Hi

I am checking one customer query where there are some empty tables in a
nontrivial query. The fixed estimation on empty tables in Postgres are
working very well, but I found another issue.

create table test_a(id int);
create table test_b(id int);
insert into test_a select generate_series(1,100000);
analyze test_a, test_b;

with zero row in test_b postgres optimizer uses nested loop

postgres=# explain analyze select * from test_a where not exists(select *
from test_b where test_a.id=test_b.id);
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│                                                    QUERY PLAN
                                        │
╞═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════╡
│ Nested Loop Anti Join  (cost=0.00..2693.00 rows=99999 width=4) (actual
time=0.024..90.530 rows=100000 loops=1)    │
│   Join Filter: (test_a.id = test_b.id)
                                         │
│   ->  Seq Scan on test_a  (cost=0.00..1443.00 rows=100000 width=4)
(actual time=0.017..8.171 rows=100000 loops=1) │
│   ->  Seq Scan on test_b  (cost=0.00..0.00 rows=1 width=4) (actual
time=0.000..0.000 rows=0 loops=100000)         │
│ Planning Time: 0.153 ms
                                        │
│ Execution Time: 94.331 ms
                                        │
└───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
(6 rows)

but if I add one fake row to test_b, I got hash antijoin

insert into test_b values(-1);
analyze test_b;

postgres=# explain analyze select * from test_a where not exists(select *
from test_b where test_a.id=test_b.id);
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│                                                    QUERY PLAN
                                        │
╞═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════╡
│ Hash Anti Join  (cost=1.02..2706.51 rows=99999 width=4) (actual
time=0.026..24.474 rows=100000 loops=1)           │
│   Hash Cond: (test_a.id = test_b.id)
                                         │
│   ->  Seq Scan on test_a  (cost=0.00..1443.00 rows=100000 width=4)
(actual time=0.010..8.522 rows=100000 loops=1) │
│   ->  Hash  (cost=1.01..1.01 rows=1 width=4) (actual time=0.008..0.010
rows=1 loops=1)                            │
│         Buckets: 1024  Batches: 1  Memory Usage: 9kB
                                         │
│         ->  Seq Scan on test_b  (cost=0.00..1.01 rows=1 width=4) (actual
time=0.003..0.004 rows=1 loops=1)        │
│ Planning Time: 0.186 ms
                                        │
│ Execution Time: 28.334 ms
                                        │
└───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
(8 rows)

Now the query is almost 3 times faster. Probably this is a cost issue,
because cost is very similar. With fake row I got better plan. But when I
disable hashjoin I got more expensive but better plan too

postgres=# explain analyze select * from test_a where not exists(select *
from test_b where test_a.id=test_b.id);
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│                                                    QUERY PLAN
                                        │
╞═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════╡
│ Nested Loop Anti Join  (cost=0.00..2944.01 rows=99999 width=4) (actual
time=0.100..47.360 rows=100000 loops=1)    │
│   Join Filter: (test_a.id = test_b.id)
                                         │
│   Rows Removed by Join Filter: 100000
                                        │
│   ->  Seq Scan on test_a  (cost=0.00..1443.00 rows=100000 width=4)
(actual time=0.019..8.586 rows=100000 loops=1) │
│   ->  Materialize  (cost=0.00..1.01 rows=1 width=4) (actual
time=0.000..0.000 rows=1 loops=100000)                │
│         ->  Seq Scan on test_b  (cost=0.00..1.01 rows=1 width=4) (actual
time=0.006..0.008 rows=1 loops=1)        │
│ Planning Time: 0.176 ms
                                        │
│ Execution Time: 51.248 ms
                                        │
└───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
(8 rows)

On empty table the Materialize node helps 50%

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