I am new to Golang and starting to use goroutines. I am curious if it is safe to read from a data structure that is being written to by another goroutines without using channel or mutex. In the example below, the events array is visible to main and goroutine, but main only reads from it and the goroutine is modifying it. Is this considered safe?
var events = []string{}
func main() {
go func() {
for {
if len(events) > 30 {
events = nil
}
event := "The time is now " + time.Now().String()
events = append(events, event)
time.Sleep(time.Millisecond * 200)
}
}()
for {
for i:=0; i < len(events); i++ {
fmt.Println(events[i])
}
time.Sleep(time.Millisecond * 100)
fmt.Println("--------------------------------------------------------")
}
}
Thanks.
No, this is absolutely not safe. You should use synchronization primitives around access to events, or redesign to use channels.
Your code may work fine today, on a specific architecture/OS, but it may break unexpectedly with small changes and/or on another architecture/OS.
Try to run your code with -race to verify. You'll probably see WARNING: DATA RACE.
See also this answer.
Related
In Go, a sync.Mutex or chan is used to prevent concurrent access of shared objects. However, in some cases I am just interested in the "latest" value of a variable or field of an object.
Or I like to write a value and do not care if another go-routine overwrites it later or has just overwritten it before.
Update: TLDR; Just don't do this. It is not safe. Read the answers, comments, and linked documents!
Update 2021: The Go memory model is going to be specified more thoroughly and there are three great articles by Russ Cox that will teach you more about the surprising effects of unsynchronized memory access. These articles summarize a lot of the below discussions and learnings.
Here are two variants good and bad of an example program, where both seem to produce "correct" output using the current Go runtime:
package main
import (
"flag"
"fmt"
"math/rand"
"time"
)
var bogus = flag.Bool("bogus", false, "use bogus code")
func pause() {
time.Sleep(time.Duration(rand.Uint32()%100) * time.Millisecond)
}
func bad() {
stop := time.After(100 * time.Millisecond)
var name string
// start some producers doing concurrent writes (DANGER!)
for i := 0; i < 10; i++ {
go func(i int) {
pause()
name = fmt.Sprintf("name = %d", i)
}(i)
}
// start consumer that shows the current value every 10ms
go func() {
tick := time.Tick(10 * time.Millisecond)
for {
select {
case <-stop:
return
case <-tick:
fmt.Println("read:", name)
}
}
}()
<-stop
}
func good() {
stop := time.After(100 * time.Millisecond)
names := make(chan string, 10)
// start some producers concurrently writing to a channel (GOOD!)
for i := 0; i < 10; i++ {
go func(i int) {
pause()
names <- fmt.Sprintf("name = %d", i)
}(i)
}
// start consumer that shows the current value every 10ms
go func() {
tick := time.Tick(10 * time.Millisecond)
var name string
for {
select {
case name = <-names:
case <-stop:
return
case <-tick:
fmt.Println("read:", name)
}
}
}()
<-stop
}
func main() {
flag.Parse()
if *bogus {
bad()
} else {
good()
}
}
The expected output is as follows:
...
read: name = 3
read: name = 3
read: name = 5
read: name = 4
...
Any combination of read: and read: name=[0-9] is correct output for this program. Receiving any other string as output would be an error.
When running this program with go run --race bogus.go it is safe.
However, go run --race bogus.go -bogus warns of the concurrent reads and writes.
For map types and when appending to slices I always need a mutex or a similar method of protection to avoid segfaults or unexpected behavior. However, reading and writing literals (atomic values) to variables or field values seems to be safe.
Question: Which Go data types can I safely read and safely write concurrently without a mutext and without producing segfaults and without reading garbage from memory?
Please explain why something is safe or unsafe in Go in your answer.
Update: I rewrote the example to better reflect the original code, where I had the the concurrent writes issue. The important leanings are already in the comments. I will accept an answer that summarizes these learnings with enough detail (esp. on the Go-runtime).
However, in some cases I am just interested in the latest value of a variable or field of an object.
Here is the fundamental problem: What does the word "latest" mean?
