what can create huge overhead of goroutines? - go

for an assignment we are using go and one of the things we are going to do is to parse a uniprotdatabasefile line-by-line to collect uniprot-records.
I prefer not to share too much code, but I have a working code snippet that does parse such a file (2.5 GB) correctly in 48 s (measured using the time go-package). It parses the file iteratively and add lines to a record until a record end signal is reached (a full record), and metadata on the record is created. Then the record string is nulled, and a new record is collected line-by-line. Then I thought that I would try to use go-routines.
I have got some tips before from stackoverflow, and then to the original code I simple added a function to handle everything concerning the metadata-creation.
So, the code is doing
create an empty record,
iterate the file and add lines to the record,
if a record stop signal is found (now we have a full record) - give it to a go routine to create the metadata
null the record string and continue from 2).
I also added a sync.WaitGroup() to make sure that I waited (in the end) for each routine to finish. I thought that this would actually lower the time spent on parsing the databasefile as it continued to parse while the goroutines would act on each record. However, the code seems to run for more than 20 minutes indicating that something is wrong or the overhead went crazy. Any suggestions?
package main
import (
"bufio"
"crypto/sha1"
"fmt"
"io"
"log"
"os"
"strings"
"sync"
"time"
)
type producer struct {
parser uniprot
}
type unit struct {
tag string
}
type uniprot struct {
filenames []string
recordUnits chan unit
recordStrings map[string]string
}
func main() {
p := producer{parser: uniprot{}}
p.parser.recordUnits = make(chan unit, 1000000)
p.parser.recordStrings = make(map[string]string)
p.parser.collectRecords(os.Args[1])
}
func (u *uniprot) collectRecords(name string) {
fmt.Println("file to open ", name)
t0 := time.Now()
wg := new(sync.WaitGroup)
record := []string{}
file, err := os.Open(name)
errorCheck(err)
scanner := bufio.NewScanner(file)
for scanner.Scan() { //Scan the file
retText := scanner.Text()
if strings.HasPrefix(retText, "//") {
wg.Add(1)
go u.handleRecord(record, wg)
record = []string{}
} else {
record = append(record, retText)
}
}
file.Close()
wg.Wait()
t1 := time.Now()
fmt.Println(t1.Sub(t0))
}
func (u *uniprot) handleRecord(record []string, wg *sync.WaitGroup) {
defer wg.Done()
recString := strings.Join(record, "\n")
t := hashfunc(recString)
u.recordUnits <- unit{tag: t}
u.recordStrings[t] = recString
}
func hashfunc(record string) (hashtag string) {
hash := sha1.New()
io.WriteString(hash, record)
hashtag = string(hash.Sum(nil))
return
}
func errorCheck(err error) {
if err != nil {
log.Fatal(err)
}
}

First of all: your code is not thread-safe. Mainly because you're accessing a hashmap
concurrently. These are not safe for concurrency in go and need to be locked. Faulty line in your code:
u.recordStrings[t] = recString
As this will blow up when you're running go with GOMAXPROCS > 1, I'm assuming that you're not doing that. Make sure you're running your application with GOMAXPROCS=2 or higher to achieve parallelism.
The default value is 1, therefore your code runs on one single OS thread which, of course, can't be scheduled on two CPU or CPU cores simultaneously. Example:
$ GOMAXPROCS=2 go run udb.go uniprot_sprot_viruses.dat
At last: pull the values from the channel or otherwise your program will not terminate.
You're creating a deadlock if the number of goroutines exceeds your limit. I tested with a
76MiB file of data, you said your file was about 2.5GB. I have 16347 entries. Assuming linear growth,
your file will exceed 1e6 and therefore there are not enough slots in the channel and your program
will deadlock, giving no result while accumulating goroutines which don't run to fail at the end
(miserably).
So the solution should be to add a go routine which pulls the values from the channel and does
something with them.
As a side note: If you're worried about performance, do not use strings as they're always copied. Use []byte instead.

