In response to Kenneth Marshall :
> > > How many rows do you have in your table? If there are relatively few,
> > > it probably guesses it to be cheaper to do a sequential scan and
> > > calculate lower values on-the-fly rather than bother with the index.
> >
> > That's one reason, an other reason, i think, is, that a btree-index can't
> > search with an 'not like' - operator.
>
> The 'not like' condition is likely to be extremely non-selective
> which would cause a sequential scan to be used in any event whether
> or not an index could be used.
That's true, but i have an example where the 'not like' condition is
extremely selective:
,----[ sql ]
| test=*# select count(1) from words where lower(w) not like lower('f%');
| count
| -------
| 10
| (1 row)
|
| test=*# select count(1) from words where lower(w) like lower('f%');
| count
| -------
| 10000
| (1 row)
`----
But the index can't use:
,----[ code ]
| test=*# explain select * from words where lower(w) not like lower('f%');
| QUERY PLAN
| ----------------------------------------------------------
| Seq Scan on words (cost=0.00..4396.15 rows=10 width=47)
| Filter: (lower(w) !~~ 'f%'::text)
| (2 rows)
`----
And i think, the reason is:
,----[ quote from docu ]
| B-trees can handle equality and range queries on data that can be sorted
| into some ordering. In particular, the PostgreSQL query planner will
| consider using a B-tree index whenever an indexed column is involved in
| a comparison using one of these operators:
|
| <
| <=
| =
| >=
| >
`----
Regards, Andreas
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Andreas Kretschmer
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