On Thu, Feb 28, 2019 at 1:50 PM Nicolas Grilly <nico...@gardentechno.com>
wrote:

> On Thu, Feb 28, 2019 at 1:24 PM Chris Travers <chris.trav...@gmail.com>
> wrote:
>
>> 1.  a) TB-scale full text search systems.
>>      b) PostgreSQL's full text search is quite capable but not so
>> powerful that it can completely replace Lucene-based systems.  So you have
>> to consider complexity vs functionality if you are tying with other data
>> that is already in PostgreSQL.  Note further that my experience with at
>> least ElasticSearch is that it is easier to scale something built on
>> multiple PostgreSQL instances into the PB range than it is to scale
>> ElasticSearch into the PB range.
>>      c) Solr or ElasticSearch
>>
>

> One question about your use of PostgreSQL for a TB-scale full-text search
> system: Did you order search results using ts_rank or ts_rank_cd? I'm
> asking because in my experience, PostgreSQL full-text search is extremely
> efficient, until you need ranking. It's because the indexes don't contain
> the necessary information for ranking, and because of this the heap has to
> be consulted, which implies a lot of random IO.
>
> I'd be curious to know a bit more about your experience in this regard.
>


Where I did this on the TB scale, we had some sort of ranking but it was
not based on ts_rank.

On the PB scale systems I work on now, it is distributed, and we don't
order in PostgreSQL (or anywhere else, though if someone wants to write to
disk and sort, they can do this I guess)

>
> Regards,
>
> Nicolas Grilly
>
> PS: A potential solution to the performance issue I mentioned is this PG
> extension: https://github.com/postgrespro/rum
>
>

-- 
Best Wishes,
Chris Travers

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