how group by having limit works - mysql

Can someone explain how construction group by + having + limit exactly work? MySQL query:
SELECT
id,
avg(sal)
FROM
StreamData
WHERE
...
GROUP BY
id
HAVING
avg(sal)>=10.0
AND avg(sal)<=50.0
LIMIT 100
Query without limit and having clauses executes for 7 seconds, with limit - instantly if condition covers a large amount of data or ~7 seconds otherwise.
Documentation says that limit executes after having which after group by, this means that query should always execute for ~7 seconds. Please help to figure out what is limited by LIMIT clause.

Using LIMIT 100 simply tells MySQL to return only the first 100 records from your result set. Assuming that you are measuring the query time as the round trip from Java, then one component of the query time is the network time needed to move the result set from MySQL across the network. This can take a considerable time for a large result set, and using LIMIT 100 should reduce this time to zero or near zero.

Things are logically applied in a certain pipeline in SQL:
Table expressions are generated and executed (FROM, JOIN)
Rows filtered (WHERE)
Projections and aggregations applied (column list, aggregates, GROUP BY)
Aggregations filtered (HAVING)
Results limited (LIMIT, OFFSET)
Now these may be composed into a different execution order by the planner if that is safe but you always get the proper data out if you think through them in this order.
So group by groups, then these are filtered with having, then the results of that are truncated.

As soon as MySQL has sent the required number of rows to the client,
it aborts the query unless you are using SQL_CALC_FOUND_ROWS. The
number of rows can then be retrieved with SELECT FOUND_ROWS(). See
Section 13.14, “Information Functions”.
http://dev.mysql.com/doc/refman/5.7/en/limit-optimization.html
This effectively means that if your table has a rather hefty number of rows, the server doesn't need to look at all of them. It can stop as soon as it has found a 100 because it knows that's all that you need.

Related

What is the fastest way to count the number of MySql rows left after a limited results query

If I have a mysql limited query:
SELECT * FROM my_table WHERE date > '2020-12-12' LIMIT 1,16;
Is there a faster way to check and see how many results are left after my limit?
I was trying to do a count with limit, but that wasn't working, i.e.
SELECT count(ID) AS count FROM my_table WHERE date > '2020-12-12' LIMIT 16,32;
The ultimate goal here is just to determine if there ARE any other rows to be had beyond the current result set, so if there is another faster way to do this that would be fine too.
It's best to do this by counting the rows:
SELECT count(*) AS count FROM my_table WHERE date > '2020-12-12'
That tells you how many total rows match the condition. Then you can compare that to the size of the result you got with your query using LIMIT. It's just arithmetic.
Past versions of MySQL had a function FOUND_ROWS() which would report how many rows would have matched if you didn't use LIMIT. But it turns out this had worse performance than running two queries, one to count rows and one to do your limit. So they deprecated this feature.
For details read:
https://www.percona.com/blog/2007/08/28/to-sql_calc_found_rows-or-not-to-sql_calc_found_rows/
https://dev.mysql.com/worklog/task/?id=12615
(You probably want OFFSET 0, not 1.)
It's simple to test whether there ARE more rows. Assuming you want 16 rows, use 1 more:
SELECT ... WHERE ... ORDER BY ... LIMIT 0,17
Then programmatically see whether it returned only 16 rows (no more available) or 17 (there ARE more).
Because it is piggybacking on the fetch you are already doing and not doing much extra work, it is very efficient.
The second 'page' would use LIMIT 16, 17; 3rd: LIMIT 32,17, etc. Each time, you are potentially getting and tossing an extra row.
I discuss this and other tricks where I point out the evils of OFFSET: Pagination
COUNT(x) checks x for being NOT NULL. This is [usually] unnecessary. The pattern COUNT(*) (or COUNT(1)) simply counts rows; the * or 1 has no significance.
SELECT COUNT(*) FROM t is not free. It will actually do a full index scan, which is slow for a large table. WHERE and ORDER BY are likely to add to that slowness. LIMIT is useless since the result is always 1 row. (That is, the LIMIT is applied to the result, not to the counting.)

Does MySQL not use LIMIT to optimize query select functions?

