neilotoole/errgroup
is a drop-in alternative to Go's wonderful
sync/errgroup
but
limited to N
goroutines. This is useful for interaction with rate-limited
APIs, databases, and the like.
Note The
sync/errgroup
package now has a Group.SetLimit method, which eliminates the need forneilotoole/errgroup
. This package will no longer be maintained. Usesync/errgroup
instead.
In effect, neilotoole/errgroup
is sync/errgroup
but with a worker pool
of N
goroutines. The exported API is identical but for an additional
function WithContextN
, which allows the caller
to specify the maximum number of goroutines (numG
) and the capacity
of the queue channel (qSize
) used to hold work before it is picked
up by a worker goroutine. The zero Group
and the Group
returned
by WithContext
have numG
and qSize
equal to runtime.NumCPU
.
The exported API of this package mirrors the sync/errgroup
package.
The only change needed is the import path of the package, from:
import (
"golang.org/x/sync/errgroup"
)
to
import (
"github.com/neilotoole/errgroup"
)
Then use in the normal manner. See the godoc for more.
g, ctx := errgroup.WithContext(ctx)
g.Go(func() error {
// do something
return nil
})
err := g.Wait()
Many users will have no need to tweak the numG
and qCh
params. However, benchmarking
may suggest particular values for your workload. For that you'll need WithContextN
:
numG, qSize := 8, 4
g, ctx := errgroup.WithContextN(ctx, numG, qSize)
The motivation for creating neilotoole/errgroup
was to provide rate-limiting while
maintaining the lovely sync/errgroup
semantics. Sacrificing some
performance vs sync/errgroup
was assumed. However, benchmarking
suggests that this implementation can be more effective than sync/errgroup
when tuned for a specific workload.
Below is a selection of benchmark results. How to read this: a workload is X tasks of Y complexity. The workload is executed for:
sync/errgroup
, listed assync_errgroup
- a non-parallel implementation (
sequential
) - various
{numG, qSize}
configurations ofneilotoole/errgroup
, listed aserrgroupn_{numG}_{qSize}
BenchmarkGroup_Short/complexity_5/tasks_50/errgroupn_default_16_16-16 25574 46867 ns/op 688 B/op 12 allocs/op
BenchmarkGroup_Short/complexity_5/tasks_50/errgroupn_4_4-16 24908 48926 ns/op 592 B/op 12 allocs/op
BenchmarkGroup_Short/complexity_5/tasks_50/errgroupn_16_4-16 24895 48313 ns/op 592 B/op 12 allocs/op
BenchmarkGroup_Short/complexity_5/tasks_50/errgroupn_32_4-16 24853 48284 ns/op 592 B/op 12 allocs/op
BenchmarkGroup_Short/complexity_5/tasks_50/sync_errgroup-16 18784 65826 ns/op 1858 B/op 55 allocs/op
BenchmarkGroup_Short/complexity_5/tasks_50/sequential-16 10000 111483 ns/op 0 B/op 0 allocs/op
BenchmarkGroup_Short/complexity_20/tasks_50/errgroupn_default_16_16-16 3745 325993 ns/op 1168 B/op 27 allocs/op
BenchmarkGroup_Short/complexity_20/tasks_50/errgroupn_4_4-16 5186 227034 ns/op 1072 B/op 27 allocs/op
BenchmarkGroup_Short/complexity_20/tasks_50/errgroupn_16_4-16 3970 312816 ns/op 1076 B/op 27 allocs/op
BenchmarkGroup_Short/complexity_20/tasks_50/errgroupn_32_4-16 3715 320757 ns/op 1073 B/op 27 allocs/op
BenchmarkGroup_Short/complexity_20/tasks_50/sync_errgroup-16 2739 432093 ns/op 1862 B/op 55 allocs/op
BenchmarkGroup_Short/complexity_20/tasks_50/sequential-16 2306 520947 ns/op 0 B/op 0 allocs/op
BenchmarkGroup_Short/complexity_40/tasks_250/errgroupn_default_16_16-16 354 3602666 ns/op 1822 B/op 47 allocs/op
BenchmarkGroup_Short/complexity_40/tasks_250/errgroupn_4_4-16 420 2468605 ns/op 1712 B/op 47 allocs/op
BenchmarkGroup_Short/complexity_40/tasks_250/errgroupn_16_4-16 334 3581349 ns/op 1716 B/op 47 allocs/op
BenchmarkGroup_Short/complexity_40/tasks_250/errgroupn_32_4-16 310 3890316 ns/op 1712 B/op 47 allocs/op
BenchmarkGroup_Short/complexity_40/tasks_250/sync_errgroup-16 253 4740462 ns/op 8303 B/op 255 allocs/op
BenchmarkGroup_Short/complexity_40/tasks_250/sequential-16 200 5924693 ns/op 0 B/op 0 allocs/op
The overall impression is that neilotoole/errgroup
can provide higher
throughput than sync/errgroup
for these (CPU-intensive) workloads,
sometimes significantly so. As always, these benchmark results should
not be taken as gospel: your results may vary.
Why require an explicit qSize
limit?
If the number of calls to Group.Go
results in qCh
becoming
full, the Go
method will block until worker goroutines relieve qCh
.
This behavior is in contrast to sync/errgroup
's Go
method, which doesn't block.
While neilotoole/errgroup
aims to be as much of a behaviorally similar
"drop-in" alternative to sync/errgroup
as possible, this blocking behavior
is a conscious deviation.
Noting that the capacity of qCh
is controlled by qSize
, it's probable an
alternative implementation could be built that uses a (growable) slice
acting - if qCh
is full - as a buffer for functions passed to Go
.
Consideration of this potential design led to this issue
regarding unlimited capacity channels, or perhaps better characterized
in this particular case as "growable capacity channels". If such a
feature existed in the language, it's possible that this implementation might
have taken advantage of it, at least in the first-pass release (benchmarking notwithstanding).
However benchmarking seems to suggest that a relatively
small qSize
has performance benefits for some workloads, so it's possible
that the explicit qSize
requirement is a better design choice regardless.