You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: readme.md
+6-2Lines changed: 6 additions & 2 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -6,7 +6,7 @@ Bloomdb implements a bloom filter in Go, while using boltdb and badgerdb as opti
6
6
7
7
Bloomdb also implement a scalable bloom filter described in a paper written by [P. Almeida, C.Baquero, N. Preguiça, D. Hutchison](https://haslab.uminho.pt/cbm/files/dbloom.pdf).
8
8
9
-
A scalable bloom filter removes the need for an apriori filter size as expected by the basic bloom filter, while preserving the desired false positive rate by scaling the filter as needed.
9
+
A scalable bloom filter allows you to grow the filter as needed, and removes the need for an apriori filter size as expected by the basic bloom filter, while preserving the desired false positive rate by scaling the filter as needed.
10
10
11
11
### Installation
12
12
@@ -74,7 +74,7 @@ import (
74
74
"fmt"
75
75
76
76
"github.com/dgraph-io/badger/v3"
77
-
gobloomgo "github.com/dsa0x/gobloomgo"
77
+
"github.com/dsa0x/gobloomgo"
78
78
)
79
79
80
80
funcmain() {
@@ -86,3 +86,7 @@ func main() {
86
86
fmt.Printf("%s\n", bf.Get([]byte("key")))
87
87
}
88
88
```
89
+
90
+
#### References
91
+
92
+
1.[P. Almeida, C.Baquero, N. Preguiça, D. Hutchison](https://haslab.uminho.pt/cbm/files/dbloom.pdf)
0 commit comments