>>Tsearch was never minded as prefix search, and index structure doesn't support
>>any kind of prefix or suffix. But you can write extension to tsearch, which will
>>search by prefix. But such solution wiil not use index, only sequence scan.
>
>
> How efficient would tsearch be for really big expressions (where 'hu%'
> would be expanded (using a btree word index on one column word table) to
> tsearch equivalent of ( "human" or "humanity" or "humming" or "huge" or
> ..1000 words here...) before passing the expression to tsearch?
GiST index of tsearch doen't support prefix search, so it will works only by
seqscan, as we know :) disk is much more slow than processor, speed will be
limited by disk.
>>Prefix searches easy realized with inverted index, but it require a lot of
>>programing.
>>The simplest way is:
>>create table invidx (
>> lexeme text not null primary key,
>> ids[] int
>>);
>>
>>where ids[] - array with identificators of documents which contains this word.
>
>
> How hard (or sensible ;) would be creating such an index using GiST ?
> As proved by tsearch GiST can cope well with many-to-many indexes.
Sorry, I don't understand. Do you mean that GiST supports one heap tuple in
several index tuple? If yes then no :). GiST doesn't support this feature. I
don't think that GiST may help in this situation.
> create table invidx (
> lexeme text not null,
> textdate date not null,
> ids[] int,
> primary key (lexeme, textdate)
> );
>
> which would partition the invidx table on textdate (or some other
> suitable datum)
>
>
>>2 If word is frequent then query with 'IN (select * from func()) may works slow...
> if it is often too slow then creating a temp table and doing a plain
> join may be faster.
Table structure as indidx decrease this problem.
--
Teodor Sigaev E-mail: teodor@sigaev.ru