I've got a complex query I have to run in an application that is giving me some performance trouble. I've simplified it here. The database is MySQL 5.6.35 on CentOS.
SELECT a.`po_num`,
Count(*) AS item_count,
Sum(b.`quantity`) AS total_quantity,
Group_concat(`web_sku` SEPARATOR ' ') AS web_skus
FROM `order` a
INNER JOIN `order_item` b
ON a.`order_id` = b.`order_key`
WHERE `store` LIKE '%foobar%'
LIMIT 200 offset 0;
The key part of this query is where I've placed "foobar" as a placeholder. If this value is something like big_store, the query takes much longer (roughly 0.4 seconds in the query provided here, much longer in the query I'm actually using) than if the value is small_store (roughly 0.1 seconds in the query provided). big_store would return significantly more results if there were not limit.
But there is a limit and that's what surprises me. Both datasets have more than the LIMIT, which is only 200. It appears to me that MySQL performing the select functions COUNT, SUM, GROUP_CONCAT for all big_store/small_store rows and then applies the LIMIT retroactively. I would imagine that it'd be best to stop when you get to 200.
Could it not do the select functions COUNT, SUM, GROUP_CONCAT actions after grabbing the 200 rows it will use, making my query much much quicker? This seems feasible to me except in cases where there's an ORDER BY on one of those rows.
Does MySQL not use LIMIT to optimize a query select functions? If not, is there a good reason for that? If so, did I make a mistake in my thinking above?
It can stop short due to the LIMIT, but that is not a reasonable query since there is no ORDER BY.
Without ORDER BY, it will pick whatever 200 rows it feels like and stop short.
With an ORDER BY, it will have to scan the entire table that contains store (please qualify columns with which table they come from!). This is because of the leading wildcard. Only then can it trim to 200 rows.
Another problem -- Without a GROUP BY, aggregates (SUM, etc) are performed across the entire table (or at least those that remain after filtering). The LIMIT does not apply until after that.
Perhaps what you are asking about is MariaDB 5.5.21's "LIMIT_ROWS_EXAMINED".
Think of it this way ... All of the components of a SELECT are done in the order specified by the syntax. Since LIMIT is last, it does not apply until after the other stuff is performed.
(There are a couple of exceptions: (1) SELECT col... must be done after FROM ..., since it would not know which table(s); (2) The optimizer readily reorders JOINed table and clauses in WHERE ... AND ....)
More details on that query.
The optimizer peeks ahead, and sees that the WHERE is filtering on order (that is where store is, yes?), so it decides to start with the table order.
It fetches all rows from order that match %foobar%.
For each such row, find the row(s) in order_item. Now it has some number of rows (possibly more than 200) with which to do the aggregates.
Perform the aggregates - COUNT, SUM, GROUP_CONCAT. (Actually this will probably be done as it gathers the rows -- another optimization.)
There is now 1 row (with an unpredictable value for a.po_num).
Skip 0 rows for the OFFSET part of the LIMIT. (OK, another out-of-order thingie.)
Deliver up to 200 rows. (There is only 1.)
Add ORDER BY (but no GROUP BY) -- big deal, sort the 1 row.
Add GROUP BY (but no ORDER BY) in, now you may have more than 200 rows coming out, and it can stop short.
Add GROUP BY and ORDER BY and they are identical, then it may have to do a sort for the grouping, but not for the ordering, and it may stop at 200.
Add GROUP BY and ORDER BY and they are not identical, then it may have to do a sort for the grouping, and will have to re-sort for the ordering, and cannot stop at 200 until after the ORDER BY. That is, virtually all the work is performed on all the data.
Oh, and all of this gets worse if you don't have the optimal index. Oh, did I fail to insist on providing SHOW CREATE TABLE?
I apologize for my tone. I have thrown quite a few tips in your direction; please learn from them.

