MySQL对多个表计数是唯一的

Question

I have two tables:

products            product_eans
+--+-----------+    +----------+-------------+
|id|name       |    |product_id|ean          |
+--+-----------+    +----------+-------------+
| 1|hello world|    |         1|4053804303361|
+--+-----------+    +----------+-------------+
| 2|hello mars |    |         1|4053804304788|
+--+-----------+    +----------+-------------+
                    |         2|4053804304825|
                    +----------+-------------+

I now want to count the (unique) products that has the string 4788 in their name or in one of their EANs. The result in the example would be 1 (one product has an EAN that contains the search string 4788 )

I have managed this with

SELECT
        COUNT(DISTINCT products.id) AS count
    FROM
        products
    WHERE
        products.name LIKE "%4788%" OR 
        (SELECT
            GROUP_CONCAT(ean)
        FROM
            product_eans
        WHERE
            product_id = product.id) LIKE "%4788%"`

but it's incredible with thousands of rows in both tables.

What is the most efficient way for a query like this?

Answer 1

Using "double-ended wildcards" is never going to be fast because you won't get use of indexing so the tables will be scanned. An inner join is probably the most efficient

SELECT COUNT(DISTINCT e.products_id)
FROM product_eans e
inner join products p on e.products_id = p.id
WHERE e.ean LIKE '%4788%'
OR p.name LIKE '%4788%'

but one other possibility is to avoid the OR in tha wheer clause by using a union query like this:

  SELECT
        COUNT(*)
  FROM (
        SELECT
              product_id
        FROM product_eans
        WHERE ean LIKE '%4788%'
        UNION
        SELECT
              id
        FROM products
        WHERE name LIKE '%4788%'
  ) d

Answer 2

After being inspired by Used_By_Already, I came across a simple idea:

SELECT
    COUNT(DISTINCT products.id) AS count
FROM
    products
WHERE
    products.name LIKE "%4788%" OR
    products.id in (SELECT product_id FROM product_eans WHERE ean "%4788%")

It's super fast now. So thanks to Used_By_Already.