Description
Bloom filter is a space efficient, probabilistic data structure, designed to test the membership of elements to a set.
blooming-bella alternatives and similar packages
Based on the "Data Structures" category.
Alternatively, view blooming-bella alternatives based on common mentions on social networks and blogs.
-
go-datastructures
a collection of useful, performant, and thread-safe data structures -
gocache
A complete Go cache library with mutiple stores (memory, memcache, redis, ...), chainable, loadable, metrics cache and more. -
hyperloglog
HyperLogLog implementation with Sparse, LogLog-Beta bias correction and TailCut space reduction. -
merkletree
Implementation of a merkle tree providing an efficient and secure verification of the contents of data structures. -
Bloomfilter
Face-meltingly fast, thread-safe, marshalable, unionable, probability- and optimal-size-calculating Bloom filter in go -
gostl
Data structure and algorithm library for go, designed to provide functions similar to C++ STL. -
hilbert
Go package for mapping values to and from space-filling curves, such as Hilbert and Peano curves. -
go-adaptive-radix-tree
A Go implementation of Adaptive Radix Tree. -
remember-go
A universal interface for caching slow database queries (backed by redis, memcached, ristretto, or in-memory). -
count-min-log
A Go implementation Count-Min-Log sketch: Approximately counting with approximate counters (Like Count-Min sketch but using less memory). -
nan
Zero allocation Nullable structures in one library with handy conversion functions, marshallers and unmarshallers.
Get performance insights in less than 4 minutes
Do you think we are missing an alternative of blooming-bella or a related project?
README
blooming-belle - A simple implementation of Bloom Filters
What?
Bloom filter is a space efficient, probabilistic data structure, designed to test the membership of elements to a set.
Trade-offs?
Being a space efficient data structure is it may return false positives, but always returns definite negatives.
Applications?
Testing for non-membership saves resources such as calls to a web server, checking a proxy cache. Google Chrome uses bloom filters as a check for malicious URLs.
blooming-bella
A bloom filter for integers. Uses mummur3,Super Fast Hash and marvin32 hashing algorithms
Example
bella, err := blooming_bella.NewBella(1000, 0.01)
if err != nil {
log.Fatal(err)
}
bella.Add(10)
bella.Add(121)
bella.Add(13)
bella.Add(111)
fmt.Println(bella.Test(10)) // => true
fmt.Println(bella.Test(104)) // => false
fmt.Println(bella.Test(110)) // => false
fmt.Println(bella.Test(13)) // => true
New
Added Super Fast Hashing algorithm
TODO
- [ ] Calculate "ideal" number of hash functions to use.
- [ ] Dynamically "generate" the hash functions. What does it mean to be alive?