "orders"
LEFT JOIN
users as u1 ON u1.id = orders.user_id
LEFT JOIN
users as u2 ON u2.id = orders.driver_id
LEFT JOIN
users as u3 ON u3.id = orders.payment_received_by
LEFT JOIN
referrals ON referrals.id = orders.referral_id
INNER JOIN
locations ON locations.id = orders.location_id
LEFT JOIN
orders_payments ON orders_payments.order_id = orders.id
WHERE
(orders.company_id = '626')
AND
(orders.created_at BETWEEN '2021-04-23 20:00:00' AND '2021-07-24 20:00:00')
AND
orders.order_status_id NOT IN (10, 5, 50)
GROUP BY
orders.id, u1.name, u2.name, u3.name, referrals.name
ORDER BY
created_at ASC LIMIT 300 OFFSET 0
Current Index:
"orders_pkey" PRIMARY KEY, btree (id)
"idx_orders_company_and_location" btree (company_id, location_id)
"idx_orders_created_at" btree (created_at)
"idx_orders_customer_id" btree (customer_id)
"idx_orders_location_id" btree (location_id)
"idx_orders_order_status_id" btree (order_status_id)
Execution Plan
Seems this takes more time on the parallel heap scan.

Answer 1

You're looking for 300 orders and try to get some additional information about these records. I would see if I could first get these 300 records, instead of getting all the data and then limit it to 300. Something like this:
WITH orders_300 AS (
SELECT * -- just get the columns that you really need, never use * in production
FROM orders
INNER JOIN locations ON locations.id = orders.location_id
WHERE orders.company_id = '626'
AND orders.created_at BETWEEN '2021-04-23 20:00:00' AND '2021-07-24 20:00:00'
AND orders.order_status_id NOT IN (10, 5, 50)
ORDER BY
created_at ASC LIMIT 300 -- LIMIT
OFFSET 0
)
SELECT
orders.id as order_id,
orders.*, -- just get the columns that you really need, never use * in production
u1.name as user_name,
u2.name as driver_name,
u3.name as payment_by_name, referrals.name as ref_name,
array_to_string(array_agg(orders_payments.payment_type_name), ',') as payment_type_name,
array_to_string(array_agg(orders_payments.amount), ',') as payment_type_amount,
array_to_string(array_agg(orders_payments.reference_code), ',') as reference_code,
array_to_string(array_agg(orders_payments.tips), ',') as tips,
array_to_string(array_agg(locations.name), ',') as location_name,
(SELECT SUM(order_items.tax) as tax
FROM order_items
WHERE order_items.order_id = orders.id
AND order_items.deleted = 'f'
) as tax,
( SELECT SUM(orders_surcharges.surcharge_tax) as surcharge_tax
FROM orders_surcharges
WHERE orders_surcharges.order_id = orders.id
)
FROM "orders_300" AS orders
LEFT JOIN users as u1 ON u1.id = orders.user_id
LEFT JOIN users as u2 ON u2.id = orders.driver_id
LEFT JOIN users as u3 ON u3.id = orders.payment_received_by
LEFT JOIN referrals ON referrals.id = orders.referral_id
LEFT JOIN orders_payments ON orders_payments.order_id = orders.id
GROUP BY
orders.id, u1.name, u2.name, u3.name, referrals.name
ORDER BY
created_at;
This will at least have a huge impact on the slowest part of your query, all these index scans on orders_payments. Every single scan is fast, but the query is doing 165000 of them... Limit this to just 300 and will be much faster.
Another issue is that none of your indexes covers the entire WHERE condition on the table "orders". But if you can't create a new index, you're out of luck.