Comment by jcgrillo
2 days ago
Yeah this is my experience with logs data. You only actually care about O(10) lines per query, usually related by some correlation ID. Or, instead of searching you're summarizing by counting things. In that case, actually counting is important ;).
In this piece though--and maybe I need to read it again--I was under the impression that the LLM's "interface" to the logs data is queries against clickhouse. So long as the queries return sensibly limited results, and it doesn't go wild with the queries, that could address both concerns?
What does O(10) mean?
Mathematically, it means that the number of lines read is bounded by 10*M, where M is some constant. So it's basically equivalent to saying that it's O(1).
I'm guessing that intention was to say "around 10 lines", though it kind of stretches the definition if we're being picky.
See https://en.wikipedia.org/wiki/Big_O_notation
I normally see that from engineers using "O(x)" as "approximately x" whenever it's clear from context that you're not actually talking about asymptomatic complexity.
I've always thought it was like this, maybe I'm wrong:
O(some constant) -- "nearby" that constant (maybe "order of magnitude" or whatever is contextually convenient)
O(some parameter) -- denotes the asymptotic behavior of some parametrized process
O(some variable representing a small number) -- denotes the negligible part of something that you're deciding you don't have to care about--error terms with exponent larger than 2 for example
2 replies →
I think the O means order of magnitude. It looks like Big O notation, but O(10) would collapse to O(1) and OP is not talking about efficiency anyway.
"about 10"