Concurrent access to maps with 'range' in Go - for-loop

The "Go maps in action" entry in the Go blog states:
Maps are not safe for concurrent use: it's not defined what happens when you read and write to them simultaneously. If you need to read from and write to a map from concurrently executing goroutines, the accesses must be mediated by some kind of synchronization mechanism. One common way to protect maps is with sync.RWMutex.
However, one common way to access maps is to iterate over them with the range keyword. It is not clear if for the purposes of concurrent access, execution inside a range loop is a "read", or just the "turnover" phase of that loop. For example, the following code may or may not run afoul of the "no concurrent r/w on maps" rule, depending on the specific semantics / implementation of the range operation:
var testMap map[int]int
testMapLock := make(chan bool, 1)
testMapLock <- true
testMapSequence := 0
...
func WriteTestMap(k, v int) {
<-testMapLock
testMap[k] = v
testMapSequence++
testMapLock<-true
}
func IterateMapKeys(iteratorChannel chan int) error {
<-testMapLock
defer func() {
testMapLock <- true
}
mySeq := testMapSequence
for k, _ := range testMap {
testMapLock <- true
iteratorChannel <- k
<-testMapLock
if mySeq != testMapSequence {
close(iteratorChannel)
return errors.New("concurrent modification")
}
}
return nil
}
The idea here is that the range "iterator" is open when the second function is waiting for a consumer to take the next value, and the writer is not blocked at that time. However, it is never the case that two reads in a single iterator are on either side of a write - this is a "fail fast" iterator, the borrow a Java term.
Is there anything anywhere in the language specification or other documents that indicates if this is a legitimate thing to do, however? I could see it going either way, and the above quoted document is not clear on exactly what consititutes a "read". The documentation seems totally quiet on the concurrency aspects of the for/range statement.
(Please note this question is about the currency of for/range, but not a duplicate of: Golang concurrent map access with range - the use case is completely different and I am asking about the precise locking requirement wrt the 'range' keyword here!)

