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This section describes the functions that can be used to manipulate temporal values.See Section 12.3, “Date and Time Types”, for a description of the range of values each date and time type has and the valid formats in which values may be specified.
Functions that expect date values usually accept datetime values and ignore the time part.
Functions that expect time values usually accept datetime values and ignore the date part.
Functions that return the current date or time each are evaluated only once per query at the start of query execution.
This means that multiple references to a function such as within a single query always produce the same result.
(For our purposes, a single query also includes a call to a stored program (stored routine, trigger, or event) and all subprograms called by that program.) This principle also applies to values are supported, with up to microsecond precision.
Querying, I want to receive COUNTed results grouped by date, and not date and time.
I came to the easy solution: SELECT DATE_FORMAT(postdate, '%Y-%m-%d') AS dd, COUNT(id) FROM My Table GROUP BY dd; I suppose this solution to be quite slow (date formatting).Later, i 'upgraded' this query to use the string function: SELECT substring(postdate, 1,10) AS dd, COUNT(id) FROM My Table GROUP BY dd;knowing, that the result is in the fixed format. Comparing Dates when using MS Access and My ODBCIf you are using MS Access and have created Access queries to substitute for views (which are not yet available in my SQL), you can use the following syntax ro perform date comparisons and avoid the dreaded "ODBC -- call failed" error: Select * from [Task Effort Summary]Where ((Date() + 0) CLng([Task Effort Summary].[s_end]))This particular example retuns tasks that are overdue (where todays date is past the scheduled end date).This query was developed for reports on a TUTOS database.Functions that take temporal arguments accept values with fractional seconds.Return values from temporal functions include fractional seconds as appropriate.function reliable when combined with other functions that extract a date part from a date.