mirror of
https://github.com/ergochat/ergo.git
synced 2024-11-25 05:19:25 +01:00
200 lines
5.5 KiB
Markdown
200 lines
5.5 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.
|
|
|
|
## Features
|
|
|
|
- `Copy()` method with copy-on-write support.
|
|
- Fast bulk loading for pre-ordered data using the `Load()` method.
|
|
- All operations are thread-safe.
|
|
- Path hinting optimization for operations with nearby keys.
|
|
|
|
## 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.
|
|
|
|
- `google`: The [google/btree](https://github.com/google/btree) package
|
|
- `tidwall`: The [tidwall/btree](https://github.com/tidwall/btree) package
|
|
- `go-arr`: Just a simple Go array
|
|
|
|
```
|
|
** sequential set **
|
|
google: set-seq 1,000,000 ops in 160ms, 6,262,097/sec, 159 ns/op, 31.0 MB, 32 bytes/op
|
|
tidwall: set-seq 1,000,000 ops in 142ms, 7,020,721/sec, 142 ns/op, 36.6 MB, 38 bytes/op
|
|
tidwall: set-seq-hint 1,000,000 ops in 87ms, 11,503,315/sec, 86 ns/op, 36.6 MB, 38 bytes/op
|
|
tidwall: load-seq 1,000,000 ops in 37ms, 27,177,242/sec, 36 ns/op, 36.6 MB, 38 bytes/op
|
|
go-arr: append 1,000,000 ops in 49ms, 20,574,760/sec, 48 ns/op
|
|
|
|
** random set **
|
|
google: set-rand 1,000,000 ops in 606ms, 1,649,921/sec, 606 ns/op, 21.5 MB, 22 bytes/op
|
|
tidwall: set-rand 1,000,000 ops in 543ms, 1,841,590/sec, 543 ns/op, 26.7 MB, 27 bytes/op
|
|
tidwall: set-rand-hint 1,000,000 ops in 573ms, 1,745,624/sec, 572 ns/op, 26.4 MB, 27 bytes/op
|
|
tidwall: set-again 1,000,000 ops in 452ms, 2,212,581/sec, 451 ns/op, 27.1 MB, 28 bytes/op
|
|
tidwall: set-after-copy 1,000,000 ops in 472ms, 2,117,457/sec, 472 ns/op, 27.9 MB, 29 bytes/op
|
|
tidwall: load-rand 1,000,000 ops in 551ms, 1,816,498/sec, 550 ns/op, 26.1 MB, 27 bytes/op
|
|
|
|
** sequential get **
|
|
google: get-seq 1,000,000 ops in 133ms, 7,497,604/sec, 133 ns/op
|
|
tidwall: get-seq 1,000,000 ops in 110ms, 9,082,972/sec, 110 ns/op
|
|
tidwall: get-seq-hint 1,000,000 ops in 55ms, 18,289,945/sec, 54 ns/op
|
|
|
|
** random get **
|
|
google: get-rand 1,000,000 ops in 149ms, 6,704,337/sec, 149 ns/op
|
|
tidwall: get-rand 1,000,000 ops in 131ms, 7,616,296/sec, 131 ns/op
|
|
tidwall: get-rand-hint 1,000,000 ops in 216ms, 4,632,532/sec, 215 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).
|