You are using a for statement with a range expression. Quoting from Spec: For statements:
The range expression is evaluated once before beginning the loop, with one exception: if the range expression is an array or a pointer to an array and at most one iteration variable is present, only the range expression's length is evaluated; if that length is constant, by definition the range expression itself will not be evaluated.
We're ranging over a map, so it's not an exception: the range expression is evaluated only once before beginning the loop. The range expression is simply a map variable testMap:
for k, _ := range testMap {}
The map value does not include the key-value pairs, it only points to a data structure that does. Why is this important? Because the map value is only evaluated once, and if later pairs are added to the map, the map value –evaluated once before the loop– will be a map that still points to a data structure that includes those new pairs. This is in contrast to ranging over a slice (which would be evaluated once too), which is also only a header pointing to a backing array holding the elements; but if elements are added to the slice during the iteration, even if that does not result in allocating and copying over to a new backing array, they will not be included in the iteration (because the slice header also contains the length - already evaluated). Appending elements to a slice may result in a new slice value, but adding pairs to a map will not result in a new map value.
Now on to iteration:
for k, v := range testMap {
t1 := time.Now()
someFunction()
t2 := time.Now()
}
Before we enter into the block, before the t1 := time.Now() line k and v variables are holding the values of the iteration, they are already read out from the map (else they couldn't hold the values). Question: do you think the map is read by the for ... range statement between t1 and t2? Under what circumstances could that happen? We have here a single goroutine that is executing someFunc(). To be able to access the map by the for statement, that would either require another goroutine, or it would require to suspend someFunc(). Obviously neither of those happen. (The for ... range construct is not a multi-goroutine monster.) No matter how many iterations there are, while someFunc() is executed, the map is not accessed by the for statement.
So to answer one of your questions: the map is not accessed inside the for block when executing an iteration, but it is accessed when the k and v values are set (assigned) for the next iteration. This implies that the following iteration over the map is safe for concurrent access:
var (
testMap = make(map[int]int)
testMapLock = &sync.RWMutex{}
)
func IterateMapKeys(iteratorChannel chan int) error {
testMapLock.RLock()
defer testMapLock.RUnlock()
for k, v := range testMap {
testMapLock.RUnlock()
someFunc()
testMapLock.RLock()
if someCond {
return someErr
}
}
return nil
}
Note that unlocking in IterateMapKeys() should (must) happen as a deferred statement, as in your original code you may return "early" with an error, in which case you didn't unlock, which means the map remained locked! (Here modeled by if someCond {...}).
Also note that this type of locking only ensures locking in case of concurrent access. It does not prevent a concurrent goroutine to modify (e.g. add a new pair) the map. The modification (if properly guarded with write lock) will be safe, and the loop may continue, but there is no guarantee that the for loop will iterate over the new pair:
If map entries that have not yet been reached are removed during iteration, the corresponding iteration values will not be produced. If map entries are created during iteration, that entry may be produced during the iteration or may be skipped. The choice may vary for each entry created and from one iteration to the next.
The write-lock-guarded modification may look like this:
func WriteTestMap(k, v int) {
testMapLock.Lock()
defer testMapLock.Unlock()
testMap[k] = v
}
Now if you release the read lock in the block of the for, a concurrent goroutine is free to grab the write lock and make modifications to the map. In your code:
testMapLock <- true
iteratorChannel <- k
<-testMapLock
When sending k on the iteratorChannel, a concurrent goroutine may modify the map. This is not just an "unlucky" scenario, sending a value on a channel is often a "blocking" operation, if the channel's buffer is full, another goroutine must be ready to receive in order for the send operation to proceed. Sending a value on a channel is a good scheduling point for the runtime to run other goroutines even on the same OS thread, not to mention if there are multiple OS threads, of which one may already be "waiting" for the write lock in order to carry out a map modification.
To sum the last part: you releasing the read lock inside the for block is like yelling to others: "Come, modify the map now if you dare!" Consequently in your code encountering that mySeq != testMapSequence is very likely. See this runnable example to demonstrate it (it's a variation of your example):
package main
import (
"fmt"
"math/rand"
"sync"
)
var (
testMap = make(map[int]int)
testMapLock = &sync.RWMutex{}
testMapSequence int
)
func main() {
go func() {
for {
k := rand.Intn(10000)
WriteTestMap(k, 1)
}
}()
ic := make(chan int)
go func() {
for _ = range ic {
}
}()
for {
if err := IterateMapKeys(ic); err != nil {
fmt.Println(err)
}
}
}
func WriteTestMap(k, v int) {
testMapLock.Lock()
defer testMapLock.Unlock()
testMap[k] = v
testMapSequence++
}
func IterateMapKeys(iteratorChannel chan int) error {
testMapLock.RLock()
defer testMapLock.RUnlock()
mySeq := testMapSequence
for k, _ := range testMap {
testMapLock.RUnlock()
iteratorChannel <- k
testMapLock.RLock()
if mySeq != testMapSequence {
//close(iteratorChannel)
return fmt.Errorf("concurrent modification %d", testMapSequence)
}
}
return nil
}
Example output:
concurrent modification 24
concurrent modification 41
concurrent modification 463
concurrent modification 477
concurrent modification 482
concurrent modification 496
concurrent modification 508
concurrent modification 521
concurrent modification 525
concurrent modification 535
concurrent modification 541
concurrent modification 555
concurrent modification 561
concurrent modification 565
concurrent modification 570
concurrent modification 577
concurrent modification 591
concurrent modification 593
We're encountering concurrent modification quite often!
Do you want to avoid this kind of concurrent modification? The solution is quite simple: don't release the read lock inside the for. Also run your app with the -race option to detect race conditions: go run -race testmap.go
Final thoughts
The language spec clearly allows you to modify the map in the same goroutine while ranging over it, this is what the previous quote relates to ("If map entries that have not yet been reached are removed during iteration.... If map entries are created during iteration..."). Modifying the map in the same goroutine is allowed and is safe, but how it is handled by the iterator logic is not defined.
If the map is modified in another goroutine, if you use proper synchronization, The Go Memory Model guarantees that the goroutine with the for ... range will observe all modifications, and the iterator logic will see it just as if "its own" goroutine would have modified it – which is allowed as stated before.

