How to Install and Uninstall golang-github-willf-bloom-dev Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 15,2024

1. Install "golang-github-willf-bloom-dev" package

This is a short guide on how to install golang-github-willf-bloom-dev on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                golang-github-willf-bloom-dev
            
                    
    
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2. Uninstall "golang-github-willf-bloom-dev" package

Please follow the guidelines below to uninstall golang-github-willf-bloom-dev on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                golang-github-willf-bloom-dev
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the golang-github-willf-bloom-dev package on Ubuntu 20.10 (Groovy Gorilla)

Package: golang-github-willf-bloom-dev
Architecture: all
Version: 2.0.3+git20190228.25ba46e-2
Priority: optional
Section: universe/devel
Source: golang-github-willf-bloom
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Go Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 37
Depends: golang-github-spaolacci-murmur3-dev, golang-github-willf-bitset-dev
Filename: pool/universe/g/golang-github-willf-bloom/golang-github-willf-bloom-dev_2.0.3+git20190228.25ba46e-2_all.deb
Size: 8872
MD5sum: 3555ae25c4dbec58c278d4fea34bfaf7
SHA1: b4c2fa3d7ba763382cd3a269d9523cdf67c0c4b7
SHA256: bb31a28a53370f39da1d5859172e20905a43b2a4d298060a1b9f3d02532ec33c
SHA512: 2f4ee004ad4b1cc82157cb19cd239bc4ec9bc4415ad4c3af2d23de7dbf61dd22d261571012541448ecfbdec7f87304d0b2cb5bb5aa97d90651058f5e4de44032
Homepage: https://github.com/willf/bloom
Description-en: Go package implementing Bloom filters
A Bloom filter is a representation of a set of n items, where the main
requirement is to make membership queries; i.e., whether an item is a
member of a set.
.
A Bloom filter has two parameters: m, a maximum size (typically a
reasonably large multiple of the cardinality of the set to represent)
and k, the number of hashing functions on elements of the set. (The
actual hashing functions are important, too, but this is not a
parameter for this implementation). A Bloom filter is backed by a BitSet
(https://github.com/willf/bitset); a key is represented in the filter
by setting the bits at each value of the hashing functions (modulo
m). Set membership is done by testing whether the bits at each value of
the hashing functions (again, modulo m) are set. If so, the item is in
the set. If the item is actually in the set, a Bloom filter will never
fail (the true positive rate is 1.0); but it is susceptible to false
positives. The art is to choose k and m correctly.
.
In this implementation, the hashing functions used is murmurhash
(github.com/spaolacci/murmur3), a non-cryptographic hashing function.
Description-md5: fa8321fa96c077c668f1fdb1878fa848