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MySQL supports indexes on generated columns. For example:
CREATE TABLE t1 (f1 INT, gc INT AS (f1 + 1) STORED, INDEX (gc)); The generated column,gc, is defined as the expressionf1 + 1. The column is also indexed and the optimizer can take that index into account during execution plan construction. In the following query, theWHERE clause refers togc and the optimizer considers whether the index on that column yields a more efficient plan:
SELECT * FROM t1 WHERE gc > 9; The optimizer can use indexes on generated columns to generate execution plans, even in the absence of direct references in queries to those columns by name. This occurs if theWHERE,ORDER BY, orGROUP BY clause refers to an expression that matches the definition of some indexed generated column. The following query does not refer directly togc but does use an expression that matches the definition ofgc:
SELECT * FROM t1 WHERE f1 + 1 > 9; The optimizer recognizes that the expressionf1 + 1 matches the definition ofgc and thatgc is indexed, so it considers that index during execution plan construction. You can see this usingEXPLAIN:
mysql> EXPLAIN SELECT * FROM t1 WHERE f1 + 1 > 9\G*************************** 1. row *************************** id: 1 select_type: SIMPLE table: t1 partitions: NULL type: rangepossible_keys: gc key: gc key_len: 5 ref: NULL rows: 1 filtered: 100.00 Extra: Using index condition In effect, the optimizer has replaced the expressionf1 + 1 with the name of the generated column that matches the expression. That is also apparent in the rewritten query available in the extendedEXPLAIN information displayed bySHOW WARNINGS:
mysql> SHOW WARNINGS\G*************************** 1. row *************************** Level: Note Code: 1003Message: /* select#1 */ select `test`.`t1`.`f1` AS `f1`,`test`.`t1`.`gc` AS `gc` from `test`.`t1` where (`test`.`t1`.`gc` > 9)The following restrictions and conditions apply to the optimizer's use of generated column indexes:
For a query expression to match a generated column definition, the expression must be identical and it must have the same result type. For example, if the generated column expression is
f1 + 1, the optimizer does not recognize a match if the query uses1 + f1, or iff1 + 1(an integer expression) is compared with a string.The optimization applies to these operators:
=,<,<=,>,>=,BETWEEN, andIN().For operators other than
BETWEENandIN(), either operand can be replaced by a matching generated column. ForBETWEENandIN(), only the first argument can be replaced by a matching generated column, and the other arguments must have the same result type.BETWEENandIN()are not yet supported for comparisons involving JSON values.The generated column must be defined as an expression that contains at least a function call or one of the operators mentioned in the preceding item. The expression cannot consist of a simple reference to another column. For example,
gc INT AS (f1) STOREDconsists only of a column reference, so indexes ongcare not considered.For comparisons of strings to indexed generated columns that compute a value from a JSON function that returns a quoted string,
JSON_UNQUOTE()is needed in the column definition to remove the extra quotes from the function value. (For direct comparison of a string to the function result, the JSON comparator handles quote removal, but this does not occur for index lookups.) For example, instead of writing a column definition like this:doc_name TEXT AS (JSON_EXTRACT(jdoc, '$.name')) STOREDWrite it like this:
doc_name TEXT AS (JSON_UNQUOTE(JSON_EXTRACT(jdoc, '$.name'))) STOREDWith the latter definition, the optimizer can detect a match for both of these comparisons:
... WHERE JSON_EXTRACT(jdoc, '$.name') = 'some_string' ...... WHERE JSON_UNQUOTE(JSON_EXTRACT(jdoc, '$.name')) = 'some_string' ...Without
JSON_UNQUOTE()in the column definition, the optimizer detects a match only for the first of those comparisons.If the optimizer picks the wrong index, an index hint can be used to disable it and force the optimizer to make a different choice.
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