The unit of concurrent access for a for range loop over a map is the map. Go maps in action.
A map is a dynamic data structure that changes for inserts, updates and deletes. Inside the Map Implementation. For example,
The iteration order over maps is not specified and is not guaranteed
to be the same from one iteration to the next. If map entries that
have not yet been reached are removed during iteration, the
corresponding iteration values will not be produced. If map entries
are created during iteration, that entry may be produced during the
iteration or may be skipped. The choice may vary for each entry
created and from one iteration to the next. If the map is nil, the
number of iterations is 0. For statements, The Go Programming
Language Specification
Reading a map with a for range loop with interleaved inserts, updates and deletes is unlikely to be useful.
Lock the map:
package main
import (
"sync"
)
var racer map[int]int
var race sync.RWMutex
func Reader() {
race.RLock() // Lock map
for k, v := range racer {
_, _ = k, v
}
race.RUnlock()
}
func Write() {
for i := 0; i < 1e6; i++ {
race.Lock()
racer[i/2] = i
race.Unlock()
}
}
func main() {
racer = make(map[int]int)
Write()
go Write()
Reader()
}
Don't lock after the read -- fatal error: concurrent map iteration and map write:
package main
import (
"sync"
)
var racer map[int]int
var race sync.RWMutex
func Reader() {
for k, v := range racer {
race.RLock() // Lock after read
_, _ = k, v
race.RUnlock()
}
}
func Write() {
for i := 0; i < 1e6; i++ {
race.Lock()
racer[i/2] = i
race.Unlock()
}
}
func main() {
racer = make(map[int]int)
Write()
go Write()
Reader()
}
Use the Go Data Race Detector. Read Introducing the Go Race Detector.

