bloomfilter-2.0.1.2: Pure and impure Bloom Filter implementations.
CopyrightBryan O'Sullivan
LicenseBSD3
MaintainerBryan O'Sullivan <bos@serpentine.com>
Stabilityunstable
Portabilityportable
Safe HaskellSafe-Inferred
LanguageHaskell2010

Data.BloomFilter

Description

A fast, space efficient Bloom filter implementation. A Bloom filter is a set-like data structure that provides a probabilistic membership test.

  • Queries do not give false negatives. When an element is added to a filter, a subsequent membership test will definitely return True.
  • False positives are possible. If an element has not been added to a filter, a membership test may nevertheless indicate that the element is present.

This module provides low-level control. For an easier to use interface, see the Data.BloomFilter.Easy module.

Synopsis

Overview

Each of the functions for creating Bloom filters accepts two parameters:

  • The number of bits that should be used for the filter. Note that a filter is fixed in size; it cannot be resized after creation.
  • A function that accepts a value, and should return a fixed-size list of hashes of that value. To keep the false positive rate low, the hashes computes should, as far as possible, be independent.

By choosing these parameters with care, it is possible to tune for a particular false positive rate. The suggestSizing function in the Data.BloomFilter.Easy module calculates useful estimates for these parameters.

Ease of use

This module provides immutable interfaces for working with a query-only Bloom filter, and for converting to and from mutable Bloom filters.

For a higher-level interface that is easy to use, see the Easy module.

Performance

The implementation has been carefully tuned for high performance and low space consumption.

For efficiency, the number of bits requested when creating a Bloom filter is rounded up to the nearest power of two. This lets the implementation use bitwise operations internally, instead of much more expensive multiplication, division, and modulus operations.

Types

type Hash = Word32 Source #

A hash value is 32 bits wide. This limits the maximum size of a filter to about four billion elements, or 512 megabytes of memory.

data Bloom a Source #

An immutable Bloom filter, suitable for querying from pure code.

Instances

Instances details
Show (Bloom a) Source # 
Instance details

Defined in Data.BloomFilter

Methods

showsPrec :: Int -> Bloom a -> ShowS #

show :: Bloom a -> String #

showList :: [Bloom a] -> ShowS #

NFData (Bloom a) Source # 
Instance details

Defined in Data.BloomFilter

Methods

rnf :: Bloom a -> () #

data MBloom s a Source #

A mutable Bloom filter, for use within the ST monad.

Instances

Instances details
Show (MBloom s a) Source # 
Instance details

Defined in Data.BloomFilter.Mutable.Internal

Methods

showsPrec :: Int -> MBloom s a -> ShowS #

show :: MBloom s a -> String #

showList :: [MBloom s a] -> ShowS #

Immutable Bloom filters

Conversion

freeze :: MBloom s a -> ST s (Bloom a) Source #

Create an immutable Bloom filter from a mutable one. The mutable filter may be modified afterwards.

thaw :: Bloom a -> ST s (MBloom s a) Source #

Copy an immutable Bloom filter to create a mutable one. There is no non-copying equivalent.

unsafeFreeze :: MBloom s a -> ST s (Bloom a) Source #

Create an immutable Bloom filter from a mutable one. The mutable filter must not be modified afterwards, or a runtime crash may occur. For a safer creation interface, use freeze or create.

Creation

unfold Source #

Arguments

:: forall a b. (a -> [Hash])

family of hash functions to use

-> Int

number of bits in filter

-> (b -> Maybe (a, b))

seeding function

-> b

initial seed

-> Bloom a 

Build an immutable Bloom filter from a seed value. The seeding function populates the filter as follows.

  • If it returns Nothing, it is finished producing values to insert into the filter.
  • If it returns Just (a,b), a is added to the filter and b is used as a new seed.

fromList Source #

Arguments

:: (a -> [Hash])

family of hash functions to use

-> Int

number of bits in filter

-> [a]

values to populate with

-> Bloom a 

Create an immutable Bloom filter, populating it from a list of values.

Here is an example that uses the cheapHashes function from the Data.BloomFilter.Hash module to create a hash function that returns three hashes.

import Data.BloomFilter.Hash (cheapHashes)

filt = fromList (cheapHashes 3) 1024 ["foo", "bar", "quux"]
 

empty Source #

Arguments

:: (a -> [Hash])

family of hash functions to use

-> Int

number of bits in filter

-> Bloom a 

Create an empty Bloom filter.

This function is subject to fusion with insert and insertList.

singleton Source #

Arguments

:: (a -> [Hash])

family of hash functions to use

-> Int

number of bits in filter

-> a

element to insert

-> Bloom a 

Create a Bloom filter with a single element.

This function is subject to fusion with insert and insertList.

Accessors

length :: Bloom a -> Int Source #

Return the size of an immutable Bloom filter, in bits.

elem :: a -> Bloom a -> Bool Source #

Query an immutable Bloom filter for membership. If the value is present, return True. If the value is not present, there is still some possibility that True will be returned.

notElem :: a -> Bloom a -> Bool Source #

Query an immutable Bloom filter for non-membership. If the value is present, return False. If the value is not present, there is still some possibility that False will be returned.

Modification

insert :: a -> Bloom a -> Bloom a Source #

Create a new Bloom filter from an existing one, with the given member added.

This function may be expensive, as it is likely to cause the underlying bit array to be copied.

Repeated applications of this function with itself are subject to fusion.

insertList :: [a] -> Bloom a -> Bloom a Source #

Create a new Bloom filter from an existing one, with the given members added.

This function may be expensive, as it is likely to cause the underlying bit array to be copied.

Repeated applications of this function with itself are subject to fusion.

The underlying representation

If you serialize the raw bit arrays below to disk, do not expect them to be portable to systems with different conventions for endianness or word size.

The raw bit array used by the immutable Bloom type.