Documentation Home
MySQL 5.7 Reference Manual
Related Documentation Download this Manual
PDF (US Ltr) - 35.1Mb
PDF (A4) - 35.2Mb
Man Pages (TGZ) - 255.8Kb
Man Pages (Zip) - 360.7Kb
Info (Gzip) - 3.4Mb
Info (Zip) - 3.4Mb
Excerpts from this Manual

MySQL 5.7 Reference Manual  /  ...  /  Column Indexes

8.3.4 Column Indexes

The most common type of index involves a single column, storing copies of the values from that column in a data structure, allowing fast lookups for the rows with the corresponding column values. The B-tree data structure lets the index quickly find a specific value, a set of values, or a range of values, corresponding to operators such as =, >, , BETWEEN, IN, and so on, in a WHERE clause.

The maximum number of indexes per table and the maximum index length is defined per storage engine. See Chapter 14, The InnoDB Storage Engine, and Chapter 15, Alternative Storage Engines. All storage engines support at least 16 indexes per table and a total index length of at least 256 bytes. Most storage engines have higher limits.

For additional information about column indexes, see Section 13.1.14, “CREATE INDEX Statement”.

Index Prefixes

With col_name(N) syntax in an index specification for a string column, you can create an index that uses only the first N characters of the column. Indexing only a prefix of column values in this way can make the index file much smaller. When you index a BLOB or TEXT column, you must specify a prefix length for the index. For example:

CREATE TABLE test (blob_col BLOB, INDEX(blob_col(10)));

Prefixes can be up to 1000 bytes long (767 bytes for InnoDB tables, unless you have innodb_large_prefix set).

Note

Prefix limits are measured in bytes, whereas the prefix length in CREATE TABLE, ALTER TABLE, and CREATE INDEX statements is interpreted as number of characters for nonbinary string types (CHAR, VARCHAR, TEXT) and number of bytes for binary string types (BINARY, VARBINARY, BLOB). Take this into account when specifying a prefix length for a nonbinary string column that uses a multibyte character set.

If a search term exceeds the index prefix length, the index is used to exclude non-matching rows, and the remaining rows are examined for possible matches.

For additional information about index prefixes, see Section 13.1.14, “CREATE INDEX Statement”.

FULLTEXT Indexes

FULLTEXT indexes are used for full-text searches. Only the InnoDB and MyISAM storage engines support FULLTEXT indexes and only for CHAR, VARCHAR, and TEXT columns. Indexing always takes place over the entire column and column prefix indexing is not supported. For details, see Section 12.9, “Full-Text Search Functions”.

Optimizations are applied to certain kinds of FULLTEXT queries against single InnoDB tables. Queries with these characteristics are particularly efficient:

  • FULLTEXT queries that only return the document ID, or the document ID and the search rank.

  • FULLTEXT queries that sort the matching rows in descending order of score and apply a LIMIT clause to take the top N matching rows. For this optimization to apply, there must be no WHERE clauses and only a single ORDER BY clause in descending order.

  • FULLTEXT queries that retrieve only the COUNT(*) value of rows matching a search term, with no additional WHERE clauses. Code the WHERE clause as WHERE MATCH(text) AGAINST ('other_text'), without any > 0 comparison operator.

For queries that contain full-text expressions, MySQL evaluates those expressions during the optimization phase of query execution. The optimizer does not just look at full-text expressions and make estimates, it actually evaluates them in the process of developing an execution plan.

An implication of this behavior is that EXPLAIN for full-text queries is typically slower than for non-full-text queries for which no expression evaluation occurs during the optimization phase.

EXPLAIN for full-text queries may show Select tables optimized away in the Extra column due to matching occurring during optimization; in this case, no table access need occur during later execution.

Spatial Indexes

You can create indexes on spatial data types. MyISAM and InnoDB support R-tree indexes on spatial types. Other storage engines use B-trees for indexing spatial types (except for ARCHIVE, which does not support spatial type indexing).

Indexes in the MEMORY Storage Engine

The MEMORY storage engine uses HASH indexes by default, but also supports BTREE indexes.