Related

Lock slice before reading and modifying it

My experience working with Go is recent and in reviewing some code, I have seen that while it is write-protected, there is a problem with reading the data. Not with the reading itself, but with possible modifications that can occur between the reading and the modification of the slice.
type ConcurrentSlice struct {
sync.RWMutex
items []Item
}
type Item struct {
Index int
Value Info
}
type Info struct {
Name string
Labels map[string]string
Failure bool
}
As mentioned, the writing is protected in this way:
func (cs *ConcurrentSlice) UpdateOrAppend(item ScalingInfo) {
found := false
i := 0
for inList := range cs.Iter() {
if item.Name == inList.Value.Name{
cs.items[i] = item
found = true
}
i++
}
if !found {
cs.Lock()
defer cs.Unlock()
cs.items = append(cs.items, item)
}
}
func (cs *ConcurrentSlice) Iter() <-chan ConcurrentSliceItem {
c := make(chan ConcurrentSliceItem)
f := func() {
cs.Lock()
defer cs.Unlock()
for index, value := range cs.items {
c <- ConcurrentSliceItem{index, value}
}
close(c)
}
go f()
return c
}
But between collecting the content of the slice and modifying it, modifications can occur.It may be that another routine modifies the same slice and when it is time to assign a value, it no longer exists: slice[i] = item
What would be the right way to deal with this?
I have implemented this method:
func GetList() *ConcurrentSlice {
if list == nil {
denylist = NewConcurrentSlice()
return denylist
}
return denylist
}
And I use it like this:
concurrentSlice := GetList()
concurrentSlice.UpdateOrAppend(item)
But I understand that between the get and the modification, even if it is practically immediate, another routine may have modified the slice. What would be the correct way to perform the two operations atomically? That the slice I read is 100% the one I modify. Because if I try to assign an item to a index that no longer exists, it will break the execution.
Thank you in advance!
The way you are doing the blocking is incorrect, because it does not ensure that the items you return have not been removed. In case of an update, the array would still be at least the same length.
A simpler solution that works could be the following:
func (cs *ConcurrentSlice) UpdateOrAppend(item ScalingInfo) {
found := false
i := 0
cs.Lock()
defer cs.Unlock()
for _, it := range cs.items {
if item.Name == it.Name{
cs.items[i] = it
found = true
}
i++
}
if !found {
cs.items = append(cs.items, item)
}
}
Use a sync.Map if the order of the values is not important.
type Items struct {
m sync.Map
}
func (items *Items) Update(item Info) {
items.m.Store(item.Name, item)
}
func (items *Items) Range(f func(Info) bool) {
items.m.Range(func(key, value any) bool {
return f(value.(Info))
})
}
Data structures 101: always pick the best data structure for your use case. If you’re going to be looking up objects by name, that’s EXACTLY what map is for. If you still need to maintain the order of the items, you use a treemap
Concurrency 101: like transactions, your mutex should be atomic, consistent, and isolated. You’re failing isolation here because the data structure read does not fall inside your mutex lock.
Your code should look something like this:
func {
mutex.lock
defer mutex.unlock
check map or treemap for name
if exists update
else add
}
After some tests, I can say that the situation you fear can indeed happen with sync.RWMutex. I think it could happen with sync.Mutex too, but I can't reproduce that. Maybe I'm missing some informations, or maybe the calls are in order because they all are blocked and the order they redeem the right to lock is ordered in some way.
One way to keep your two calls safe without other routines getting in 'conflict' would be to use an other mutex, for every task on that object. You would lock that mutex before your read and write, and release it when you're done. You would also have to use that mutex on any other call that write (or read) to that object. You can find an implementation of what I'm talking about here in the main.go file. In order to reproduce the issue with RWMutex, you can simply comment the startTask and the endTask calls and the issue is visible in the terminal output.
EDIT : my first answer was wrong as I misinterpreted a test result, and fell in the situation described by OP.
tl;dr;
If ConcurrentSlice is to be used from a single goroutine, the locks are unnecessary, because the way algorithm written there is not going to be any concurrent read/writes to slice elements, or the slice.
If ConcurrentSlice is to be used from multiple goroutines, existings locks are not sufficient. This is because UpdateOrAppend may modify slice elements concurrently.
A safe version woule need two versions of Iter:
This can be called by users of ConcurrentSlice, but it cannot be called from `UpdateOrAppend:
func (cs *ConcurrentSlice) Iter() <-chan ConcurrentSliceItem {
c := make(chan ConcurrentSliceItem)
f := func() {
cs.RLock()
defer cs.RUnlock()
for index, value := range cs.items {
c <- ConcurrentSliceItem{index, value}
}
close(c)
}
go f()
return c
}
and this is only to be called from UpdateOrAppend:
func (cs *ConcurrentSlice) internalIter() <-chan ConcurrentSliceItem {
c := make(chan ConcurrentSliceItem)
f := func() {
// No locking
for index, value := range cs.items {
c <- ConcurrentSliceItem{index, value}
}
close(c)
}
go f()
return c
}
And UpdateOrAppend should be synchronized at the top level:
func (cs *ConcurrentSlice) UpdateOrAppend(item ScalingInfo) {
cs.Lock()
defer cs.Unlock()
....
}
Here's the long version:
This is an interesting piece of code. Based on my understanding of the go memory model, the mutex lock in Iter() is only necessary if there is another goroutine working on this code, and even with that, there is a possible race in the code. However, UpdateOrAppend only modifies elements of the slice with lower indexes than what Iter is working on, so that race never manifests itself.
The race can happen as follows:
The for-loop in iter reads element 0 of the slice
The element is sent through the channel. Thus, the slice receive happens after the first step.
The receiving end potentially updates element 0 of the slice. There is no problem up to here.
Then the sending goroutine reads element 1 of the slice. This is when a race can happen. If step 3 updated index 1 of the slice, the read at step 4 is a race. That is: if step 3 reads the update done by step 4, it is a race. You can see this if you start with i:=1 in UpdateOrAppend, and running it with the -race flag.
But UpdateOrAppend always modifies slice elements that are already seen by Iter when i=0, so this code is safe, even without the lock.
If there will be other goroutines accessing and modifying the structure, you need the Mutex, but you need it to protect the complete UpdateOrAppend method, because only one goroutine should be allowed to run that. You need the mutex to protect the potential updates in the first for-loop, and that mutex has to also include the slice append case, because that may actually modify the slice of the underlying object.
If Iter is only called from UpdateOrAppend, then this single mutex should be sufficient. If however Iter can be called from multiple goroutines, then there is another race possibility. If one UpdateOrAppend is running concurrently with multiple Iter instances, then some of those Iter instances will read from the modified slice elements concurrently, causing a race. So, it should be such that multiple Iters can only run if there are no UpdateOrAppend calls. That is a RWMutex.
But Iter can be called from UpdateOrAppend with a lock, so it cannot really call RLock, otherwise it is a deadlock.
Thus, you need two versions of Iter: one that can be called outside UpdateOrAppend, and that issues RLock in the goroutine, and another that can only be called from UpdateOrAppend and does not call RLock.

