mirror of https://github.com/tidwall/tile38.git
191 lines
5.1 KiB
Markdown
191 lines
5.1 KiB
Markdown
# btree
|
|
|
|
[](https://godoc.org/github.com/tidwall/btree)
|
|
|
|
An [efficient](#performance) [B-tree](https://en.wikipedia.org/wiki/B-tree) implementation in Go.
|
|
|
|
## Installing
|
|
|
|
To start using btree, install Go and run `go get`:
|
|
|
|
```sh
|
|
$ go get -u github.com/tidwall/btree
|
|
```
|
|
|
|
## Usage
|
|
|
|
```go
|
|
package main
|
|
|
|
import (
|
|
"fmt"
|
|
|
|
"github.com/tidwall/btree"
|
|
)
|
|
|
|
type Item struct {
|
|
Key, Val string
|
|
}
|
|
|
|
// byKeys is a comparison function that compares item keys and returns true
|
|
// when a is less than b.
|
|
func byKeys(a, b interface{}) bool {
|
|
i1, i2 := a.(*Item), b.(*Item)
|
|
return i1.Key < i2.Key
|
|
}
|
|
|
|
// byVals is a comparison function that compares item values and returns true
|
|
// when a is less than b.
|
|
func byVals(a, b interface{}) bool {
|
|
i1, i2 := a.(*Item), b.(*Item)
|
|
if i1.Val < i2.Val {
|
|
return true
|
|
}
|
|
if i1.Val > i2.Val {
|
|
return false
|
|
}
|
|
// Both vals are equal so we should fall though
|
|
// and let the key comparison take over.
|
|
return byKeys(a, b)
|
|
}
|
|
|
|
func main() {
|
|
// Create a tree for keys and a tree for values.
|
|
// The "keys" tree will be sorted on the Keys field.
|
|
// The "values" tree will be sorted on the Values field.
|
|
keys := btree.New(byKeys)
|
|
vals := btree.New(byVals)
|
|
|
|
// Create some items.
|
|
users := []*Item{
|
|
&Item{Key: "user:1", Val: "Jane"},
|
|
&Item{Key: "user:2", Val: "Andy"},
|
|
&Item{Key: "user:3", Val: "Steve"},
|
|
&Item{Key: "user:4", Val: "Andrea"},
|
|
&Item{Key: "user:5", Val: "Janet"},
|
|
&Item{Key: "user:6", Val: "Andy"},
|
|
}
|
|
|
|
// Insert each user into both trees
|
|
for _, user := range users {
|
|
keys.Set(user)
|
|
vals.Set(user)
|
|
}
|
|
|
|
// Iterate over each user in the key tree
|
|
keys.Ascend(nil, func(item interface{}) bool {
|
|
kvi := item.(*Item)
|
|
fmt.Printf("%s %s\n", kvi.Key, kvi.Val)
|
|
return true
|
|
})
|
|
|
|
fmt.Printf("\n")
|
|
// Iterate over each user in the val tree
|
|
vals.Ascend(nil, func(item interface{}) bool {
|
|
kvi := item.(*Item)
|
|
fmt.Printf("%s %s\n", kvi.Key, kvi.Val)
|
|
return true
|
|
})
|
|
|
|
// Output:
|
|
// user:1 Jane
|
|
// user:2 Andy
|
|
// user:3 Steve
|
|
// user:4 Andrea
|
|
// user:5 Janet
|
|
// user:6 Andy
|
|
//
|
|
// user:4 Andrea
|
|
// user:2 Andy
|
|
// user:6 Andy
|
|
// user:1 Jane
|
|
// user:5 Janet
|
|
// user:3 Steve
|
|
}
|
|
```
|
|
|
|
## Operations
|
|
|
|
### Basic
|
|
|
|
```
|
|
Len() # return the number of items in the btree
|
|
Set(item) # insert or replace an existing item
|
|
Get(item) # get an existing item
|
|
Delete(item) # delete an item
|
|
```
|
|
|
|
### Iteration
|
|
|
|
```
|
|
Ascend(pivot, iter) # scan items in ascending order starting at pivot.