Suppoose that, mathematically speaking, we have a sequence of values Xi, with 0 <= i < N. Then obviously Xj is "later than" Xi if j > i. That's a nice simple definition of "latest" and is probably the one you want.
But when two separate CPUs within a single machine—including two goroutines in a Go program—are working at the same time, time itself loses meaning. We cannot say whether i < j, i == j, or i > j. So there is no correct definition for the word latest.
To solve this kind of problem, modern CPU hardware, and Go as a programming language, gives us certain synchronization primitives. If CPUs A and B execute memory fence instructions, or synchronization instructions, or use whatever other hardware provisions exist, the CPUs (and/or some external hardware) will insert whatever is required for the notion of "time" to regain its meaning. That is, if the CPU uses barrier instructions, we can say that a memory load or store that was executed before the barrier is a "before" and a memory load or store that is executed after the barrier is an "after".
(The actual implementation, in some modern hardware, consists of load and store buffers that can rearrange the order in which loads and stores go to memory. The barrier instruction either synchronizes the buffers, or places an actual barrier in them, so that loads and stores cannot move across the barrier. This particular concrete implementation gives an easy way to think about the problem, but isn't complete: you should think of time as simply not existing outside the hardware-provided synchronization, i.e., all loads from, and stores to, some location are happening simultaneously, rather than in some sequential order, except for these barriers.)
In any case, Go's sync package gives you a simple high level access method to these kinds of barriers. Compiled code that executes before a mutex Lock call really does complete before the lock function returns, and the code that executes after the call really does not start until after the lock function returns.
Go's channels provide the same kinds of before/after time guarantees.
Go's sync/atomic package provides much lower level guarantees. In general you should avoid this in favor of the higher level channel or sync.Mutex style guarantees. (Edit to add note: You could use sync/atomic's Pointer operations here, but not with the string type directly, as Go strings are actually implemented as a header containing two separate values: a pointer, and a length. You could solve this with another layer of indirection, by updating a pointer that points to the string object. But before you even consider doing that, you should benchmark the use of the language's preferred methods and verify that these are a problem, because code that works at the sync/atomic level is hard to write and hard to debug.)
Which Go data types can I safely read and safely write concurrently without a mutext and without producing segfaults and without reading garbage from memory?
None.
It really is that simple: You cannot, under no circumstance whatsoever, read and write concurrently to anything in Go.
(Btw: Your "correct" program is not correct, it is racy and even if you get rid of the race condition it would not deterministically produce the output.)
Why can't you use channels
package main
import (
"fmt"
"sync"
)
func main() {
var wg sync.WaitGroup // wait group to close channel
var buffer int = 1 // buffer of the channel
// channel to get the share data
cName := make(chan string, buffer)
for i := 0; i < 10; i++ {
wg.Add(1) // add to wait group
go func(i int) {
cName <- fmt.Sprintf("name = %d", i)
wg.Done() // decrease wait group.
}(i)
}
go func() {
wg.Wait() // wait of wait group to be 0
close(cName) // close the channel
}()
// process all the data
for n := range cName {
println("read:", n)
}
}
The above code returns the following output
read: name = 0
read: name = 5
read: name = 1
read: name = 2
read: name = 3
read: name = 4
read: name = 7
read: name = 6
read: name = 8
read: name = 9
https://play.golang.org/p/R4n9ssPMOeS
Article about channels
How can one only attempt to acquire a mutex-like lock in go, either aborting immediately (like TryLock does in other implementations) or by observing some form of deadline (basically LockBefore)?
I can think of 2 situations right now where this would be greatly helpful and where I'm looking for some sort of solution. The first one is: a CPU-heavy service which receives latency sensitive requests (e.g. a web service). In this case you would want to do something like the RPCService example below. It is possible to implement it as a worker queue (with channels and stuff), but in that case it becomes more difficult to gauge and utilize all available CPU. It is also possible to just accept that by the time you acquire the lock your code may already be over deadline, but that is not ideal as it wastes some amount of resources and means we can't do things like a "degraded ad-hoc response".
