Re: ML-based indexing ("The Case for Learned Index Structures", a paper from Google) - Mailing list pgsql-hackers

From Peter Geoghegan
Subject Re: ML-based indexing ("The Case for Learned Index Structures", a paper from Google)
Date
Msg-id CAH2-Wz=L6OsZDjFd7gvgZz7PZCAbhL3H9h6Wk7dqUBAUHjf0vg@mail.gmail.com
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In response to Re: ML-based indexing ("The Case for Learned Index Structures", a paper from Google)  (Chapman Flack <chap@anastigmatix.net>)
Responses Re: ML-based indexing ("The Case for Learned Index Structures", a paper from Google)  ("Jonah H. Harris" <jonah.harris@gmail.com>)
List pgsql-hackers
On Tue, Apr 20, 2021 at 12:35 PM Chapman Flack <chap@anastigmatix.net> wrote:
> How would showing that to be true for data structure X be different from
> making a case for data structure X?

You don't have to understand the theoretical basis of B-Tree indexes
to see that they work well. In fact, it took at least a decade for
somebody to formalize how the space utilization works with B-Trees
containing random data. Of course theory matters, but the fact is that
B-Trees had been widely used for commercial and scientific
applications that whole time.

Maybe I'll be wrong about learned indexes - who knows? But the burden
of proof is not mine. I prefer to spend my time on things that I am
reasonably confident will work out well ahead of time.


--
Peter Geoghegan



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