Comments (1)
Unfortunately I lack the cycles to maintain this project. (I've added a note in the README.)
These textbook implementations in here are best suited for inspiration. The modern standard in Bloom filter implementation is no longer double hashing, but modulo reduction of a fast general-purpose 64-bit hash digest, e.g., as computed by xxHash. Please see VAST for an example implementation.
The non-standard Bloom filter implementations were an academic experiment, but I do not recommend using them in practice.
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Related Issues (20)
- Avoid assert failure on bits_.size() % digests.size() HOT 2
- Path with space
- Possible performance issue when performing look-ups for non-existent entries HOT 3
- N3980: a more flexible way of hashing HOT 3
- make test failure
- how to install the code in os x? HOT 5
- Possible performance improvement by replacing % (modulo) with multiply + shift HOT 3
- Wrapping for Python 3 HOT 6
- Conan package HOT 5
- bits.size % digests.size() assert error make this library not friendly. HOT 3
- Remove dependency on Threads HOT 1
- MSVC not supported? HOT 1
- aux is a reserved file name on windows HOT 3
- Error while building on windows using MSVC HOT 1
- Segmentation fault when running in thread HOT 1
- Correction about counting bf. HOT 3
- GCC: Version 10.0.1 "runtime_error’ is not a member of ‘std" in hash.cpp HOT 2
- Incorrect header inclusion
- How can I add raw bytes, or non-null terminated strings? HOT 1
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