Doesn't this depend on your data to a large extent? In a very dense graph "far" results (in terms of the effort spent searching) that match the filters might actually be quite similar?
The "far" here means "with vectors having a very low cosine similarity / very high distance". So in vector use cases where you want near vectors matching a given set of filters, far vectors matching a set of filters are useless. So in Redis Vector Sets you have another "EF" (effort) parameter just for filters, and you can decide in case not enough results are collected so far how much efforts you want to do. If you want to scan all the graph, that's fine, but Redis by default will do the sane thing and early stop when the vectors anyway are already far.
antirez|3 months ago