It was found that unnecessary work of building Ordered_key structures
is being done when processing NULL-aware materialization for IN predicates
having only one column. In fact, the logic for that simplified case can be
expressed as follows.
Say we have predicate left_expr IN (SELECT <subq1>), where left_expr is
scalar(not a tuple).
Then
if (left_expr is NULL) {
if (subq1 produced any rows) {
// note that we don't care if subq1 has produced
// NULLs or not.
NULL IN (<some values>) -> UNKNOWN, i.e. NULL.
} else {
NULL IN ({empty-set}) -> FALSE.
}
} else {
// left_expr is a non-NULL value
if (subq1 output has a match for left_expr) {
left_expr IN (..., left_expr ...) -> TRUE
} else {
// no "known" matches.
if (subq1 output has a NULL) {
left_expr IN ( ... NULL ...) ->
(NULL could have been a match or not)
-> NULL.
} else {
// subq1 didn't produce any "UNKNOWNs" so
// we're positive there weren't any matches
-> FALSE.
}
}
}
This commit introduces subselect_single_column_partial_engine class
implementing the logic described.
Reviewer: Sergei Petrunia <sergey@mariadb.com>
This commits adds the "materialization" block to the output of
EXPLAIN/ANALYZE FORMAT=JSON when materialized subqueries are involved
into processing. In the case of ANALYZE additional runtime information
is displayed, such as:
- chosen strategy of materialization
- number of partial match/index lookup loops
- sizes of partial match buffers
