@hackage unagi-bloomfilter0.1.1.2

A fast, cache-efficient, concurrent bloom filter

This library implements a fast concurrent bloom filter, based on bloom-1 from "Fast Bloom Filters and Their Generalization" by Y Qiao, et al.

A bloom filter is a probabilistic, constant-space, set-like data structure supporting insertion and membership queries. This implementation is backed by SipHash so can safely consume untrusted inputs.

The implementation here compares favorably with traditional set implementations in a single-threaded context, e.g. here are 10 inserts or lookups compared across some sets of different sizes:

With the llvm backend benchmarks take around 75-85% of the runtime of the native code gen.

Unfortunately writes in particular don't seem to scale currently; i.e. distributing writes across multiple threads may be slower than in a single-threaded context, because of memory effects. We plan to export functionality that would support using the filter here in a concurrent context with better memory behavior (e.g. a server that shards to a thread-pool which handles only a portion of the bloom array).

  • Installation

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  • Dependents (1)

    @hackage/acme-everything

    • Package Flags

      dev
       (off by default)

      To build tests, executables and benchmarks do `configure -fdev --enable-tests` and run the built executables by hand (i.e. not with `cabal test` etc.; we put all our different executables in test-suite sections in order to hide their dependencies from hackage)

      instrumented
       (off by default)

      Enables assertions in library code. When --enable-library-profiling and --enable-executable-profiling is turned on, you can get stacktraces as well