Well, I'm asking ppl actually try to test using such high dimensions.
Based on my own experience, I consider it unusable. It seems other
folks may have run into trouble too. If the project committers can't
even really use vectors with such high dimension counts, then its not
in an OK state for users, and we shouldn't bump the limit.

I'm happy to discuss/compromise etc, but simply bumping the limit
without addressing the underlying usability/scalability is a real
no-go, it is not really solving anything, nor is it giving users any
freedom or allowing them to do something they couldnt do before.
Because if it still doesnt work it still doesnt work.

We all need to be on the same page, grounded in reality, not fantasy,
where if we set a limit of 1024 or 2048, that you can actually index
vectors with that many dimensions and it actually works and scales.

On Thu, Apr 6, 2023 at 11:38 AM Alessandro Benedetti
<a.benede...@sease.io> wrote:
>
> As I said earlier, a max limit limits usability.
> It's not forcing users with small vectors to pay the performance penalty of 
> big vectors, it's literally preventing some users to use 
> Lucene/Solr/Elasticsearch at all.
> As far as I know, the max limit is used to raise an exception, it's not used 
> to initialise or optimise data structures (please correct me if I'm wrong).
>
> Improving the algorithm performance is a separate discussion.
> I don't see a correlation with the fact that indexing billions of whatever 
> dimensioned vector is slow with a usability parameter.
>
> What about potential users that need few high dimensional vectors?
>
> As I said before, I am a big +1 for NOT just raise it blindly, but I believe 
> we need to remove the limit or size it in a way it's not a problem for both 
> users and internal data structure optimizations, if any.
>
>
> On Wed, 5 Apr 2023, 18:54 Robert Muir, <rcm...@gmail.com> wrote:
>>
>> I'd ask anyone voting +1 to raise this limit to at least try to index
>> a few million vectors with 756 or 1024, which is allowed today.
>>
>> IMO based on how painful it is, it seems the limit is already too
>> high, I realize that will sound controversial but please at least try
>> it out!
>>
>> voting +1 without at least doing this is really the
>> "weak/unscientifically minded" approach.
>>
>> On Wed, Apr 5, 2023 at 12:52 PM Michael Wechner
>> <michael.wech...@wyona.com> wrote:
>> >
>> > Thanks for your feedback!
>> >
>> > I agree, that it should not crash.
>> >
>> > So far we did not experience crashes ourselves, but we did not index
>> > millions of vectors.
>> >
>> > I will try to reproduce the crash, maybe this will help us to move forward.
>> >
>> > Thanks
>> >
>> > Michael
>> >
>> > Am 05.04.23 um 18:30 schrieb Dawid Weiss:
>> > >> Can you describe your crash in more detail?
>> > > I can't. That experiment was a while ago and a quick test to see if I
>> > > could index rather large-ish USPTO (patent office) data as vectors.
>> > > Couldn't do it then.
>> > >
>> > >> How much RAM?
>> > > My indexing jobs run with rather smallish heaps to give space for I/O
>> > > buffers. Think 4-8GB at most. So yes, it could have been the problem.
>> > > I recall segment merging grew slower and slower and then simply
>> > > crashed. Lucene should work with low heap requirements, even if it
>> > > slows down. Throwing ram at the indexing/ segment merging problem
>> > > is... I don't know - not elegant?
>> > >
>> > > Anyway. My main point was to remind folks about how Apache works -
>> > > code is merged in when there are no vetoes. If Rob (or anybody else)
>> > > remains unconvinced, he or she can block the change. (I didn't invent
>> > > those rules).
>> > >
>> > > D.
>> > >
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>> >
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