Joining on range? Wrong!

The problem I am going to describe is likely to be around since the very beginning of MySQL, however unless you carefully analyse and profile your queries, it might easily go unnoticed. I used it as one of the examples in our talk given at phpDay.it conference last week to demonstrate some pitfalls one may hit when designing schemas and queries, but then I thought it could be a good idea to publish this on the blog as well.

To demonstrate the issue let’s use a typical example – a sales query. Our data is a tiny store directory consisting of three very simple tables:

“Please excuse the crudity of this model, I didn’t have time to build it to scale or to paint it.” — Dr. Emmett Brown

I populated these tables with enough data to serve our purpose.

Our hypothetical sales query could be to figure out how many LCD TVs were sold yesterday.

Seems like a very successful day! 🙂

When we look at the data structures it looks quite good – there is index on

in

, there is index on

in

and indexes on other columns used in joins. Let’s verify how the query performed in greater detail:

Somehow this does not look as good as the sales numbers. Query matched 4103 rows, but almost 120000 were scanned. And we have proper indexes on all necessary columns! What does EXPLAIN have to say about this?

To remind – our structure design is:

In 3rd row key_len is only 4 bytes, while the full key length is 4 bytes for itm_prd_id plus 4 bytes for itm_order_timestamp, so 8 bytes in total! Also ref shows only one column being used by the last join.

How should we understand this then? Database reads all ordered items where tag is ‘lcd’, which totals to about 120000 rows as shown by the counters in SHOW STATUS output above, and then filters out those not matching the date range. A very inefficient approach! MySQL was unable to optimize those simple conditions to match both product id and date range by index and read only the relevant rows.

This affects joins only. When you use a range condition on the first (or the only) table, it works as expected: