Mysql indexes: Difference between revisions
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The order of the columns is significant,<br> | The order of the columns is significant,<br> | ||
there are debates over the optimal ordering,<br> | there are debates over the optimal ordering,<br> | ||
but generally least-specific to most-specific is how you want to organize your index. | but generally least-specific to most-specific is how you want to organize your index.<br> | ||
see https://dba.stackexchange.com/questions/160649/composite-indexes-most-selective-column-first/210122#210122 | |||
<syntaxhighlight lang="yaml"> | <syntaxhighlight lang="yaml"> | ||
- (unspecific -> specific) (ex. id, province, country) | - (unspecific -> specific) (ex. id, province, country) |
Revision as of 05:25, 6 September 2022
Indexes use various datastructures to store data to prevent full scans of all rows in the table.
Index Types
Index
A regular index, on a single column. Defaults to BTREE.
Multi-Column Index
A multi-column index is a regular index,
where the values of multiple columns are concatenated together to form one string.order
The order of the columns is significant,
there are debates over the optimal ordering,
but generally least-specific to most-specific is how you want to organize your index.
see https://dba.stackexchange.com/questions/160649/composite-indexes-most-selective-column-first/210122#210122- (unspecific -> specific) (ex. id, province, country) - arguably most scalable. you can reuse the same index when breaking up query into batches. - (specific -> unspecfic) - creates larger decision-tree. - more work on initial query, making it difficult to decompose into multiple queries. - less likely to select on most-specific rows alone # but perhaps it is best to consider which columns will be used without the others (likely least specific) # avoiding the write-cost of adding a row-change to 2x indexes.in single-column queries
You can take advantage of a multi-column index for single-column queries,
if your query includes items in the leftmost-to-rightmost order.For example
# we have a multi-column index on (country, province, city) SELECT ... WHERE country = "CA"; # CAN use index, query on leftmost column SELECT ... WHERE country = "CA" AND province = "ON" # CAN use index, query on each of the two leftmost columns SELECT ... WHERE proince = "ON"; # CANNOT use index, queries 2nd column without 1st
Index Datastructure Types
Show the current index using
SHOW INDEX FROM foo_table;BTree
A binary tree. Default for persisted storage engines.
Optimize Queries that are
- sorted - match on field prefixes (but not suffixes) - range bound (less than 10, between C and F)But not queries
- match on field suffixesHASH
A hash table. Default for the memory engine.
hash-collisions are accounted for, but each key with the same hash will need to be checked, making the query more expensive.
Indexes have a small memory footprint.Optimize queries that are
- based on the full value (ex. 'IN, NOT IN, =')But not queries that
- match on only a single key from a multi-key index (since both keys are hashed together) - are range bound. (ex. less than 10, betweeen C and F) (hash-tables are un-ordered, so range queries are not optimized)FULLTEXT
Fulltext indexes are optimized for finding keywords within blocks of text.
They are used when theMATCH AGAINST ".."
operator is used.
It may still be beneficial to have a second index with a different type on the same column.
Index Strategies
Covering Index
A covering index is a multi-column-index that indexes all fields used by a query.
It makes that one specific query more efficient.