Data races are among the most common and hardest to debug types of bugs in concurrent systems. A data race occurs when two goroutines access the same variable concurrently and at least one of the accesses is a write. See the The Go Memory Model for details.
Here is an example of a data race that can lead to crashes and memory corruption:
func main() { c := make(chan bool) m := make(map[string]string) go func() { m["1"] = "a" // First conflicting access. c <- true }() m["2"] = "b" // Second conflicting access. <-c for k, v := range m { fmt.Println(k, v) } }
To help diagnose such bugs, Go includes a built-in data race detector.
To use it, add the -race
flag to the go command:
$ go test -race mypkg // to test the package $ go run -race mysrc.go // to run the source file $ go build -race mycmd // to build the command $ go install -race mypkg // to install the package
When the race detector finds a data race in the program, it prints a report. The report contains stack traces for conflicting accesses, as well as stacks where the involved goroutines were created. Here is an example:
WARNING: DATA RACE Read by goroutine 185: net.(*pollServer).AddFD() src/net/fd_unix.go:89 +0x398 net.(*pollServer).WaitWrite() src/net/fd_unix.go:247 +0x45 net.(*netFD).Write() src/net/fd_unix.go:540 +0x4d4 net.(*conn).Write() src/net/net.go:129 +0x101 net.func·060() src/net/timeout_test.go:603 +0xaf Previous write by goroutine 184: net.setWriteDeadline() src/net/sockopt_posix.go:135 +0xdf net.setDeadline() src/net/sockopt_posix.go:144 +0x9c net.(*conn).SetDeadline() src/net/net.go:161 +0xe3 net.func·061() src/net/timeout_test.go:616 +0x3ed Goroutine 185 (running) created at: net.func·061() src/net/timeout_test.go:609 +0x288 Goroutine 184 (running) created at: net.TestProlongTimeout() src/net/timeout_test.go:618 +0x298 testing.tRunner() src/testing/testing.go:301 +0xe8
The GORACE
environment variable sets race detector options.
The format is:
GORACE="option1=val1 option2=val2"
The options are:
log_path
(default stderr
): The race detector writes
its report to a file named log_path.pid
.
The special names stdout
and stderr
cause reports to be written to standard output and
standard error, respectively.
exitcode
(default 66
): The exit status to use when
exiting after a detected race.
strip_path_prefix
(default ""
): Strip this prefix
from all reported file paths, to make reports more concise.
history_size
(default 1
): The per-goroutine memory
access history is 32K * 2**history_size elements
.
Increasing this value can avoid a "failed to restore the stack" error in reports, at the
cost of increased memory usage.
halt_on_error
(default 0
): Controls whether the program
exits after reporting first data race.
atexit_sleep_ms
(default 1000
): Amount of milliseconds
to sleep in the main goroutine before exiting.
Example:
$ GORACE="log_path=/tmp/race/report strip_path_prefix=/my/go/sources/" go test -race
When you build with -race
flag, the go
command defines additional
build tag race
.
You can use the tag to exclude some code and tests when running the race detector.
Some examples:
// +build !race package foo // The test contains a data race. See issue 123. func TestFoo(t *testing.T) { // ... } // The test fails under the race detector due to timeouts. func TestBar(t *testing.T) { // ... } // The test takes too long under the race detector. func TestBaz(t *testing.T) { // ... }
To start, run your tests using the race detector (go test -race
).
The race detector only finds races that happen at runtime, so it can't find
races in code paths that are not executed.
If your tests have incomplete coverage,
you may find more races by running a binary built with -race
under a realistic
workload.
Here are some typical data races. All of them can be detected with the race detector.
func main() { var wg sync.WaitGroup wg.Add(5) for i := 0; i < 5; i++ { go func() { fmt.Println(i) // Not the 'i' you are looking for. wg.Done() }() } wg.Wait() }
The variable i
in the function literal is the same variable used by the loop, so
the read in the goroutine races with the loop increment.
(This program typically prints 55555, not 01234.)
