It says that the company is co-founded by Postgres creator. I find that bit hard to believe given that there is nothing novel in the article, probably discovery for them. I do understand that everyone has to go through their own journey to learn these things but at the same time when you are running business then seeking professional help isnt a bad idea.
Based on my experience queries like these cannot scale, whatever you do. However if you are already on a path where you had invested a lot in such queries then hire a DBA, if you are not far off then hire an architect to model the data for better performance.
Scale with what? If you have m distinct values in an index, then listing them this way takes m log(n) time, which is fine for many use cases no matter how much data you have.
The way the OP is trying to achieve all the goals by pushing the complexity on the queries/database is what I am referring to as non-scalable as data grows on SQL DB.
> If you have m distinct values in an index, then listing them this way takes m log(n) time, which is fine for many use cases no matter how much data you have.
And NO the runtimes are not right away applicable on machines at scale. You are dealing with DB locks, page sizes, available memory, existing data in memory, queue depth. Experienced folks get paid to short circuit such learnings
Correct. This is documented in depth: DISTINCT sorts the results first.
The article's use case seems to imply the author did not know about GROUP BY, nor does it imply the author knew about indexes, nor ANALYZE. Postgres 18's new skip scan indexing also could help here, so ensuring the planner chooses that could help.
Postgres doesn't have it yet https://wiki.postgresql.org/wiki/Loose_indexscan
Based on my experience queries like these cannot scale, whatever you do. However if you are already on a path where you had invested a lot in such queries then hire a DBA, if you are not far off then hire an architect to model the data for better performance.
> If you have m distinct values in an index, then listing them this way takes m log(n) time, which is fine for many use cases no matter how much data you have.
And NO the runtimes are not right away applicable on machines at scale. You are dealing with DB locks, page sizes, available memory, existing data in memory, queue depth. Experienced folks get paid to short circuit such learnings
Correct. This is documented in depth: DISTINCT sorts the results first.
The article's use case seems to imply the author did not know about GROUP BY, nor does it imply the author knew about indexes, nor ANALYZE. Postgres 18's new skip scan indexing also could help here, so ensuring the planner chooses that could help.
The article explains that skip scan doesn't do anything here.
> nor does it imply the author knew about indexes, nor ANALYZE
Indexes were talked about a lot, and they explicitly mentioned looking at the query plan.
It had the same stuff a month ago.
I guess we just have to patiently wait for the OP to hopefully read Postgres documentation from postgreSQL 10.x before correcting the article again.
Someone else said it doesn't.