The optimizer is largely cost-based and will try to choose the optimal plan for any query. However in some cases it does not have enough information to choose a perfect plan and in these cases you may have to provide hints to force the optimizer to use another plan.
You can examine the query plan for a SELECT
by writing EXPLAIN
before the statement. As of MariaDB 10.0.5, SHOW EXPLAIN
shows the output of a running query. In some cases, its output can be closer to reality than EXPLAIN
.
For the following queries, we will use the world database for the examples.
Download it from ftp://ftp.askmonty.org/public/world.sql.gz
Install it with:
mysqladmin create world zcat world.sql.gz | ../client/mysql world
or
mysqladmin create world gunzip world.sql.gz ../client/mysql world < world.sql
You can force the join order by using STRAIGHT_JOIN
either in the SELECT
or JOIN
part.
The simplest way to force the join order is to put the tables in the correct order in the FROM
clause and use SELECT STRAIGHT_JOIN
like so:
SELECT STRAIGHT_JOIN SUM(City.Population) FROM Country,City WHERE City.CountryCode=Country.Code AND Country.HeadOfState="Vladimir Putin";
If you only want to force the join order for a few tables, use STRAIGHT_JOIN
in the FROM
clause. When this is done, only tables connected with STRAIGHT_JOIN
will have their order forced. For example:
SELECT SUM(City.Population) FROM Country STRAIGHT_JOIN City WHERE City.CountryCode=Country.Code AND Country.HeadOfState="Vladimir Putin";
In both of the above cases Country
will be scanned first and for each matching country (one in this case) all rows in City
will be checked for a match. As there is only one matching country this will be faster than the original query.
The output of EXPLAIN
for the above cases is:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | Country | ALL | PRIMARY | NULL | NULL | NULL | 239 | Using where |
1 | SIMPLE | City | ALL | NULL | NULL | NULL | NULL | 4079 | Using where; Using join buffer (flat, BNL join) |
This is one of the few cases where ALL
is ok, as the scan of the Country
table will only find one matching row.
In some cases the optimizer may choose a non-optimal index or it may choose to not use an index at all, even if some index could theoretically be used.
In these cases you have the option to either tell the optimizer to only use a limited set of indexes, ignore one or more indexes, or force the usage of some particular index.
You can limit which indexes are considered with the USE INDEX option.
USE INDEX [{FOR {JOIN|ORDER BY|GROUP BY}] ([index_list])
The default is 'FOR JOIN
', which means that the hint only affects how the WHERE
clause is optimized.
USE INDEX
is used after the table name in the FROM
clause.
Example:
CREATE INDEX Name ON City (Name); CREATE INDEX CountryCode ON City (Countrycode); EXPLAIN SELECT Name FROM City USE INDEX (CountryCode) WHERE name="Helsingborg" AND countrycode="SWE";
This produces:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | City | ref | CountryCode | CountryCode | 3 | const | 14 | Using where |
If we had not used USE INDEX, the Name
index would have been in possible keys
.
You can tell the optimizer to not consider some particular index with the IGNORE INDEX option.
IGNORE INDEX [{FOR {JOIN|ORDER BY|GROUP BY}] ([index_list])
This is used after the table name in the FROM
clause:
CREATE INDEX Name ON City (Name); CREATE INDEX CountryCode ON City (Countrycode); EXPLAIN SELECT Name FROM City IGNORE INDEX (Name) WHERE name="Helsingborg" AND countrycode="SWE";
This produces:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | City | ref | CountryCode | CountryCode | 3 | const | 14 | Using where |
The benefit of using IGNORE_INDEX
instead of USE_INDEX
is that it will not disable a new index which you may add later.
Forcing an index to be used is mostly useful when the optimizer decides to do a table scan even if you know that using an index would be better. (The optimizer could decide to do a table scan even if there is an available index when it believes that most or all rows will match and it can avoid the overhead of using the index).
CREATE INDEX Name ON City (Name); EXPLAIN SELECT Name,CountryCode FROM City FORCE INDEX (Name) WHERE name>="A" and CountryCode >="A";
This produces:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | City | range | Name | Name | 35 | NULL | 4079 | Using where |
FORCE_INDEX
works by only considering the given indexes (like with USE_INDEX
) but in addition it tells the optimizer to regard a table scan as something very expensive. However if none of the 'forced' indexes can be used, then a table scan will be used anyway.
When using index hints (USE, FORCE or IGNORE INDEX), the index name value can also be an unambiguous prefix of an index name.
The optimizer will try to use indexes to resolve ORDER BY and GROUP BY.
You can use USE INDEX, IGNORE INDEX and FORCE INDEX as in the WHERE
clause above to ensure that some specific index used:
USE INDEX [{FOR {JOIN|ORDER BY|GROUP BY}] ([index_list])
This is used after the table name in the FROM
clause.
Example:
CREATE INDEX Name ON City (Name); EXPLAIN SELECT Name,Count(*) FROM City FORCE INDEX FOR GROUP BY (Name) WHERE population >= 10000000 GROUP BY Name;
This produces:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | City | index | NULL | Name | 35 | NULL | 4079 | Using where |
Without the FORCE INDEX option we would have 'Using where; Using temporary; Using filesort
' in the 'Extra' column, which means that the optimizer would created a temporary table and sort it.
The optimizer uses several strategies to optimize GROUP BY and ORDER BY:
A temporary table will always be used if the fields which will be sorted are not from the first table in the JOIN order.
Using an in-memory table (as described above) is usually the fastest option for GROUP BY if the result set is small. It is not optimal if the result set is very big. You can tell the optimizer this by using SELECT SQL_SMALL_RESULT
or SELECT SQL_BIG_RESULT
.
For example:
EXPLAIN SELECT SQL_SMALL_RESULT Name,Count(*) AS Cities FROM City GROUP BY Name HAVING Cities > 2;
produces:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | City | ALL | NULL | NULL | NULL | NULL | 4079 | Using temporary; Using filesort |
while:
EXPLAIN SELECT SQL_BIG_RESULT Name,Count(*) AS Cities FROM City GROUP BY Name HAVING Cities > 2;
produces:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | City | ALL | NULL | NULL | NULL | NULL | 4079 | Using filesort |
The difference is that with SQL_SMALL_RESULT
a temporary table is used.
In some cases you may want to force the use of a temporary table for the result to free up the table/row locks for the used tables as quickly as possible.
You can do this with the SQL_BUFFER_RESULT
option:
CREATE INDEX Name ON City (Name); EXPLAIN SELECT SQL_BUFFER_RESULT Name,Count(*) AS Cities FROM City GROUP BY Name HAVING Cities > 2;
This produces:
id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
---|---|---|---|---|---|---|---|---|---|
1 | SIMPLE | City | index | NULL | Name | 35 | NULL | 4079 | Using index; Using temporary |
Without SQL_BUFFER_RESULT
, the above query would not use a temporary table for the result set.
In MariaDB 5.3 we added an optimizer switch which allows you to specify which algorithms will be considered when optimizing a query.
See the optimizer section for more information about the different algorithms which are used.
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Licensed under the Creative Commons Attribution 3.0 Unported License and the GNU Free Documentation License.
https://mariadb.com/kb/en/index-hints-how-to-force-query-plans/