Queries with LIMITs and OFFSETs are common in application that require pagination and in some cases might work well for a while. In many cases though, they become slow and painful once the OFFSET has a high value.
The important thing here, as I understand it, is that adding the limit might make your query faster, but it will not make it slower.
Queries can become slow for various reasons ranging from improper index usage to bugs in the storage engine itself. However, in most cases, queries become slow because developers or MySQL database administrators neglect to monitor them and keep an eye on their performance.
MySQL Offset is used to specify from which row we want the data to retrieve. To be precise, specify which row to start retrieving from. Offset is used along with the LIMIT. Here, LIMIT is nothing but to restrict the number of rows from the output.
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:
WHERE id > lastId limit 0,30
So you can always have a ZERO offset. You will be amazed by the performance improvement.
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.
Assuming that id
is the primary key of a MyISAM table, or a unique non-primary key field on an InnoDB 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:
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.
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 id
s (i.e. gaps).
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
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.
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.
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