You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I checked the current Go implementation against the Java optimization linked here. ixorBitmap still computes the XOR cardinality first and then performs the XOR in a second pass for dense results. On an M4 pro, a prototype that XORs into the receiver first, computes its cardinality, and converts only when sparse improved a 50%-dense case from approximately 742 ns/op to 677 ns/op, with zero allocations in both versions. I’d add benchmarks across dense, sparse, and near-empty results, along with focused in-place correctness tests. Is this issue still available for a PR?
Interesting optimization...
https://github.com/RoaringBitmap/RoaringBitmap/pull/542/files
by @richardstartin