Ignoring error codes from type conversion allows default (wrong) values to
go unnoticed in the formation of index search conditions.
Fixed by correctly checking for conversion errors.
fails
The bug was introduced with the push of the fix for bug#20953: after
the error on view creation we never reset the error state, so some
valid statements would give the same error after that.
The solution is to properly reset the error state.
This performance degradation for UPDATEs could be observed in the update
statements for which the search key cannot be converted to any valid
value of the type of the search column, like for a the condition
int_fld=99999999999999999999999999, though it can be guaranteed here
that there is no row with such a key value.
There was already support for CREATE DEFINER=... EVENT syntax in the
parser, but DEFINER information was ignored.
This patch adds processing of DEFINER, and a new ALTER DEFINER=...
EVENT syntax.
The bug could cause choosing a sub-optimal execution plan for
a single-table query if a unique index with many null keys were
defined for the table.
It happened because the code of the check_quick_keys function
made an assumption that any key may occur in an unique index
only once. Yet this is not true for keys with nulls that may
have multiple occurrences in the index.
Two problems here:
Problem 1:
While constructing the join columns list the optimizer does as follows:
1. Sets the join_using_fields/natural_join members of the right JOIN
operand.
2. Makes a "table reference" (TABLE_LIST) to parent the two tables.
3. Assigns the join_using_fields/is_natural_join of the wrapper table
using join_using_fields/natural_join of the rightmost table
4. Sets join_using_fields to NULL for the right JOIN operand.
5. Passes the parent table up to the same procedure on the upper
level.
Step 1 overrides the the join_using_fields that are set for a nested
join wrapping table in step 4.
Fixed by making a designated variable SELECT_LEX::prev_join_using to
pass the data from step 1 to step 4 without destroying the wrapping
table data.
Problem 2:
The optimizer checks for ambiguous columns while transforming
NATURAL JOIN/JOIN USING to JOIN ON. While doing that there was no
distinction between columns that are used in the generated join
condition (where ambiguity can be checked) and the other columns
(where ambiguity can be checked only when resolving references
coming from outside the JOIN construct itself).
Fixed by allowing the non-USING columns to be present in multiple
copies in both sides of the join and moving the ambiguity check
to the place where unqualified references to the join columns are
resolved (find_field_in_natural_join()).
When a merge table is opened compare column and key definition of
underlying tables against column and key definition of merge table.
If any of underlying tables have different column/key definition
refuse to open merge table.
The optimizer takes away columns from GROUP BY/DISTINCT if they constitute
all the parts of an unique index.
However if some of the columns can contain NULLs this cannot be done
(because an UNIQUE index can have multiple rows with NULL values).
Fixed by not using UNIQUE indexes with nullable columns to remove
grouping columns from GROUP BY/DISTINCT.
Depending on the queries we use different data processing methods
and can lose some data in case of double (and decimal in 4.1) fields.
The fix consists of two parts:
1. double comparison changed, now double a is equal to double b
if (a-b) is less than 5*0.1^(1 + max(a->decimals, b->decimals)).
For example, if a->decimals==1, b->decimals==2, a==b if (a-b)<0.005
2. if we use a temporary table, store double values there as is
to avoid any data conversion (rounding).
Checking for NULL before calling the val_xxx()
methods only checks for such arguments that are
known to be NULLs at compile time.
The arguments that may or may not contain
NULLs (e.g. function calls and possibly others)
are not checked at all.
Fixed by first calling the val_xxx() method and
then checking for null in SEC_TO_TIME().
In addition QUARTER() was not returning 0 (as all the
val_int() functions do when processing a NULL value).
Before this fix, a IN predicate of the form: "IN (( subselect ))", with two
parenthesis, would be evaluated as a single row subselect: if the subselect
returns more that 1 row, the statement would fail.
The SQL:2003 standard defines a special exception in the specification,
and mandates that this particular form of IN predicate shall be equivalent
to "IN ( subselect )", which involves a table subquery and works with more
than 1 row.
This fix implements "IN (( subselect ))", "IN ((( subselect )))" etc
as per the SQL:2003 requirement.
All the details related to the implementation of this change have been
commented in the code, and the relevant sections of the SQL:2003 spec
are given for reference, so they are not repeated here.
Having access to the spec is a requirement to review in depth this patch.