What happens when reading or writing concurrently without a mutex

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

Difference in behavior between slices and maps

A related questions is here https://stackoverflow.com/a/12965872/6421681.
In go, you can do:
func numsInFactorial(n int) (nums []int) {
// `nums := make([]int)` is not needed
for i := 1; i <= n; i++ {
nums = append(nums, i)
}
return
}
However,the following doesn't work:
func mapWithOneKeyAndValue(k int, v int) (m map[int]int) {
m[k] = v
return
}
An error is thrown:
panic: assignment to entry in nil map
Instead, you must:
func mapWithOneKeyAndValue(k int, v int) map[int]int {
m := make(map[int]int)
m[k] = v
return
}
I can't find the documentation for this behavior.
I have read through all of effective go, and there's no mention of it there either.
I know that named return values are defined (i.e. memory is allocated; close to what new does) but not initialized (so make behavior isn't replicated).
After some experimenting, I believe this behavior can be reduced into understanding the behavior of the following code:
func main() {
var s []int // len and cap are both 0
var m map[int]int
fmt.Println(s) // works... prints an empty slice
fmt.Println(m) // works... prints an empty map
s = append(s, 10) // returns a new slice, so underlying array gets allocated
fmt.Println(s) // works... prints [10]
m[10] = 10 // program crashes, with "assignment to entry in nil map"
fmt.Println(m)
}
The issue seems that append likely calls make and allocates a new slice detecting that the capacity of s is 0. However, map never gets an explicit initialization.
The reason for this SO question is two-pronged. First, I would like to document the behavior on SO. Second, why would the language allow non-initializing definitions of slice and map? With my experience with go so far, it seems to be a pragmatic language (i.e. unused variables lead to compilation failure, gofmt forces proper formatting), so it would make sense for it to prevent the code from compiling.
Try to assign in nil slice by index - you will get "panic: runtime error: index out of range" (example: https://play.golang.org/p/-XHh1jNyn5g)
The only reason why append function works with nil, is that append function can do reallocation for the given slice.
For example, if you trying to to append 6th element to slice of 5 elements with current capacity 5, it will create the new array with new capacity, copy all the info from old one, and swap the data array pointers in the given slice. In my understanding, it is just golang implementation of dynamic arrays.
So, the nil slice is just a special case of slice with not enough capacity, so it would be reallocated on any append operation.
More details on https://blog.golang.org/go-slices-usage-and-internals
From https://blog.golang.org/go-maps-in-action
A nil map behaves like an empty map when reading, but attempts to write to a nil map will cause a runtime panic; don't do that. To initialize a map, use the built in make function
It seems like a nil map is considered a valid empty map and that's the reason they don't allocate memory for it automatically.