/* Example 1: LockBefore() for latency sensitive code. */
func (s *RPCService) DoTheThing(ctx context.Context, ...) ... {
if s.someObj[req.Parameter].mtx.LockBefore(ctx.Deadline()) {
defer s.someObj[req.Parameter].mtx.Unlock()
... expensive computation based on internal state ...
} else {
return s.cheapCachedResponse[req.Parameter]
}
}
Another case is when you have a bunch of objects which should be touched, but which may be locked, and where touching them should complete within a certain amount of time (e.g. updating some stats). In this case you could also either use LockBefore() or some form of TryLock(), see the Stats example below.
/* Example 2: TryLock() for updating stats. */
func (s *StatsObject) updateObjStats(key, value interface{}) {
if s.someObj[key].TryLock() {
defer s.someObj[key].Unlock()
... update stats ...
... fill in s.cheapCachedResponse ...
}
}
func (s *StatsObject) UpdateStats() {
s.someObj.Range(s.updateObjStats)
}
For ease of use, let's assume that in the above case we're talking about the same s.someObj. Any object may be blocked by DoTheThing() operations for a long time, which means we would want to skip it in updateObjStats. Also, we would want to make sure that we return the cheap response in DoTheThing() in case we can't acquire a lock in time.
Unfortunately, sync.Mutex only and exclusively has the functions Lock() and Unlock(). There is no way to potentially acquire a lock. Is there some easy way to do this instead? Am I approaching this class of problems from an entirely wrong angle, and is there a different, more "go"ish way to solve them? Or will I have to implement my own Mutex library if I want to solve these? I am aware of issue 6123 which seems to suggest that there is no such thing and that the way I'm approaching these problems is entirely un-go-ish.
Use a channel with buffer size of one as mutex.
l := make(chan struct{}, 1)
Lock:
l <- struct{}{}
Unlock:
<-l
Try lock:
select {
case l <- struct{}{}:
// lock acquired
<-l
default:
// lock not acquired
}
Try with timeout:
select {
case l <- struct{}{}:
// lock acquired
<-l
case <-time.After(time.Minute):
// lock not acquired
}
I think you're asking several different things here:
Does this facility exist in the standard libray? No, it doesn't. You can probably find implementations elsewhere - this is possible to implement using the standard library (atomics, for example).
Why doesn't this facility exist in the standard library: the issue you mentioned in the question is one discussion. There are also several discussions on the go-nuts mailing list with several Go code developers contributing: link 1, link 2. And it's easy to find other discussions by googling.
How can I design my program such that I won't need this?
The answer to (3) is more nuanced and depends on your exact issue. Your question already says
It is possible to implement it as a worker queue (with channels and
stuff), but in that case it becomes more difficult to gauge and
utilize all available CPU
Without providing details on why it would be more difficult to utilize all CPUs, as opposed to checking for a mutex lock state.
In Go you usually want channels whenever the locking schemes become non-trivial. It shouldn't be slower, and it should be much more maintainable.
How about this package: https://github.com/viney-shih/go-lock . It use channel and semaphore (golang.org/x/sync/semaphore) to solve your problem.
go-lock implements TryLock, TryLockWithTimeout and TryLockWithContext functions in addition to Lock and Unlock. It provides flexibility to control the resources.
Examples:
package main
import (
"fmt"
"time"
"context"
lock "github.com/viney-shih/go-lock"
)
func main() {
casMut := lock.NewCASMutex()
casMut.Lock()
defer casMut.Unlock()
// TryLock without blocking
fmt.Println("Return", casMut.TryLock()) // Return false
// TryLockWithTimeout without blocking
fmt.Println("Return", casMut.TryLockWithTimeout(50*time.Millisecond)) // Return false
// TryLockWithContext without blocking
ctx, cancel := context.WithTimeout(context.Background(), 50*time.Millisecond)
defer cancel()
fmt.Println("Return", casMut.TryLockWithContext(ctx)) // Return false
// Output:
// Return false
// Return false
// Return false
}
PMutex from package https://github.com/myfantasy/mfs
PMutex implements RTryLock(ctx context.Context) and TryLock(ctx context.Context)
// ctx - some context
ctx := context.Background()
mx := mfs.PMutex{}
isLocked := mx.TryLock(ctx)
if isLocked {
// DO Something
mx.Unlock()
} else {
// DO Something else
}
For some reason, when I remove the fmt.Printlns then the code is blocking.