Related

how to batch dealing with files using Goroutine?

Assuming I have a bunch of files to deal with(say 1000 or more), first they should be processed by function A(), function A() will generate a file, then this file will be processed by B().
If we do it one by one, that's too slow, so I'm thinking process 5 files at a time using goroutine(we can not process too much at a time cause the CPU cannot bear).
I'm a newbie in golang, I'm not sure if my thought is correct, I think the function A() is a producer and the function B() is a consumer, function B() will deal with the file that produced by function A(), and I wrote some code below, forgive me, I really don't know how to write the code, can anyone give me a help? Thank you in advance!
package main
import "fmt"
var Box = make(chan string, 1024)
func A(file string) {
fmt.Println(file, "is processing in func A()...")
fileGenByA := "/path/to/fileGenByA1"
Box <- fileGenByA
}
func B(file string) {
fmt.Println(file, "is processing in func B()...")
}
func main() {
// assuming that this is the file list read from a directory
fileList := []string{
"/path/to/file1",
"/path/to/file2",
"/path/to/file3",
}
// it seems I can't do this, because fileList may have 1000 or more file
for _, v := range fileList {
go A(v)
}
// can I do this?
for file := range Box {
go B(file)
}
}
Update:
sorry, maybe I haven’t made myself clear, actually the file generated by function A() is stored in the hard disk(generated by a command line tool, I just simple execute it using exec.Command()), not in a variable(the memory), so it doesn't have to be passed to function B() immediately.
I think there are 2 approach:
approach1
approach2
Actually I prefer approach2, as you can see, the first B() doesn't have to process the file1GenByA, it's the same for B() to process any file in the box, because file1GenByA may generated after file2GenByA(maybe the file is larger so it takes more time).
You could spawn 5 goroutines that read from a work channel. That way you have at all times 5 goroutines running and don't need to batch them so that you have to wait until 5 are finished to start the next 5.
func main() {
stack := []string{"a", "b", "c", "d", "e", "f", "g", "h"}
work := make(chan string)
results := make(chan string)
// create worker 5 goroutines
wg := sync.WaitGroup{}
for i := 0; i < 5; i++ {
wg.Add(1)
go func() {
defer wg.Done()
for s := range work {
results <- B(A(s))
}
}()
}
// send the work to the workers
// this happens in a goroutine in order
// to not block the main function, once
// all 5 workers are busy
go func() {
for _, s := range stack {
// could read the file from disk
// here and pass a pointer to the file
work <- s
}
// close the work channel after
// all the work has been send
close(work)
// wait for the workers to finish
// then close the results channel
wg.Wait()
close(results)
}()
// collect the results
// the iteration stops if the results
// channel is closed and the last value
// has been received
for result := range results {
// could write the file to disk
fmt.Println(result)
}
}
https://play.golang.com/p/K-KVX4LEEoK
you're halfway there. There's a few things you need to fix:
your program deadlocks because nothing closes Box, so the main function can never get done rangeing over it.
You aren't waiting for your goroutines to finish, and there than 5 goroutines. (The solutions to these are too intertwined to describe them separately)
1. Deadlock
fatal error: all goroutines are asleep - deadlock!
goroutine 1 [chan receive]:
main.main()
When you range over a channel, you read each value from the channel until it is both closed and empty. Since you never close the channel, the range over that channel can never complete, and the program can never finish.
This is a fairly easy problem to solve in your case: we just need to close the channel when we know there will be no more writes to the channel.
for _, v := range fileList {
go A(v)
}
close(Box)
Keep in mind that closeing a channel doesn't stop it from being read, only written. Now consumers can distinguish between an empty channel that may receive more data in the future, and an empty channel that will never receive more data.
Once you add the close(Box), the program doesn't deadlock anymore, but it still doesn't work.
2. Too Many Goroutines and not waiting for them to complete
To run a certain maximum number of concurrent executions, instead of creating a goroutine for each input, create the goroutines in a "worker pool":