How to understand this behavior of goroutine?

package main
import (
"fmt"
"time"
)
type field struct {
name string
}
func (p *field) print() {
fmt.Println(p.name)
}
func main() {
data := []field{ {"one"},{"two"},{"three"} }
for _,v := range data {
go v.print()
}
<-time.After(1 * time.Second)
}
why does this code print 3 "three" instead of "one" "two" "three" in any order?
There is a data race.
The code implicitly takes address of variable v when evaluating arguments to the goroutine function. Note that the call v.print() is shorthand for the call (&v).print().
The loop changes the value of variable v.
When goroutines execute, it so happens that v has the last value of the loop. That's not guaranteed. It could execute as you expected.
It's helpful and easy to run programs with the race detector. This data race is detected and reported by the detector.
One fix is to create another variable scoped to the inside of the loop:
for _, v := range data {
v := v // short variable declaration of new variable `v`.
go v.print()
}
With this change, the address of the inner variable v is taken when evaluating the arguments to the goroutine. There is a unique inner variable v for each iteration of the loop.
Yet another way to fix the problem is use a slice of pointers:
data := []*field{ {"one"},{"two"},{"three"} } // note '*'
for _, v := range data {
go v.print()
}
With this change, the individual pointers in the slice are passed to the goroutine, not the address of the range variable v.
Another fix is to use the address of the slice element:
data := []field{ {"one"},{"two"},{"three"} } // note '*'
for i:= range data {
v := &data[i]
go v.print()
}
Because pointer values are typically used with types having a pointer receiver, this subtle issue does not come up often in practice. Because field has a pointer receiver, it would be typical to use []*field instead of []field for the type of data in the question.
If the goroutine function is in an anonymous function, then a common approach for avoiding the issue is to pass the range variables as an argument to the anonymous function:
for _, v := range data {
go func(v field) {
v.print() // take address of argument v, not range variable v.
}(v)
}
Because the code in the question does not already use an anonymous function for the goroutine, the first approach used in this answer is simpler.
As stated above there’s a race condition it’s result depends on delays on different processes and not well defined and predictable.
For example if you add time.Sleep(1*time.Seconds) you likely to get a correct result. Because usually goroutine prints faster than 1second and will have correct variable v but it’s a very bad way.
Golang has a special race detector tool which helps to find such situations. I recommend read about it while reading testing. Definitely it’s worth it.
There’s another way - explicitly pass variable value at goroutine start:
for _, v := range data {
go func(iv field) {
iv.print()
}(v)
}
Here v will be copied to iv (“internal v”) on every iteration and each goroutine will use correct value.

How to use channels to safely synchronise data in Go

Below is an example of how to use mutex lock in order to safely access data. How would I go about doing the same with the use of CSP (communication sequential processes) instead of using mutex lock’s and unlock’s?
type Stack struct {
top *Element
size int
sync.Mutex
}
func (ss *Stack) Len() int {
ss.Lock()
size := ss.size
ss.Unlock()
return size
}
func (ss *Stack) Push(value interface{}) {
ss.Lock()
ss.top = &Element{value, ss.top}
ss.size++
ss.Unlock()
}
func (ss *SafeStack) Pop() (value interface{}) {
ss.Lock()
size := ss.size
ss.Unlock()
if size > 0 {
ss.Lock()
value, ss.top = ss.top.value, ss.top.next
ss.size--
ss.Unlock()
return
}
return nil
}
If you actually were to look at how Go implements channels, you'd essentially see a mutex around an array with some additional thread handling to block execution until the value is passed through. A channel's job is to move data from one spot in memory to another with ease. Therefore where you have locks and unlocks, you'd have things like this example:
func example() {
resChan := make(int chan)
go func(){
resChan <- 1
}()
go func(){
res := <-resChan
}
}
So in the example, the first goroutine is blocked after sending the value until the second goroutine reads from the channel.
To do this in Go with mutexes, one would use sync.WaitGroup which will add one to the group on setting the value, then release it from the group and the second goroutine will lock and then unlock the value.
The oddities in your example are 1 no goroutines, so it's all happening in a single main goroutine and the locks are being used more traditionally (as in c thread like) so channels won't really accomplish anything. The example you have would be considered an anti-pattern, like the golang proverb says "Don't communicate by sharing memory, share memory by communicating."

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