I've got no idea why it happens. All I want to do is to implement a simple concurrency limiter...
I've never experienced such a weird thing. It's like that fmt flushes the variables or something and makes it work.
Also, when I use a regular function instead of a goroutine then it works too.
Here's the following code -
package main
import "fmt"
type ConcurrencyLimit struct {
active int
Limit int
}
func (c *ConcurrencyLimit) Block() {
for {
fmt.Println(c.active, c.Limit)
// If should block
if c.active == c.Limit {
continue
}
c.active++
break
}
}
func (c *ConcurrencyLimit) Decrease() int {
fmt.Println("decrease")
if c.active > 0 {
c.active--
}
return c.active
}
func main() {
c := ConcurrencyLimit{Limit: 1}
c.Block()
go func() {
c.Decrease()
}()
c.Block()
}
Clarification: Even though I've accepted #kaedys 's answer(here) a solution was answered by #Kaveh Shahbazian (here)
You're not giving c.Decrease() a chance to run. c.Block() runs an infinite for loop, but it never blocks in that for loop, just calling continue over and over on every iteration. The main thread spins at 100% usage endlessly.
However, when you add an fmt.Print() call, that makes a syscall, which allows the other goroutine to run.
This post has details on how exactly goroutines yield or are pre-empted. Note, however, that it's slightly out of date, as entering a function now has a random chance to yield that thread to another goroutine, to prevent similar style flooding of threads.
As others have pointed out, Block() will never yield; a goroutine is not a thread. You could use Gosched() in the runtime package to force a yield -- but note that spinning this way in Block() is a pretty terrible idea.
There are much better ways to do concurrency limiting. See http://jmoiron.net/blog/limiting-concurrency-in-go/ for one example
What you are looking for is called a semaphore. You can apply this pattern using channels
http://www.golangpatterns.info/concurrency/semaphores
The idea is that you create a buffered channel of a desired length. Then you make callers acquire the resource by putting a value into the channel and reading it back out when they want to free the resource. Doing so creates proper synchronization points in your program so that the Go scheduler runs correctly.
What you are doing now is spinning the cpu and blocking the Go scheduler. It depends on how many cpus you have available, the version of Go, and the value of GOMAXPROCS. Given the right combination, there may not be another available thread to service other goroutines while you infinitely spin that particular thread.
While other answers pretty much covered the reason (not giving a chance for the goroutine to run) - and I'm not sure what you intend to achieve here - you are mutating a value concurrently without proper synchronization. A rewrite of above code with synchronization considered; would be:
type ConcurrencyLimit struct {
active int
Limit int
cond *sync.Cond
}
func (c *ConcurrencyLimit) Block() {
c.cond.L.Lock()
for c.active == c.Limit {
c.cond.Wait()
}
c.active++
c.cond.L.Unlock()
c.cond.Signal()
}
func (c *ConcurrencyLimit) Decrease() int {
defer c.cond.Signal()
c.cond.L.Lock()
defer c.cond.L.Unlock()
fmt.Println("decrease")
if c.active > 0 {
c.active--
}
return c.active
}
func main() {
c := ConcurrencyLimit{
Limit: 1,
cond: &sync.Cond{L: &sync.Mutex{}},
}
c.Block()
go func() {
c.Decrease()
}()
c.Block()
fmt.Println(c.active, c.Limit)
}
sync.Cond is a synchronization utility designed for times that you want to check if a condition is met, concurrently; while other workers are mutating the data of the condition.
The Lock and Unlock functions work as we expect from a lock. When we are done with checking or mutating, we can call Signal to awake one goroutine (or call Broadcast to awake more than one), so the goroutine knows that is free to act upon the data (or check a condition).
The only part that may seem unusual is the Wait function. It is actually very simple. It is like calling Unlock and instantly call Lock again - with the exception that Wait would not try to lock again, unless triggered by Signal (or Broadcast) in other goroutines; like the workers that are mutating the data (of the condition).
