David Rowley <dgrowleyml@gmail.com> writes:
> On Mon, 2 May 2022 at 21:00, Pavel Stehule <pavel.stehule@gmail.com> wrote:
>> I found a query that is significantly slower with more memory
> If it was work_mem you increased, it seems strange that the plan would
> switch over to using a Nested Loop / Memoize plan.
Yeah, there's something unexplained there.
I think that the most probable explanation for the symptoms is that
cost_memoize_rescan is computing some insane value for est_entries,
causing ExecInitMemoize to allocate-and-zero a huge hash table,
which ExecEndMemoize then frees again. Neither of those steps
gets counted into any plan node's runtime, but EXPLAIN's total
execution time will include them. An insane value for est_entries
could perhaps go along with a cost misestimate that convinces the
planner to include the memoize even though it seems pointless.
I spent some time studying cost_memoize_rescan, and the only
conclusions I arrived at were that the variable names are poorly
chosen and the comments are unhelpful. For instance, one would
think that est_entry_bytes is the expected size of one cache entry,
but it seems to actually be the total space that would be occupied
if the whole input relation were loaded into the cache. And
the est_cache_entries computation seems nonsensical; if it does
make sense, the comment sure doesn't illuminate why. So I am
quite prepared to buy into the idea that cost_memoize_rescan is
producing bogus answers, but it's hard to tell what it's coming out
with in this example. Too bad EXPLAIN doesn't print est_entries.
regards, tom lane