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Nikolay Samokhvalov 🇺🇦
@samokhvalov
This thread is astonishing. People know 1001 way to optimize a simple
@PostgreSQL
query to a table with 11M rows running 3s — from migrating to ClickHouse to involving sharding And only a few understand what's btree and how it is working 🤷🏻‍♂️
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James Long
@jlongster
Hitting scaling issues with PostgreSQL. Yes! The best kind of problem! Now I need to figure out how to make a query on 11644420 rows take less then 3 seconds.
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Nikolay Samokhvalov 🇺🇦
@samokhvalov
Disclaimer: I do hope this doesn't sound offensive to anyone. This is just a thought about lack of good materials that could improve average level of SQL optimization knowledge. Level is not good, we need better docs, talks, books etc. Maybe Postgres itself needs something.
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DrakoRod
@AlfredoDrakoRod
Replying to
@samokhvalov
Maybe Postgres just need Marketing... I've read the twit and I don't understand what he want, I believe 3 seconds for 11M rows is good. Postgres maybe don't need more docs, talks, books and nice community, maybe, just need marketing...
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Peter Geoghegan
@petervgeoghegan
Replying to
@AlfredoDrakoRod
and
@samokhvalov
An index scan will locate the relevant point in the table very fast. 3 seconds might be fast if it was inherently necessary to look at all 11 million rows to get an answer, because of the specific query. But it's not, so index scan practically instant. That's the key takeaway.
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