I have a code like,
Routine 1 {
runtime.LockOSThread()
print something
send int to routine 2
runtime.UnlockOSThread
}
Routine 2 {
runtime.LockOSThread()
print something
send int to routine 1
runtime.UnlockOSThread
}
main {
go Routine1
go Routine2
}
I use run time lock-unlock because, I don't want that printing of
Routine 1 will mix with Routine 2. However, after execution of above
code, it outputs same as without lock-unlock (means printing outputs
mixed). Can anybody help me why this thing happening and how to force
this for happening.
NB: I give an example of print something, however there are lots of
printing and sending events.
If you want to serialize "print something", e.g. each "print something" should perform atomically, then just serialize it.
You can surround "print something" by a mutex. That'll work unless the code deadlock because of that - and surely it easily can in a non trivial program.
The easy way in Go to serialize something is to do it with a channel. Collect in a (go)routine everything which should be printed together. When collection of the print unit is done, send it through a channel to some printing "agent" as a "print job" unit. That agent will simply receive its "tasks" and atomically print each one. One gets that atomicity for free and as an important bonus the code can not deadlock easily no more in the simple case, where there are only non interdependent "print unit" generating goroutines.
I mean something like:
func printer(tasks chan string) {
for s := range tasks {
fmt.Printf(s)
}
}
func someAgentX(tasks chan string) {
var printUnit string
//...
tasks <- printUnit
//...
}
func main() {
//...
tasks := make(chan string, size)
go printer(tasks)
go someAgent1(tasks)
//...
go someAgentN(tasks)
//...
<- allDone
close(tasks)
}
What runtime.LockOSThread does is prevent any other goroutine from running on the same thread. It forces the runtime to create a new thread and run Routine2 there. They are still running concurrently but on different threads.
You need to use sync.Mutex or some channel magic instead.
You rarely need to use runtime.LockOSThread but it can be useful for forcing some higher priority goroutine to run on a thread of it's own.
package main
import (
"fmt"
"sync"
"time"
)
var m sync.Mutex
func printing(s string) {
m.Lock() // Other goroutines will stop here if until m is unlocked
fmt.Println(s)
m.Unlock() // Now another goroutine at "m.Lock()" can continue running
}
func main() {
for i := 0; i < 10; i++ {
go printing(fmt.Sprintf("Goroutine #%d", i))
}
<-time.After(3e9)
}
I think, this is because of runtime.LockOSThread(),runtime.UnlockOSThread does not work all time. It totaly depends on CPU, execution environment etc. It can't be forced by anyother way.
So, right now, I just pass a pointer to a Queue object (implementation doesn't really matter) and call queue.add(result) at the end of goroutines that should add things to the queue.
I need that same sort of functionality—and of course doing a loop checking completion with the comma ok syntax is unacceptable in terms of performance versus the simple queue add function call.
Is there a way to do this better, or not?
There are actually two parts to your question: how does one queue data in Go, and how does one use a channel without blocking.
For the first part, it sounds like what you need to do is instead of using the channel to add things to the queue, use the channel as a queue. For example:
var (
ch = make(chan int) // You can add an int parameter to this make call to create a buffered channel
// Do not buffer these channels!
gFinished = make(chan bool)
processFinished = make(chan bool)
)
func f() {
go g()
for {
// send values over ch here...
}
<-gFinished
close(ch)
}
func g() {
// create more expensive objects...
gFinished <- true
}
func processObjects() {
for val := range ch {
// Process each val here
}
processFinished <- true
}
func main() {
go processObjects()
f()
<-processFinished
}
As for how you can make this more asynchronous, you can (as cthom06 pointed out) pass a second integer to the make call in the second line which will make send operations asynchronous until the channel's buffer is full.
EDIT: However (as cthom06 also pointed out), because you have two goroutines writing to the channel, one of them has to be responsible for closing the channel. Also, my previous revision would exit before processObjects could complete. The way I chose to synchronize the goroutines is by creating a couple more channels that pass around dummy values to ensure that the cleanup gets finished properly. Those channels are specifically unbuffered so that the sends happen in lock-step.