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Home/ Questions/Q 8674829
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Editorial Team
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Editorial Team
Asked: June 12, 20262026-06-12T19:48:03+00:00 2026-06-12T19:48:03+00:00

I’m trying to query two fairly large tables here to pull some results and

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I’m trying to query two fairly large tables here to pull some results and having some trouble with effeciency.

Note: I’ve only included relevant columns to make this not look so messy!

TableA (Stock) has productID, ownerID, and count columns

TableB (Owners) has ID, accountHolderID, and name columns

What I’m trying to do is query TableA and where productID = X pull up Stock.productID, Stock.accountHolderID and Owners.name. The relation between these two tables is Stock.ownerID = Owners.ID so if the WHERE condition pulled say five productIDs then I’d want the name from TableB that matched up to the ownerID from TableA.

The only unique ID in this situation is Owners.ID from TableB

Just doing a basic SELECT query on TableA for those products takes 15 seconds however when I add an INNER JOIN to match things up to TableB the query takes significantly longer, upwards of 10 minutes. I’m guessing I’ve designed this query inefficiently.

SELECT
Owners.name,
Stock.productID,
Stock.ownerID
FROM Stock
INNER JOIN 
Owners
ON Stock.ownerID = Owners.ID
WHERE
Stock.productID = 42301679

How can I make this query more efficient?

Would adding ORs to the WHERE condition allow me to pull multiple productIDs at once?

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  1. Editorial Team
    Editorial Team
    2026-06-12T19:48:05+00:00Added an answer on June 12, 2026 at 7:48 pm

    Based on your comment, it looks like you’re missing a very critical index on the owners.id field. Now, keep in mind this index will help this query, but you have to take into consideration all of the other queries that run against this table to determine if it is a good idea to add that index.

    At 29M rows, having an index on a table that is frequently inserted to may have a noticeable effect on insert times.

    This may be a situation where different applications need different indexes – namely your OLTP app and your reporting app (which may just be you running ad hoc queries). A common solution is to have a second server that runs your reporting/data warehouse queries that has indexes properly tuned to this function.

    Best of luck.

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