What we're running into:

Engine: MySQL.

We've been working on a filter where an user can search for a reference number. However, we've ran into an issue with performance on bigger data sets.

We need to search for partial words; say we have the reference AB12345678 - the user wants to find this reference by either searching AB, B123, 1234 or any other combination which contains part of this string.

We have an INDEX on reference & date

We're currently using LIKE %STRING%, but this cannot be indexed - and performance is bad in certain situations:

(1) When we search for AB we get a fast result.

(2) When we search for AB12345678 we get a slow result.

Both situations have ORDER BY date & LIMIT.

When we turn off either ORDER BY or LIMIT with situation (2), we also get a fast result.

A slow result is around 14-15 seconds of query execution time.

The dataset contains around 300k results.

What we've tried so far:

We tried implementing FULLTEXT indexes and MATCH .. AGAINST queries, however MATCH .. AGAINST doesn't allow us to search for both sides, the * wildcard is only allowed at the end of the input string.

We've also tried removing the INDEX on date. This gave us faster results (around 1/3th of the time) however, the query still took around 4-5 seconds.

We're kinda lost on the best implementation that can improve our performance on this query and how we can best solve it right now. What method should we use to get our performance back and be able to search on both sides?

Below is part our query which has slow results (we removed the SELECT part):

FROM orders o0_
AND o0_.customer_id = 130
AND (o0_.reference LIKE '%AB12345678%')
  • Can you provide SHOW CREATE TABLE, SHOW INDEX and EXPLAIN ? We need more information to discuss. – shx Feb 21 '16 at 11:05

If you can get rid of the leading wildcard (%), do so; then we can discuss better indexes.

Meanwhile, use INDEX(customer_id, date4); it has some chance of speeding up the query.

What version are you running?

Please provide SHOW CREATE TABLE if you want to discuss this further.

  • Hi there! Thanks for the suggestion for that index. It already speed up more then half the query time, not perfect but a lot better! I can't however share more in-depth information about the table from the company, sadly. – Rocco Feb 22 '16 at 8:24

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