|
|
Descend(pivot, iter) # scan items in descending order starting at pivot.
|
|
```
|
|
|
|
### Queues
|
|
|
|
```
|
|
Min() # return the first item in the btree
|
|
Max() # return the last item in the btree
|
|
PopMin() # remove and return the first item in the btree
|
|
PopMax() # remove and return the last item in the btree
|
|
```
|
|
### Bulk loading
|
|
|
|
```
|
|
Load(item) # load presorted items into tree
|
|
```
|
|
|
|
### Path hints
|
|
|
|
```
|
|
SetHint(item, *hint) # insert or replace an existing item
|
|
GetHint(item, *hint) # get an existing item
|
|
DeleteHint(item, *hint) # delete an item
|
|
```
|
|
|
|
## Performance
|
|
|
|
This implementation was designed with performance in mind.
|
|
|
|
The following benchmarks were run on my 2019 Macbook Pro (2.4 GHz 8-Core Intel Core i9) using Go 1.15.3. The items are simple 8-byte ints.
|
|
|
|
- `tidwall`: The [tidwall/btree](https://github.com/tidwall/btree) package
|
|
- `google`: The [google/btree](https://github.com/google/btree) package
|
|
- `go-arr`: Just a simple Go array
|
|
|
|
```
|
|
** sequential set **
|
|
tidwall: set-seq 1,000,000 ops in 143ms, 6,996,275/sec, 142 ns/op, 30.9 MB, 32 bytes/op
|
|
tidwall: set-seq-hint 1,000,000 ops in 65ms, 15,441,082/sec, 64 ns/op, 30.9 MB, 32 bytes/op
|
|
tidwall: load-seq 1,000,000 ops in 19ms, 53,242,398/sec, 18 ns/op, 30.9 MB, 32 bytes/op
|
|
google: set-seq 1,000,000 ops in 175ms, 5,700,922/sec, 175 ns/op, 33.1 MB, 34 bytes/op
|
|
go-arr: append 1,000,000 ops in 52ms, 19,153,714/sec, 52 ns/op, 41.3 MB, 43 bytes/op
|
|
|
|
** random set **
|
|
tidwall: set-rand 1,000,000 ops in 589ms, 1,697,471/sec, 589 ns/op, 22.5 MB, 23 bytes/op
|
|
tidwall: set-rand-hint 1,000,000 ops in 592ms, 1,688,184/sec, 592 ns/op, 22.2 MB, 23 bytes/op
|
|
tidwall: load-rand 1,000,000 ops in 578ms, 1,728,932/sec, 578 ns/op, 22.3 MB, 23 bytes/op
|
|
google: set-rand 1,000,000 ops in 662ms, 1,509,924/sec, 662 ns/op, 32.1 MB, 33 bytes/op
|
|
|
|
** sequential get **
|
|
tidwall: get-seq 1,000,000 ops in 111ms, 8,995,090/sec, 111 ns/op
|
|
tidwall: get-seq-hint 1,000,000 ops in 56ms, 18,017,397/sec, 55 ns/op
|
|
google: get-seq 1,000,000 ops in 135ms, 7,414,046/sec, 134 ns/op
|
|
|
|
** random get **
|
|
tidwall: get-rand 1,000,000 ops in 139ms, 7,214,017/sec, 138 ns/op
|
|
tidwall: get-rand-hint 1,000,000 ops in 191ms, 5,243,833/sec, 190 ns/op
|
|
google: get-rand 1,000,000 ops in 161ms, 6,199,818/sec, 161 ns/op
|
|
```
|
|
|
|
*You can find the benchmark utility at [tidwall/btree-benchmark](https://github.com/tidwall/btree-benchmark)*
|
|
|
|
## Contact
|
|
|
|
Josh Baker [@tidwall](http://twitter.com/tidwall)
|
|
|
|
## License
|
|
|
|
Source code is available under the MIT [License](/LICENSE).
|