On Wed, Jun 28, 2000 at 10:56:17AM -0400, Tom Lane wrote:
> Ang Chin Han <angch@pollcities.com> writes:
> If it was like that then a hash index wouldn't have been applicable
> anyway; hashes are only good for strict equality checks. If you want
> something that can do ordering checks you need a btree index.
>
> (There are good reasons why btree is the default index type ;-))
There _was_ a btree index, before I added the extra hash index:
pintoo=# \dcountry_pkeyIndex "country_pkey"Attribute | Type
------------+----------country_id | smallint
unique btree (primary key)
> > Original cost est:
> > Hash Join (cost=8.85..16.76 rows=75 width=18)
> > -> Seq Scan on city (cost=0.00..1.75 rows=75 width=16)
> > -> Hash (cost=5.53..5.53 rows=253 width=2)
> > -> Seq Scan on country (cost=0.00..5.53 rows=253 width=2)
>
> > I guess the problem is that country-city is a one-to-many relation,
> > BUT I've more countries than cities (note the # of rows above), thus
> > throwing the planner off...
>
> Off what? This looks like a pretty reasonable plan to me, given the
> fairly small table sizes. Do you have evidence that another plan
> type would be quicker for this problem?
No evidence, but I was hoping that having a prehashed country_id
would speed things up a bit, since the seq scan on country could
be redundant, requring only a seq scan on city and a index (hash)
lookup on country.
Or maybe this is a related question (just curious):
pintoo=# explain select country_id from country order by country_id;
NOTICE: QUERY PLAN:
Sort (cost=15.63..15.63 rows=253 width=2) -> Seq Scan on country (cost=0.00..5.53 rows=253 width=2)
pintoo=# explain select name from country order by name;
NOTICE: QUERY PLAN:
Sort (cost=15.63..15.63 rows=253 width=12) -> Seq Scan on country (cost=0.00..5.53 rows=253 width=12)
If there is already in b-tree index on country_id, why bother
re-sorting it, when it could be output'd by traversing the tree?
Comparing with an unindexed column, we can see that the index
is not used at all.
