Optimizing a condition based on an a very unequally distributed value.

Hi-

I have a field that is very rarely set to 'YES', but I need to filter my
results so that only rows where it is set to 'NO' appear.

Here is the distribution:


temp=#  select count(*) from case_data where case_impound = 'YES';
 count
-------
     1
(1 row)

temp=#  select count(*) from case_data where case_impound = 'NO';
 count
-------
 23768
(1 row)


Since I always test this field, I want to make sure an index is used, but
depending on what I look for, I get different query plans:



temp=# explain select count(*) from case_data where case_impound = 'NO';
NOTICE:  QUERY PLAN:

Aggregate  (cost=815.52..815.52 rows=1 width=0)
  ->  Seq Scan on case_data  (cost=0.00..756.10 rows=23768 width=0)

EXPLAIN
temp=# explain select count(*) from case_data where case_impound = 'YES';
NOTICE:  QUERY PLAN:

Aggregate  (cost=2.23..2.23 rows=1 width=0)
  ->  Index Scan using case_data_case_impound on case_data  (cost=0.00..2.22
rows=1 width=0)

EXPLAIN
temp=# explain select count(*) from case_data where case_impound != 'NO';
NOTICE:  QUERY PLAN:

Aggregate  (cost=756.10..756.10 rows=1 width=0)
  ->  Seq Scan on case_data  (cost=0.00..756.10 rows=1 width=0)

EXPLAIN
temp=# explain select count(*) from case_data where case_impound != 'YES';
NOTICE:  QUERY PLAN:

Aggregate  (cost=815.52..815.52 rows=1 width=0)
  ->  Seq Scan on case_data  (cost=0.00..756.10 rows=23768 width=0)



So my question in general is why does PGSQL opt to use the index when
looking for the single field row, and not use it when looking for the other
23768 rows?

More specifically is there a trick to make it use the index in the condition
that I want to test for, which could be either [ = 'NO' ] or [ != 'YES' ]?

Thanks!

-NickF



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Nick Fankhauser  nickf@ontko.com  Phone 1.765.935.4283  Fax 1.765.962.9788
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