Efficient bloom filter like datastructure, based on the Rank Select Quotient Filter (RSQF).

This is a small and flexible general-purpose AMQ-Filter. It not only supports approximate membership testing like a bloom filter but also deletions, merging (not implemented), resizing and serde serialization.

• High performance
• Supports removals
• Extremely compact, more so than comparable filters
• Can be created with a initial small capacity and grow as needed
• (De)Serializable with serde
• Portable Rust implementation

let mut f = qfilter::Filter::new(1000000, 0.01);
for i in 0..1000 {
    f.insert(i).unwrap();
}
for i in 0..1000 {
    assert!(f.contains(i));
}

The hashing algorithm used is xxhash3 which offers both high performance and stability across platforms.

For a given capacity and error probability the RSQF may require significantly less space than the equivalent bloom filter or other AMQ-Filters.

• Merging
• Shrink to fit
• Counting
• Smoother resizing by chaining exponentially larger and more precise filters

The implementation assumes the popcnt instruction (equivalent to integer.count_ones()) is present when compiling for x86_64 targets. This is theoretically not guaranteed as the instruction is only available on AMD/Intel CPUs released after 2007/2008. If that's not the case the Filter constructor will panic.

Support for such legacy x86_64 CPUs can be optionally enabled with the legacy_x86_64_support which incurs a ~10% performance penalty.

This project is licensed under the MIT license.