Does it matter which way I order the criteria in the ON clause for a JOIN?
select a.Name, b.Status from a inner join b on a.StatusID = b.ID
versus
select a.Name, b.Status from a inner join b on b.ID = a.StatusID
Is there any impact on performance? What if I had multiple criteria?
Is one order more maintainable than another?
The order of the conditions in the ON clause doesn't matter.
JOIN order doesn't matter, the query engine will reorganize their order based on statistics for indexes and other stuff.
JOIN
order can be forced by putting the tables in the right order in the FROM
clause:
MySQL has a special clause called STRAIGHT_JOIN
which makes the order matter.
This will use an index on b.id
:
SELECT a.Name, b.Status FROM a STRAIGHT_JOIN b ON b.ID = a.StatusID
And this will use an index on a.StatusID
:
SELECT a.Name, b.Status FROM b STRAIGHT_JOIN a ON b.ID = a.StatusID
Oracle has a special hint ORDERED
to enforce the JOIN
order:
This will use an index on b.id
or build a hash table on b
:
SELECT /*+ ORDERED */ * FROM a JOIN b ON b.ID = a.StatusID
And this will use an index on a.StatusID
or build a hash table on a
:
SELECT /*+ ORDERED */ * FROM b JOIN a ON b.ID = a.StatusID
SQL Server has a hint called FORCE ORDER
to do the same:
This will use an index on b.id
or build a hash table on b
:
SELECT * FROM a JOIN b ON b.ID = a.StatusID OPTION (FORCE ORDER)
And this will use an index on a.StatusID
or build a hash table on a
:
SELECT * FROM b JOIN a ON b.ID = a.StatusID OPTION (FORCE ORDER)
PostgreSQL guys, sorry. Your TODO list says:
Optimizer hints (not wanted)
Optimizer hints are used to work around problems in the optimizer. We would rather have the problems reported and fixed.
As for the order in the comparison, it doesn't matter in any RDBMS
, AFAIK.
Though I personally always try to estimate which column will be searched for and put this column in the left (for it to seem like an lvalue
).
See this answer for more detail.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With