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Here "materialization" just means that the query planner treats it as an optimization fence. That means the system doesn't do any optimization between the CTE a
by da_chicken 6y ago
Here "materialization" just means that the query planner treats it as an optimization fence. That means the system doesn't do any optimization between the CTE and the query referencing it. It would prepare the output of the CTE as a completely separate entity essentially as if you had dumped it to a temp table. It may not be written to disk if there was sufficient memory, but either way you're sacrificing any optimization. I believe that it would even materialize the CTE multiple times if it was referenced multiple times, but don't quote me on that.
On the other hand, if the same query were written with subqueries instead of with CTEs, then the query optimizer would not treat it as an optimization fence. If it could utilize indexes or rewrite the query to be relationally equivalent, it would do so.
Note that sometimes that optimization fence is beneficial. There are situations where it's better to create temp tables and run smaller simpler queries instead of running an extremely complex monolithic query because the query planner isn't perfect even with hints. You can still enable that optimization fence functionality in PostgreSQL if you need to, but it's generally pretty rare that it happens like this. Still, you'll see stored procedures for reports still using temp tables and even cursors sometimes because they can be made to perform better in certain situations.
- ibejoeb 6y agoA simple example would be something like predicate pushdown: with mycte as ( select a, count(b) from foo group by a ) select * from mycte where a = 10; There is enough information in the statement to plan it as with mycte as ( select a, count(b) from foo where a = 10; group by a ) select * from mycte; Before, Postgres would have computed the aggregate for all values of `a`.