Retrieving only a fixed number of rows in MySQL

I am testing my database design under load and I need to retrieve only a fixed number of rows (5000)
I can specify a LIMIT to achieve this, however it seems that the query builds the result set of all rows that match and then returns only the number of rows specified in the limit. Is that how it is implemented?
Is there a for MySQL to read one row, read another one and basically stop when it retrieves the 5000th matching row?
MySQL is smart in that if you specify a LIMIT 5000 in your query, and it is possible to produce that result without generating the whole result set first, then it will not build the whole result.
For instance, the following query:
SELECT * FROM table ORDER BY column LIMIT 5000
This query will need to scan the whole table unless there is an index on column, in which case it does the smart thing and uses the index to find the rows with the smallest column.
SELECT * FROM `your_table` LIMIT 0, 5000
This will display the first 5000 results from the database.
SELECT * FROM `your_table` LIMIT 1001, 5000
This will show records from 1001 to 6000 (counting from 0).
Complexity of such query is O(LIMIT) (unless you specify order by).
It means that if 10000000 rows will match your query, and you specify limit equal to 5000, then the complexity will be O(5000).
#Jarosław Gomułka is right
If you use LIMIT with ORDER BY, MySQL ends the sorting as soon as it has found the first row_count rows of the sorted result, rather than sorting the entire result. If ordering is done by using an index, this is very fast. In either case, after the initial rows have been found, there is no need to sort any remainder of the result set, and MySQL does not do so.
if the set is not sorted it terminates the SELECT operation as soon as it's got enough rows to the result set.
The exact plan the query optimizer uses depends on your query (what fields are being selected, the LIMIT amount and whether there is an ORDER BY) and your table (keys, indexes, and number of rows in the table). Selecting an unindexed column and/or ordering by a non-key column is going to produce a different execution plan than selecting a column and ordering by the primary key column. The later will not even touch the table, and only process the number of rows specified in your LIMIT.
Each database defines its own way of limiting the result set size depends on the database you are using.
While the SQL:2008 specification defines a standard syntax for limiting a SQL query, MySQL 8 does not support it.
Therefore, on MySQL, you need to use the LIMIT clause to restrict the result set to the Top-N records:
SELECT
title
FROM
post
ORDER BY
id DESC
LIMIT 50
Notice that we are using an ORDER BY clause since, otherwise, there is no guarantee which are the first records to be included in the returning result set.

MySQL Data - Best way to implement paging?

