github.com/panmari/cuckoofilter@v1.0.7-0.20231223155748-763d1d471ee8/doc.go (about)

     1  /*
     2  Permission is hereby granted, free of charge, to any person obtaining a copy
     3  of this software and associated documentation files (the "Software"), to deal
     4  in the Software without restriction, including without limitation the rights
     5  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
     6  copies of the Software, and to permit persons to whom the Software is
     7  furnished to do so, subject to the following conditions:
     8  
     9  The above copyright notice and this permission notice shall be included in all
    10  copies or substantial portions of the Software.
    11  
    12  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    13  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    14  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    15  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    16  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    17  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    18  SOFTWARE.
    19  */
    20  
    21  /*
    22  Package cuckoo provides a Cuckoo Filter, a Bloom filter replacement for approximated set-membership queries.
    23  
    24  While Bloom filters are well-known space-efficient data structures to serve queries like "if item x is in a set?", they do not support deletion. Their variances to enable deletion (like counting Bloom filters) usually require much more space.
    25  
    26  Cuckoo filters provide the flexibility to add and remove items dynamically. A cuckoo filter is based on cuckoo hashing (and therefore named as cuckoo filter). It is essentially a cuckoo hash table storing each key's fingerprint. Cuckoo hash tables can be highly compact, thus a cuckoo filter could use less space than conventional Bloom filters, for applications that require low false positive rates (< 3%).
    27  
    28  "Cuckoo Filter: Better Than Bloom" by Bin Fan, Dave Andersen and Michael Kaminsky
    29  (https://www.cs.cmu.edu/~dga/papers/cuckoo-conext2014.pdf)
    30  
    31  */
    32  package cuckoo