The program can be fixed by making a copy of the variable:
func main() { var wg sync.WaitGroup wg.Add(5) for i := 0; i < 5; i++ { go func(j int) { fmt.Println(j) // Good. Read local copy of the loop counter. wg.Done() }(i) } wg.Wait() }
// ParallelWrite writes data to file1 and file2, returns the errors. func ParallelWrite(data []byte) chan error { res := make(chan error, 2) f1, err := os.Create("file1") if err != nil { res <- err } else { go func() { // This err is shared with the main goroutine, // so the write races with the write below. _, err = f1.Write(data) res <- err f1.Close() }() } f2, err := os.Create("file2") // The second conflicting write to err. if err != nil { res <- err } else { go func() { _, err = f2.Write(data) res <- err f2.Close() }() } return res }
The fix is to introduce new variables in the goroutines (note the use of :=
):
... _, err := f1.Write(data) ... _, err := f2.Write(data) ...
If the following code is called from several goroutines, it leads to races on the service
map.
Concurrent reads and writes of the same map are not safe:
var service map[string]net.Addr func RegisterService(name string, addr net.Addr) { service[name] = addr } func LookupService(name string) net.Addr { return service[name] }
To make the code safe, protect the accesses with a mutex:
var ( service map[string]net.Addr serviceMu sync.Mutex ) func RegisterService(name string, addr net.Addr) { serviceMu.Lock() defer serviceMu.Unlock() service[name] = addr } func LookupService(name string) net.Addr { serviceMu.Lock() defer serviceMu.Unlock() return service[name] }
Data races can happen on variables of primitive types as well (bool
, int
, int64
, etc.),
as in this example:
type Watchdog struct{ last int64 } func (w *Watchdog) KeepAlive() { w.last = time.Now().UnixNano() // First conflicting access. } func (w *Watchdog) Start() { go func() { for { time.Sleep(time.Second) // Second conflicting access. if w.last < time.Now().Add(-10*time.Second).UnixNano() { fmt.Println("No keepalives for 10 seconds. Dying.") os.Exit(1) } } }() }
Even such "innocent" data races can lead to hard-to-debug problems caused by non-atomicity of the memory accesses, interference with compiler optimizations, or reordering issues accessing processor memory .
A typical fix for this race is to use a channel or a mutex.
To preserve the lock-free behavior, one can also use the
sync/atomic
package.
type Watchdog struct{ last int64 } func (w *Watchdog) KeepAlive() { atomic.StoreInt64(&w.last, time.Now().UnixNano()) } func (w *Watchdog) Start() { go func() { for { time.Sleep(time.Second) if atomic.LoadInt64(&w.last) < time.Now().Add(-10*time.Second).UnixNano() { fmt.Println("No keepalives for 10 seconds. Dying.") os.Exit(1) } } }() }
As this example demonstrates, unsynchronized send and close operations on the same channel can also be a race condition:
c := make(chan struct{}) // or buffered channel // The race detector cannot derive the happens before relation // for the following send and close operations. These two operations // are unsynchronized and happen concurrently. go func() { c <- struct{}{} }() close(c)
According to the Go memory model, a send on a channel happens before the corresponding receive from that channel completes. To synchronize send and close operations, use a receive operation that guarantees the send is done before the close:
c := make(chan struct{}) // or buffered channel go func() { c <- struct{}{} }() <-c close(c)
The race detector runs on
linux/amd64
, linux/ppc64le
,
linux/arm64
, freebsd/amd64
,
netbsd/amd64
, darwin/amd64
,
darwin/arm64
, and windows/amd64
.
The cost of race detection varies by program, but for a typical program, memory usage may increase by 5-10x and execution time by 2-20x.
The race detector currently allocates an extra 8 bytes per defer
and recover
statement. Those extra allocations are not recovered until the goroutine
exits. This means that if you have a long-running goroutine that is
periodically issuing defer
and recover
calls,
the program memory usage may grow without bound. These memory allocations
will not show up in the output of runtime.ReadMemStats
or
runtime/pprof
.