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0 pointsngrilly9y ago0 comments

Thanks a lot for sharing this!

Last time I tried, it was on a machine with a spinning disk... It looks like I should try again with a SSD, which are a lot better with regard to random access.

Your search term is "Quassel". What happens if you search for a term that matches a lot of rows? This is the case where ts_rank is very expensive. I'd be curious to look at the explain of such a low-selectivity query.

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kuschku9y ago

> What happens if you search for a term that matches a lot of rows? This is the case where ts_rank is very expensive. I'd be curious to look at the explain of such a low-selectivity query.

That’s actually quite unproblematic, if you have the tsvector as its own column (not just as index).

It’s far more problematic to actually load that data from disk.

ngrillyOP9y ago

> That’s actually quite unproblematic, if you have the tsvector as its own column (not just as index).

Yes, it works, but it is slow because the tsvector is usually big enough to be stored in a TOAST table, and this produces a lot of random access reads.

This is why there is a project of storing additional information in the GIN (term positions) in order for the index to contain all necessary information for the ranking:

https://wiki.postgresql.org/images/2/25/Full-text_search_in_...

kuschku9y ago

> usually big enough to be stored in a TOAST table

Ah, luckily, in my case, that can’t happen – each row’s message contains one IRC message, so at most 512 bytes. That also automatically ensures we’ll never run into TOAST issues.

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kuschku9y ago

> What happens if you search for a term that matches a lot of rows? This is the case where ts_rank is very expensive. I'd be curious to look at the explain of such a low-selectivity query.

That’s actually quite unproblematic, if you have the tsvector as its own column (not just as index).

It’s far more problematic to actually load that data from disk.

ngrillyOP9y ago

> That’s actually quite unproblematic, if you have the tsvector as its own column (not just as index).

Yes, it works, but it is slow because the tsvector is usually big enough to be stored in a TOAST table, and this produces a lot of random access reads.

This is why there is a project of storing additional information in the GIN (term positions) in order for the index to contain all necessary information for the ranking:

https://wiki.postgresql.org/images/2/25/Full-text_search_in_...

kuschku9y ago

> usually big enough to be stored in a TOAST table

Ah, luckily, in my case, that can’t happen – each row’s message contains one IRC message, so at most 512 bytes. That also automatically ensures we’ll never run into TOAST issues.

1 more reply

j / k navigate · click thread line to collapse