Re: surprising query optimisation
От | Ron |
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Тема | Re: surprising query optimisation |
Дата | |
Msg-id | eab8a947-3e28-8ab6-275d-6646b3e43ace@gmail.com обсуждение исходный текст |
Ответ на | Re: surprising query optimisation (Chris Withers <chris@withers.org>) |
Ответы |
Re: surprising query optimisation
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Список | pgsql-general |
On 12/05/2018 08:42 AM, Chris Withers wrote: > On 05/12/2018 14:38, Stephen Frost wrote: >> Greetings, >> >> * Chris Withers (chris@withers.org) wrote: >>> On 30/11/2018 15:33, Stephen Frost wrote: >>>> * Chris Withers (chris@withers.org) wrote: >>>>> On 28/11/2018 22:49, Stephen Frost wrote: >>>> For this, specifically, it's because you end up with exactly what you >>>> have: a large index with tons of duplicate values. Indexes are >>>> particularly good when you have high-cardinality fields. Now, if you >>>> have a skewed index, where there's one popular value and a few much less >>>> popular ones, then that's where you really want a partial index (as I >>>> suggest earlier) so that queries against the non-popular value(s) is >>>> able to use the index and the index is much smaller. >>> >>> Interesting! In my head, for some reason, I'd always assumed a btree index >>> would break down a char field based on the characters within it. Does that >>> never happen? >> >> Not sure what you mean by 'break down a char field'. > > Rather than breaking into three buckets ('NEW', 'ACK', 'RSV'), a more > complicated hierarchy ('N', 'NE', 'A', 'AC', etc). The b-tree indexes on legacy RDBMS which I still occasionally fiddle with performs key prefix compression in a manner similar to what you refer to, but otherwise that's not how b-trees work. -- Angular momentum makes the world go 'round.
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