Awesome
Overview
Doublejump is a revamped Google's jump consistent hash. It overcomes the shortcoming of the original design - being unable to remove nodes. Here is how it works.
Benchmark
Doublejump/10-nodes 49276861 22.3 ns/op 0 B/op 0 allocs/op
Doublejump/100-nodes 33304191 34.9 ns/op 0 B/op 0 allocs/op
Doublejump/1000-nodes 25261296 46.3 ns/op 0 B/op 0 allocs/op
StathatConsistent/10-nodes 4780832 273.5 ns/op 80 B/op 2 allocs/op
StathatConsistent/100-nodes 4059537 291.8 ns/op 80 B/op 2 allocs/op
StathatConsistent/1000-nodes 3132294 367.6 ns/op 80 B/op 2 allocs/op
SerialxHashring/10-nodes 2766384 455.7 ns/op 152 B/op 5 allocs/op
SerialxHashring/100-nodes 2500936 487.6 ns/op 152 B/op 5 allocs/op
SerialxHashring/1000-nodes 2254138 560.0 ns/op 152 B/op 5 allocs/op
Getting Started
V1
## If golang version <= 1.17
go get -u github.com/edwingeng/doublejump
V2
## If golang version >= 1.18
go get -u github.com/edwingeng/doublejump/v2
Examples
V1
// If golang version <= 1.17
import "github.com/edwingeng/doublejump"
func Example() {
h := NewHash()
for i := 0; i < 10; i++ {
h.Add(fmt.Sprintf("node%d", i))
}
fmt.Println(h.Len())
fmt.Println(h.LooseLen())
fmt.Println(h.Get(1000))
fmt.Println(h.Get(2000))
fmt.Println(h.Get(3000))
h.Remove("node3")
fmt.Println(h.Len())
fmt.Println(h.LooseLen())
fmt.Println(h.Get(1000))
fmt.Println(h.Get(2000))
fmt.Println(h.Get(3000))
// Output:
// 10
// 10
// node9
// node2
// node3
// 9
// 10
// node9
// node2
// node0
}
V2
// If golang version >= 1.18
import "github.com/edwingeng/doublejump/v2"
func Example() {
h := NewHash[string]()
for i := 0; i < 10; i++ {
h.Add(fmt.Sprintf("node%d", i))
}
fmt.Println(h.Len())
fmt.Println(h.LooseLen())
fmt.Println(h.Get(1000))
fmt.Println(h.Get(2000))
fmt.Println(h.Get(3000))
h.Remove("node3")
fmt.Println(h.Len())
fmt.Println(h.LooseLen())
fmt.Println(h.Get(1000))
fmt.Println(h.Get(2000))
fmt.Println(h.Get(3000))
// Output:
// 10
// 10
// node9 true
// node2 true
// node3 true
// 9
// 10
// node9 true
// node2 true
// node0 true
}
Acknowledgements
The implementation of the original algorithm is credited to dgryski.