Beginning with Postgres 7.1 it is possible to control the query planner to some extent by using explicit JOIN syntax. To see why this matters, we first need some background.
In a simple join query, such as
SELECT * FROM a,b,c WHERE a.id = b.id AND b.ref = c.id;the planner is free to join the given tables in any order. For example, it could generate a query plan that joins A to B, using the WHERE clause a.id = b.id, and then joins C to this joined table, using the other WHERE clause. Or it could join B to C and then join A to that result. Or it could join A to C and then join them with B --- but that would be inefficient, since the full Cartesian product of A and C would have to be formed, there being no applicable WHERE clause to allow optimization of the join. (All joins in the Postgres executor happen between two input tables, so it's necessary to build up the result in one or another of these fashions.) The important point is that these different join possibilities give semantically equivalent results but may have hugely different execution costs. Therefore, the planner will explore all of them to try to find the most efficient query plan.
When a query only involves two or three tables, there aren't many join orders to worry about. But the number of possible join orders grows exponentially as the number of tables expands. Beyond ten or so input tables it's no longer practical to do an exhaustive search of all the possibilities, and even for six or seven tables planning may take an annoyingly long time. When there are too many input tables, the Postgres planner will switch from exhaustive search to a genetic probabilistic search through a limited number of possibilities. (The switchover threshold is set by the GEQO_THRESHOLD run-time parameter described in the Administrator's Guide.) The genetic search takes less time, but it won't necessarily find the best possible plan.
When the query involves outer joins, the planner has much less freedom than it does for plain (inner) joins. For example, consider
SELECT * FROM a LEFT JOIN (b JOIN c ON (b.ref = c.id)) ON (a.id = b.id);Although this query's restrictions are superficially similar to the previous example, the semantics are different because a row must be emitted for each row of A that has no matching row in the join of B and C. Therefore the planner has no choice of join order here: it must join B to C and then join A to that result. Accordingly, this query takes less time to plan than the previous query.
In Postgres 7.1, the planner treats all explicit JOIN syntaxes as constraining the join order, even though it is not logically necessary to make such a constraint for inner joins. Therefore, although all of these queries give the same result:
SELECT * FROM a,b,c WHERE a.id = b.id AND b.ref = c.id; SELECT * FROM a CROSS JOIN b CROSS JOIN c WHERE a.id = b.id AND b.ref = c.id; SELECT * FROM a JOIN (b JOIN c ON (b.ref = c.id)) ON (a.id = b.id);the second and third take less time to plan than the first. This effect is not worth worrying about for only three tables, but it can be a lifesaver with many tables.
You do not need to constrain the join order completely in order to cut search time, because it's OK to use JOIN operators in a plain FROM list. For example,
SELECT * FROM a CROSS JOIN b, c, d, e WHERE ...;forces the planner to join A to B before joining them to other tables, but doesn't constrain its choices otherwise. In this example, the number of possible join orders is reduced by a factor of 5.
If you have a mix of outer and inner joins in a complex query, you might not want to constrain the planner's search for a good ordering of inner joins inside an outer join. You can't do that directly in the JOIN syntax, but you can get around the syntactic limitation by using subselects. For example,
SELECT * FROM d LEFT JOIN (SELECT * FROM a, b, c WHERE ...) AS ss ON (...);Here, joining D must be the last step in the query plan, but the planner is free to consider various join orders for A,B,C.
Constraining the planner's search in this way is a useful technique both for reducing planning time and for directing the planner to a good query plan. If the planner chooses a bad join order by default, you can force it to choose a better order via JOIN syntax --- assuming that you know of a better order, that is. Experimentation is recommended.