My iPhone application connects to my PHP web service to retrieve data from a MySQL database, a request can return up to 500 results.
What is the best way to implement paging and retrieve 20 items at a time?
Let's say I receive the first 20 entries from my database, how can I now request the next 20 entries?
From the MySQL documentation:
The LIMIT clause can be used to constrain the number of rows returned by the SELECT statement. LIMIT takes one or two numeric arguments, which must both be nonnegative integer constants (except when using prepared statements).
With two arguments, the first argument specifies the offset of the first row to return, and the second specifies the maximum number of rows to return. The offset of the initial row is 0 (not 1):
SELECT * FROM tbl LIMIT 5,10; # Retrieve rows 6-15
To retrieve all rows from a certain offset up to the end of the result set, you can use some large number for the second parameter. This statement retrieves all rows from the 96th row to the last:
SELECT * FROM tbl LIMIT 95,18446744073709551615;
With one argument, the value specifies the number of rows to return from the beginning of the result set:
SELECT * FROM tbl LIMIT 5; # Retrieve first 5 rows
In other words, LIMIT row_count is equivalent to LIMIT 0, row_count.
For 500 records efficiency is probably not an issue, but if you have millions of records then it can be advantageous to use a WHERE clause to select the next page:
SELECT *
FROM yourtable
WHERE id > 234374
ORDER BY id
LIMIT 20
The "234374" here is the id of the last record from the prevous page you viewed.
This will enable an index on id to be used to find the first record. If you use LIMIT offset, 20 you could find that it gets slower and slower as you page towards the end. As I said, it probably won't matter if you have only 200 records, but it can make a difference with larger result sets.
Another advantage of this approach is that if the data changes between the calls you won't miss records or get a repeated record. This is because adding or removing a row means that the offset of all the rows after it changes. In your case it's probably not important - I guess your pool of adverts doesn't change too often and anyway no-one would notice if they get the same ad twice in a row - but if you're looking for the "best way" then this is another thing to keep in mind when choosing which approach to use.
If you do wish to use LIMIT with an offset (and this is necessary if a user navigates directly to page 10000 instead of paging through pages one by one) then you could read this article about late row lookups to improve performance of LIMIT with a large offset.
Define OFFSET for the query. For example
page 1 - (records 01-10): offset = 0, limit=10;
page 2 - (records 11-20) offset = 10, limit =10;
and use the following query :
SELECT column FROM table LIMIT {someLimit} OFFSET {someOffset};
example for page 2:
SELECT column FROM table
LIMIT 10 OFFSET 10;
There's literature about it:
Optimized Pagination using MySQL, making the difference between counting the total amount of rows, and pagination.
Efficient Pagination Using MySQL, by Yahoo Inc. in the Percona Performance Conference 2009. The Percona MySQL team provides it also as a Youtube video: Efficient Pagination Using MySQL (video),
The main problem happens with the usage of large OFFSETs. They avoid using OFFSET with a variety of techniques, ranging from id range selections in the WHERE clause, to some kind of caching or pre-computing pages.
There are suggested solutions at Use the INDEX, Luke:
"Paging Through Results".
"Pagination done the right way".
This tutorial shows a great way to do pagination.
Efficient Pagination Using MySQL
In short, avoid to use OFFSET or large LIMIT
you can also do
SELECT SQL_CALC_FOUND_ROWS * FROM tbl limit 0, 20
The row count of the select statement (without the limit) is captured in the same select statement so that you don't need to query the table size again.
You get the row count using SELECT FOUND_ROWS();
Query 1: SELECT * FROM yourtable WHERE id > 0 ORDER BY id LIMIT 500
Query 2: SELECT * FROM tbl LIMIT 0,500;
Query 1 run faster with small or medium records, if number of records equal 5,000 or higher, the result are similar.
Result for 500 records:
Query1 take 9.9999904632568 milliseconds
Query2 take 19.999980926514 milliseconds
Result for 8,000 records:
Query1 take 129.99987602234 milliseconds
Query2 take 160.00008583069 milliseconds
Here's how I'm solving this problem using node.js and a MySQL database.
First, lets declare our variables!
const
Key = payload.Key,
NumberToShowPerPage = payload.NumberToShowPerPage,
Offset = payload.PageNumber * NumberToShowPerPage;
NumberToShowPerPage is obvious, but the offset is the page number.
Now the SQL query...
pool.query("SELECT * FROM TableName WHERE Key = ? ORDER BY CreatedDate DESC LIMIT ? OFFSET ?", [Key, NumberToShowPerPage, Offset], (err, rows, fields) => {}));
I'll break this down a bit.
Pool, is a pool of MySQL connections. It comes from mysql node package module. You can create a connection pool using mysql.createPool.
The ?s are replaced by the variables in the array [PageKey, NumberToShow, Offset] in sequential order. This is done to prevent SQL injection.
See at the end were the () => {} is? That's an arrow function. Whatever you want to do with the data, put that logic between the braces.
Key = ? is something I'm using to select a certain foreign key. You would likely remove that if you don't use foreign key constraints.
Hope this helps.
If you are wanting to do this in a stored procedure you can try this
SELECT * FROM tbl limit 0, 20.
Unfortunately using formulas doesn't work so you can you execute a prepared statement or just give the begin and end values to the procedure.

How does MySQL execute an aggregate query with a limit?

Does it group all possible results and then send back the results found within the given LIMIT?
This page from the MySQL manual explains the ways in which it optimizes queries that use LIMIT:
http://dev.mysql.com/doc/refman/5.1/en/limit-optimization.html
In short, it doesn't just do the naive thing, which would be to compute the entire result set and then send you the first N rows.
There are some things that will prevent optimizations, including using a HAVING clause and using SQL_CALC_FOUND_ROWS.
The LIMIT clause is only selection of the records returned - it has nothing to do with the value(s) returned from the query itself. For example, if you use LIMIT 10 on a query that only returns 5 rows - you'll only get 5 rows. If the query returned 11+ rows, you'd only get 10 rows. For a query using LIMIT to consistently return the same results, you need to specify an ORDER BY clause.
Think of the query occurring in the following steps:
Query without ORDER BY or LIMIT
ORDER BY criteria applied to query output from Step 1
LIMIT criteria applied to output from Steps 1 & 2
If there's no ORDER BY specified, the step is not performed.