SELECT statement optimization MySQL - mysql

Question

I am looking for a way how to make my SELECT query even faster than it is now, because I have a feeling it should be possible to make it faster.
Here is the query
SELECT r.id_customer, ROUND(AVG(tp.percentile_weighted), 2) AS percentile
FROM tag_rating AS r USE INDEX (value_date_add)
JOIN tag_product AS tp ON (tp.id_pair = r.id_pair)
WHERE
r.value = 1 AND
r.date_add > '2020-08-08 11:56:00'
GROUP BY r.id_customer
Here is EXPLAIN SELECT
+----+-------------+-------+--------+----------------+----------------+---------+---------------+--------+---------------------------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+----------------+----------------+---------+---------------+--------+---------------------------------------------------------------------+
| 1 | SIMPLE | r | ref | value_date_add | value_date_add | 1 | const | 449502 | Using index condition; Using where; Using temporary; Using filesort |
+----+-------------+-------+--------+----------------+----------------+---------+---------------+--------+---------------------------------------------------------------------+
| 1 | SIMPLE | tp | eq_ref | PRIMARY | PRIMARY | 4 | dev.r.id_pair | 1 | |
+----+-------------+-------+--------+----------------+----------------+---------+---------------+--------+---------------------------------------------------------------------+
Now the tables are
CREATE TABLE `tag_product` (
`id_pair` int(10) unsigned NOT NULL AUTO_INCREMENT,
`id_product` int(10) unsigned NOT NULL,
`id_user_tag` int(10) unsigned NOT NULL,
`status` tinyint(3) NOT NULL,
`percentile` decimal(8,4) unsigned NOT NULL,
`percentile_weighted` decimal(8,4) unsigned NOT NULL,
`elo` int(10) unsigned NOT NULL,
`date_add` datetime NOT NULL,
`date_upd` datetime NOT NULL,
PRIMARY KEY (`id_pair`),
UNIQUE KEY `id_product_id_user_tag` (`id_product`,`id_user_tag`),
KEY `status` (`status`),
KEY `id_user_tag` (`id_user_tag`),
CONSTRAINT `tag_product_ibfk_5` FOREIGN KEY (`id_user_tag`) REFERENCES `user_tag` (`id`) ON DELETE CASCADE ON UPDATE CASCADE
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
CREATE TABLE `tag_rating` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`id_customer` int(10) unsigned NOT NULL,
`id_pair` int(10) unsigned NOT NULL,
`id_duel` int(10) unsigned NOT NULL,
`value` tinyint(4) NOT NULL,
`date_add` datetime NOT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `id_duel_id_pair` (`id_duel`,`id_pair`),
KEY `id_pair_id_customer` (`id_pair`,`id_customer`),
KEY `value` (`value`),
KEY `value_date_add` (`value`,`date_add`),
KEY `id_customer_value_date_add` (`id_customer`,`value`,`date_add`),
CONSTRAINT `tag_rating_ibfk_3` FOREIGN KEY (`id_pair`) REFERENCES `tag_product` (`id_pair`) ON DELETE CASCADE ON UPDATE CASCADE,
CONSTRAINT `tag_rating_ibfk_6` FOREIGN KEY (`id_duel`) REFERENCES `tag_rating_duel` (`id_duel`) ON DELETE CASCADE ON UPDATE CASCADE,
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
The table tag_product has about 250k rows and the tag_rating has about 1M rows.
My issue is that the SQL query takes about 0.8s on average on my machine. I would like to make it ideally under 0.5s while also assuming the tables can get like 10 times bigger. The amount of rows taken into play should be about the same because I have a date condition (I only want less than a month old rows).
Is this possible to make faster just by some trick (aka not restructuring my tables)? When I slightly modify (dont join the smaller table) the statement as
SELECT r.id_customer, COUNT(*)
FROM tag_rating AS r USE INDEX (value_date_add)
WHERE
r.value = 1 AND
r.date_add > '2020-08-08 11:56:00'
GROUP BY r.id_customer;
here is EXPLAIN SELECT
+----+-------------+-------+------+----------------+----------------+---------+-------+--------+---------------------------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+----------------+----------------+---------+-------+--------+---------------------------------------------------------------------+
| 1 | SIMPLE | r | ref | value_date_add | value_date_add | 1 | const | 449502 | Using index condition; Using where; Using temporary; Using filesort |
+----+-------------+-------+------+----------------+----------------+---------+-------+--------+---------------------------------------------------------------------+
it takes about 0.25s which is great. So the JOIN makes it 3x slower. Is that inevitable? I feel like since I am joining via primary key it shouldnt make a query 3x slower.
---UPDATE---
This is actually my query. The number of different id_customer values is about 1 thousand and is expected to rise, the number of rows with value=1 is exactly half. So far the query performance seems to be slowing down linearly based on the number of rows in rating table
Using adding id_pair at the end of the id_customer_value_date_add or value_id_customer_date_add index doesnt help.
SELECT r.id_customer, ROUND(AVG(tp.percentile_weighted), 2) AS percentile
FROM tag_rating AS r USE INDEX (id_customer_value_date_add)
JOIN tag_product AS tp ON (tp.id_pair = r.id_pair)
WHERE
r.value = 1 AND
r.id_customer IN (2593179,1461878,2318871,2654090,2840415,2852531,2987432,3473275,3960453,3961798,4129734,4191571,4202912,4204817,4211263,4248789,765650,1341317,1430380,2116196,3367674,3701901,3995273,4118307,4136114,4236589,783262,913493,1034296,2626574,3574634,3785772,2825128,4157953,3331279,4180367,4208685,4287879,1038898,1445750,1975108,3658055,4185296,4276189,428693,4248631,1892448,3773855,2901524,3830868,3934786) AND
r.date_add > '2020-08-08 11:56:00'
GROUP BY r.id_customer
This is EXPLAIN SELECT
+----+-------------+-------+--------+----------------------------+----------------------------+---------+----------------------------------+--------+--------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+----------------------------+----------------------------+---------+----------------------------------+--------+--------------------------+
| 1 | SIMPLE | r | range | id_customer_value_date_add | id_customer_value_date_add | 10 | | 558906 | Using where; Using index |
+----+-------------+-------+--------+----------------------------+----------------------------+---------+----------------------------------+--------+--------------------------+
| 1 | SIMPLE | tp | eq_ref | PRIMARY,status | PRIMARY | 4 | dev.r.id_pair | 1 | Using where |
+----+-------------+-------+--------+----------------------------+----------------------------+---------+----------------------------------+--------+--------------------------+
Any tips are appreciated. Thank you

Answer 1

INDEX(value, date_add, id_customer, id_pair)
Would be "covering", giving an extra boost on performance for both queries. And also for Gordon's formulation.
At the same time, get rid of these:
KEY `value` (`value`),
KEY `value_date_add` (`value`,`date_add`),
because they might get in the way of the Optimizer picking the new index. Any other queries that were using those indexes will easily use the new index.
If you are not otherwise using tag_rating.id, get rid of it and promote the UNIQUE to PRIMARY KEY.

Answer 2

Try writing the query using a correlated subquery:
SELECT r.id_customer,
(SELECT ROUND(AVG(tp.percentile_weighted), 2)
FROM tag_product tp
WHERE tp.id_pair = r.id_pair
) AS percentile
FROM tag_rating AS r
WHERE r.value = 1 AND
r.date_add > '2020-08-08 11:56:00';
This eliminates the outer aggregation which should be faster.