bigopool
is a small library that implements high performance worker pool in Golang and allows error
/result
handling in the main thread.
It also provides a thread safe parallel processing abstraction
install:
go get -u github.com/bigodines/bigopool
Use this whenever the number of jobs you have is too large to run as goroutines at the same time.
implement this simple interface:
type TestJob {
// your properties go here
}
func (j TestJob) Execute() (bigopool.Result, error) {
// your logic here.
// Result is an interface{}
return "anything", nil
}
add to your code:
// configure dispatcher to run 5 workers with a queue of capacity 100
dispatcher, err := bigopool.NewDispatcher(5, 100)
if err != nil {
panic(err)
}
// spawn workers
dispatcher.Run()
// send work items
dispatcher.Enqueue(TestJob{}) // <-- add one job
dispatcher.Enqueue(TestJob{}, TestJob{}) // <-- add multiple jobs
// wait for workers to finish (this is a blocking call)
results, errs := dispatcher.Wait()
// Note we've opted to use our own thread safe error module (it still implements the `error` interface but if you want to get a []error,
// use errs.All())
💥
Use this if you don't need worker pools and just want to execute tasks in parallel
run multiple functions in parallel:
func UploadAndDownload() error {
var email string
errs := bigopool.Parallel(
func() error {
return api.Post(Request{Order: 123123})
},
func() error {
user, err := api.Get(Request{ID: 1234})
if err != nil {
return err
}
email = user.Email
return nil
},
)
fmt.Println("email:", email)
return errs.ToError()
}
If you can fix a bug or make it faster, I'll buy you coffee. PRs that drop code coverage will not be merged.
box specs:
MacBook Pro (Retina, 15-inch, 2016)
Processor 2,7 GHz QUad-Core Intel Core i7
Memory 16 GB 2133 MHz LPDDR3
$ go test -bench=. -benchmem=true -cpu=1,2,4,8 -run Bench
goos: darwin
goarch: amd64
pkg: github.com/bigodines/bigopool
Benchmark1Workers1Queue 1756252 687 ns/op 98 B/op 0 allocs/op
Benchmark1Workers1Queue-2 1209124 1041 ns/op 91 B/op 0 allocs/op
Benchmark1Workers1Queue-4 1242471 953 ns/op 89 B/op 0 allocs/op
Benchmark1Workers1Queue-8 1151955 1023 ns/op 96 B/op 0 allocs/op
Benchmark5Workers1000Queue 2190982 566 ns/op 98 B/op 0 allocs/op
Benchmark5Workers1000Queue-2 1960696 610 ns/op 88 B/op 0 allocs/op
Benchmark5Workers1000Queue-4 1727991 692 ns/op 80 B/op 0 allocs/op
Benchmark5Workers1000Queue-8 1508758 773 ns/op 91 B/op 0 allocs/op
Benchmark10Workers100Queue 2168791 559 ns/op 79 B/op 0 allocs/op
Benchmark10Workers100Queue-2 1961818 624 ns/op 88 B/op 0 allocs/op
Benchmark10Workers100Queue-4 1672346 702 ns/op 82 B/op 0 allocs/op
Benchmark10Workers100Queue-8 1382486 864 ns/op 80 B/op 0 allocs/op
Benchmark20Workers200Queue 2159338 572 ns/op 80 B/op 0 allocs/op
Benchmark20Workers200Queue-2 1967389 608 ns/op 88 B/op 0 allocs/op
Benchmark20Workers200Queue-4 1765658 711 ns/op 98 B/op 0 allocs/op
Benchmark20Workers200Queue-8 1445559 838 ns/op 95 B/op 0 allocs/op
Benchmark20Workers10000Queue 2220480 551 ns/op 97 B/op 0 allocs/op
Benchmark20Workers10000Queue-2 1990562 629 ns/op 87 B/op 0 allocs/op
Benchmark20Workers10000Queue-4 1721840 684 ns/op 80 B/op 0 allocs/op
Benchmark20Workers10000Queue-8 1417897 835 ns/op 97 B/op 0 allocs/op
Benchmark100Workers10000Queue 2206069 556 ns/op 98 B/op 0 allocs/op
Benchmark100Workers10000Queue-2 2074681 586 ns/op 83 B/op 0 allocs/op
Benchmark100Workers10000Queue-4 1824800 685 ns/op 95 B/op 0 allocs/op
Benchmark100Workers10000Queue-8 1537908 785 ns/op 90 B/op 0 allocs/op
PASS
ok github.com/bigodines/bigopool 46.191s
MIT