Why does MYSQL higher LIMIT offset slow the query down?

Why does MYSQL higher LIMIT offset slow the query down?

Scenario in short: A table with more than 16 million records [2GB in size]. The higher LIMIT offset with SELECT, the slower the query becomes, when using ORDER BY *primary_key*
So
SELECT * FROM large ORDER BY `id` LIMIT 0, 30

takes far less than
SELECT * FROM large ORDER BY `id` LIMIT 10000, 30

That only orders 30 records and same eitherway. So it’s not the overhead from ORDER BY.
Now when fetching the latest 30 rows it takes around 180 seconds. How can I optimize that simple query?

Solutions/Answers:

Solution 1:

It’s normal that higher offsets slow the query down, since the query needs to count off the first OFFSET + LIMIT records (and take only LIMIT of them). The higher is this value, the longer the query runs.

The query cannot go right to OFFSET because, first, the records can be of different length, and, second, there can be gaps from deleted records. It needs to check and count each record on its way.

Related:  MySQL & nested set: slow JOIN (not using index)

Assuming that id is a PRIMARY KEY of a MyISAM table, you can speed it up by using this trick:

SELECT  t.*
FROM    (
        SELECT  id
        FROM    mytable
        ORDER BY
                id
        LIMIT 10000, 30
        ) q
JOIN    mytable t
ON      t.id = q.id

See this article:

Solution 2:

I had the exact same problem myself. Given the fact that you want to collect a large amount of this data and not a specific set of 30 you’ll be probably running a loop and incrementing the offset by 30.

So what you can do instead is:

  1. Hold the last id of a set of data(30) (e.g. lastId = 530)
  2. Add the condition WHERE id > lastId limit 0,30

So you can always have a ZERO offset. You will be amazed by the performance improvement.

Solution 3:

MySQL cannot go directly to the 10000th record (or the 80000th byte as your suggesting) because it cannot assume that it’s packed/ordered like that (or that it has continuous values in 1 to 10000). Although it might be that way in actuality, MySQL cannot assume that there are no holes/gaps/deleted ids.

Related:  Host is not allowed to connect to this mysql server when making a local connection [closed]

So, as bobs noted, MySQL will have to fetch 10000 rows (or traverse through 10000th entries of the index on id) before finding the 30 to return.

EDIT : To illustrate my point

Note that although

SELECT * FROM large ORDER BY id LIMIT 10000, 30 

would be slow(er),

SELECT * FROM large WHERE id >  10000 ORDER BY id LIMIT 30 

would be fast(er), and would return the same results provided that there are no missing ids (i.e. gaps).

Solution 4:

The time-consuming part of the two queries is retrieving the rows from the table. Logically speaking, in the LIMIT 0, 30 version, only 30 rows need to be retrieved. In the LIMIT 10000, 30 version, 10000 rows are evaluated and 30 rows are returned. There can be some optimization can be done my the data-reading process, but consider the following:

What if you had a WHERE clause in the queries? The engine must return all rows that qualify, and then sort the data, and finally get the 30 rows.

Related:  How to instruct SQLAlchemy ORM to execute multiple queries in parallel when loading relationships?

Also consider the case where rows are not processed in the ORDER BY sequence. All qualifying rows must be sorted to determine which rows to return.

Solution 5:

I found an interesting example to optimize SELECT queries ORDER BY id LIMIT X,Y.
I have 35million of rows so it took like 2 minutes to find a range of rows.

Here is the trick :

select id, name, address, phone
FROM customers
WHERE id > 990
ORDER BY id LIMIT 1000;

Just put the WHERE with the last id you got increase a lot the performance. For me it was from 2minutes to 1 second 🙂

Other interesting tricks here : http://www.iheavy.com/2013/06/19/3-ways-to-optimize-for-paging-in-mysql/

It works too with strings