Quickly detect already witnessed data, ideal for deduplication.
Limited memory of witnessed data, oldest are forgotten. Library is thread safe. Offers deterministic and probabilistic (over an order of magnitude less memory consuming) implementation. The probabilistic implementation uses bloom filters, meaning false positives are possible but not false negatives.
Compiled binaries for many platforms are available and can be downloaded for the latest release.
Extract the binary for your platform and add it to your system path.
Requires golang environment/workspace.
# compile and install library
go get github.com/f483/dejavu
# compile and install binary
go install github.com/f483/dejavu/dejavu
$ dejavu -h
Usage: dejavu [OPTION]... [FILE]...
Concatenate FILE(s) and filter or output duplicate lines.
With no FILE, or when FILE is -, read standard input.
Options:
-D use deterministic mode instead of probabilistic
WARNING requires order of magnitude more memory
-d output only duplicates instead of filtering
-f float
chance of false positive, between 0.0 and 1.0
only for probabilistic mode (default 1e-06)
-l uint
limit after which entries are forgotton (default 1000000)
-o string
output file, defaults to stdout
-v output version information and exit
Examples:
dejavu
default probabilistic deduplication from stdin to std out with
1mil entry limit and 1/1mil chance of false positive (~8M mem usage)
dejavu -o s f - g
deduplicat f, then stdin, then g, to output s
dejavu -l 10000000 -fp 0.000000001
probabilistic deduplication with 10mil entry limit
and 1/1bil chance of false positive (~70M mem usage)
dejavu -d -D -l 65536
output duplicates and avoid false positives with deterministic mode
lower entry limit to avoid excessive memory usage
Implementation:
Efficient probabilistic and deterministic duplicate detection with O(1)
detection time and O(n) memory usage in relation to entry limit. Default
probabilistic implementation uses bloom filters, meaning false
positives are possible but not false negatives.
Author: Fabian Barkhau <[email protected]>
Project: https://github.com/f483/dejavu
License: MIT https://raw.githubusercontent.com/f483/dejavu/master/LICENSE
package main
import (
"fmt"
"github.com/f483/dejavu"
)
func main() {
// probably remembers last 65536 with 0.000001 chance of false positive
p := dejavu.NewProbabilistic(65536, 0.000001)
fmt.Println(p.Witness([]byte("bar"))) // entry added
fmt.Println(p.Witness([]byte("bar"))) // probably remembers entry
}
package main
import (
"fmt"
"github.com/f483/dejavu"
)
func main() {
// always remembers last 1024 entries
d := dejavu.NewDeterministic(1024)
fmt.Println(d.Witness([]byte("foo"))) // entry added
fmt.Println(d.Witness([]byte("foo"))) // remembers entry
}
0.000001 chance of false positive.
0.000001 chance of false positive.
