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Indexes are used to find rows with specific column values fast. Without an index, MySQL has to start with the first record and then read through the whole table to find the relevant rows. The larger the table, the more this costs. If the table has an index for the columns in question, MySQL can quickly determine the position to seek to in the middle of the data file without having to look at all the data. If a table has 1,000 rows, this is at least 100 times faster than reading sequentially. Note that if you need to access almost all 1,000 rows, it is faster to read sequentially, because that minimizes disk seeks.
Most MySQL indexes (PRIMARY KEY,
UNIQUE, INDEX, and
FULLTEXT) are stored in B-trees. Exceptions are
that indexes on spatial column types use R-trees, and
MEMORY (HEAP) tables support
hash indexes.
Strings are automatically prefix- and end-space compressed. See
Section 13.1.4, “CREATE INDEX Syntax”.
In general, indexes are used as described in the following
discussion. Characteristics specific to hash indexes (as used in
MEMORY tables) are described at the end of this
section.
Indexes are used for these operations:
To quickly find the rows that match a WHERE
clause.
To eliminate rows from consideration. If there is a choice between multiple indexes, MySQL normally uses the index that finds the smallest number of rows.
To retrieve rows from other tables when performing joins.
To find the MIN() or MAX()
value for a specific indexed column
key_col. This is optimized by a
preprocessor that checks whether you are using WHERE
on all key parts that
occur before key_part_# =
constantkey_col in the index. In
this case, MySQL does a single key lookup for each
MIN() or MAX() expression and
replace it with a constant. If all expressions are replaced with
constants, the query returns at once. For example:
SELECT MIN(key_part2),MAX(key_part2) FROMtbl_nameWHEREkey_part1=10;
To sort or group a table if the sorting or grouping is done on a
leftmost prefix of a usable key (for example, ORDER BY
). If all key parts
are followed by key_part1,
key_part2DESC, the key is read in reverse
order. See Section 7.2.10, “How MySQL Optimizes ORDER BY”.
In some cases, a query can be optimized to retrieve values without consulting the data rows. If a query uses only columns from a table that are numeric and that form a leftmost prefix for some key, the selected values may be retrieved from the index tree for greater speed:
SELECTkey_part3FROMtbl_nameWHEREkey_part1=1
Suppose that you issue the following SELECT
statement:
mysql> SELECT * FROM tbl_name WHERE col1=val1 AND col2=val2;
If a multiple-column index exists on col1 and
col2, the appropriate rows can be fetched
directly. If separate single-column indexes exist on
col1 and col2, the optimizer
tries to find the most restrictive index by deciding which index
finds fewer rows and using that index to fetch the rows.
If the table has a multiple-column index, any leftmost prefix of the
index can be used by the optimizer to find rows. For example, if you
have a three-column index on (col1, col2, col3),
you have indexed search capabilities on (col1),
(col1, col2), and (col1, col2,
col3).
MySQL can't use a partial index if the columns don't form a leftmost
prefix of the index. Suppose that you have the
SELECT statements shown here:
SELECT * FROMtbl_nameWHERE col1=val1; SELECT * FROMtbl_nameWHERE col2=val2; SELECT * FROMtbl_nameWHERE col2=val2 AND col3=val3;
If an index exists on (col1, col2, col3), only
the first of the preceding queries uses the index. The second and
third queries do involve indexed columns, but
(col2) and (col2, col3) are
not leftmost prefixes of (col1, col2, col3).
A B-tree index can be used for column comparisons in expressions
that use the =, >,
>=, <,
<=, or BETWEEN operators.
The index also can be used for LIKE comparisons
if the argument to LIKE is a constant string that
doesn't start with a wildcard character. For example, the following
SELECT statements use indexes:
SELECT * FROMtbl_nameWHEREkey_colLIKE 'Patrick%'; SELECT * FROMtbl_nameWHEREkey_colLIKE 'Pat%_ck%';
In the first statement, only rows with 'Patrick' <=
are
considered. In the second statement, only rows with key_col < 'Patricl''Pat'
<= are
considered.
key_col < 'Pau'
The following SELECT statements do not use
indexes:
SELECT * FROMtbl_nameWHEREkey_colLIKE '%Patrick%'; SELECT * FROMtbl_nameWHEREkey_colLIKEother_col;
In the first statement, the LIKE value begins
with a wildcard character. In the second statement, the
LIKE value is not a constant.
MySQL 4.0 and up performs an additional LIKE
optimization. If you use ... LIKE
'% and
string%'string is longer than three characters,
MySQL uses the Turbo Boyer-Moore algorithm to
initialize the pattern for the string and then use this pattern to
perform the search quicker.
Searching using uses indexes if col_name IS
NULLcol_name
is indexed.
Any index that doesn't span all AND levels in the
WHERE clause is not used to optimize the query.
In other words, to be able to use an index, a prefix of the index
must be used in every AND group.
The following WHERE clauses use indexes:
... WHEREindex_part1=1 ANDindex_part2=2 ANDother_column=3 /*index= 1 ORindex= 2 */ ... WHEREindex=1 OR A=10 ANDindex=2 /* optimized like "index_part1='hello'" */ ... WHEREindex_part1='hello' ANDindex_part3=5 /* Can use index onindex1but not onindex2orindex3*/ ... WHEREindex1=1 ANDindex2=2 ORindex1=3 ANDindex3=3;
These WHERE clauses do not
use indexes:
/*index_part1is not used */ ... WHEREindex_part2=1 ANDindex_part3=2 /* Index is not used in both AND parts */ ... WHEREindex=1 OR A=10 /* No index spans all rows */ ... WHEREindex_part1=1 ORindex_part2=10
Sometimes MySQL does not use an index, even if one is available. One
way this occurs is when the optimizer estimates that using the index
would require MySQL to access a large percentage of the rows in the
table. (In this case, a table scan is probably much faster, because
it requires fewer seeks.) However, if such a query uses
LIMIT to only retrieve part of the rows, MySQL
uses an index anyway, because it can much more quickly find the few
rows to return in the result.
Hash indexes have somewhat different characteristics than those just discussed:
They are used only for equality comparisons that use the
= or <=> operators (but
are very fast). They are not used for
comparison operators such as < that find a
range of values.
The optimizer cannot use a hash index to speed up ORDER
BY operations. (This type of index cannot be used to
search for the next entry in order.)
MySQL cannot determine approximately how many rows there are
between two values (this is used by the range optimizer to decide
which index to use). This may affect some queries if you change a
MyISAM table to a hash-indexed
MEMORY table.
Only whole keys can be used to search for a row. (With a B-tree index, any leftmost prefix of the key can be used to find rows.)
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