I’m trying to optimize a report query run on an ecommerce site. I’m pretty sure that I’m doing something stupid, since this query shouldn’t be taking nearly as long to run as it does.
The query in question is:
SELECT inventories_name, inventories_code, SUM(shop_orders_inventories_qty) AS qty,
SUM(shop_orders_inventories_price) AS tot_price, inventories_categories_name,
inventories_price_list, inventories_id
FROM shop_orders
LEFT JOIN shop_orders_inventories ON (shop_orders_id = join_shop_orders_id)
LEFT JOIN inventories ON (join_inventories_id = inventories_id)
WHERE {$date_type} BETWEEN '{$start_date}' AND '{$end_date}'
AND shop_orders_x_response_code = 1
GROUP BY join_inventories_id, join_shop_categories_id
{$order}
{$limit}
It’s basically trying to get total sales per item over a period of time; values in curly brackets are filled in via a form. It works fine for a period of a couple days, but querying a time interval of a week or more can take 30 seconds+.
I feel like it’s joining way too many rows in order to calculate the aggregate values and sucking up huge amounts of memory, but I’m not sure how to limit it.
Note – I realize that I’m selecting fields which aren’t in the group by, but they correspond 1-1 with inventory ID, which is in the group by.
Any suggestions?
— Edit —
The current indices are:
inventories:
join_categories – BTREE
inventories_name, inventories_code, inventories_description – FULLTEXT
shop_orders_inventories:
shop_orders_inventories_id – BTREE
shop_orders:
shop_orders_id – BTREE
Two sequential left joins will work quite long on a big table. Try to use “join” instead of “left join” (unless you have records in shop_orders with now matching records in shop_orders_inventories or inventories) or split this query to couple of small ones. Also by using “sum” and “group by” you are forcing MySQL to create temp tables – you might want to increase MySQL cache so those tables would fit in to memory (otherwise MySQL will dump them to disk which will also increase SQL execution time).