Create a channel to pass the workers their work
Create a channel for the goroutines to return their results, if any
Start the number of goroutines you want
Start at least one additional goroutine to either dispatch work or collect the result, so you don't have to try doing both from the main goroutine
use a sync.WaitGroup to wait for all data to be processed
close the channels to signal to the workers and the results collector that their channels are done being filled.
Before we get into the implementation, let's talk aobut how A and B interact.
first they should be processed by function A(), function A() will generate a file, then this file will be processed by B().
A() and B() must, then, execute serially. They can still pass their data through a channel, but since their execution must be serial, it does nothing for you. Simpler is to run them sequentially in the workers. For that, we'll need to change A() to either call B, or to return the path for B and the worker can call. I choose the latter.
func A(file string) string {
fmt.Println(file, "is processing in func A()...")
fileGenByA := "/path/to/fileGenByA1"
return fileGenByA
}
Before we write our worker function, we also must consider the result of B. Currently, B returns nothing. In the real world, unless B() cannot fail, you would at least want to either return the error, or at least panic. I'll skip over collecting results for now.
Now we can write our worker function.
func worker(wg *sync.WaitGroup, incoming <-chan string) {
defer wg.Done()
for file := range incoming {
B(A(file))
}
}
Now all we have to do is start 5 such workers, write the incoming files to the channel, close it, and wg.Wait() for the workers to complete.
incoming_work := make(chan string)
var wg sync.WaitGroup
for i := 0; i < 5; i++ {
wg.Add(1)
go worker(&wg, incoming_work)
}
for _, v := range fileList {
incoming_work <- v
}
close(incoming_work)
wg.Wait()
Full example at https://go.dev/play/p/A1H4ArD2LD8
Returning Results.
It's all well and good to be able to kick off goroutines and wait for them to complete. But what if you need results back from your goroutines? In all but the simplest of cases, you would at least want to know if files failed to process so you could investigate the errors.
We have only 5 workers, but we have many files, so we have many results. Each worker will have to return several results. So, another channel. It's usually worth defining a struct for your return:
type result struct {
file string
err error
}
This tells us not just whether there was an error but also clearly defines which file from which the error resulted.
How will we test an error case in our current code? In your example, B always gets the same value from A. If we add A's incoming file name to the path it passes to B, we can mock an error based on a substring. My mocked error will be that file3 fails.
func A(file string) string {
fmt.Println(file, "is processing in func A()...")
fileGenByA := "/path/to/fileGenByA1/" + file
return fileGenByA
}
func B(file string) (r result) {
r.file = file
fmt.Println(file, "is processing in func B()...")
if strings.Contains(file, "file3") {
r.err = fmt.Errorf("Test error")
}
return
}
Our workers will be sending results, but we need to collect them somewhere. main() is busy dispatching work to the workers, blocking on its write to incoming_work when the workers are all busy. So the simplest place to collect the results is another goroutine. Our results collector goroutine has to read from a results channel, print out errors for debugging, and the return the total number of failures so our program can return a final exit status indicating overall success or failure.
failures_chan := make(chan int)
go func() {
var failures int
for result := range results {
if result.err != nil {
failures++
fmt.Printf("File %s failed: %s", result.file, result.err.Error())
}
}
failures_chan <- failures
}()
Now we have another channel to close, and it's important we close it after all workers are done. So we close(results) after we wg.Wait() for the workers.
close(incoming_work)
wg.Wait()
close(results)
if failures := <-failures_chan; failures > 0 {
os.Exit(1)
}
Putting all that together, we end up with this code:
package main
import (
"fmt"
"os"
"strings"
"sync"
)
func A(file string) string {
fmt.Println(file, "is processing in func A()...")
fileGenByA := "/path/to/fileGenByA1/" + file
return fileGenByA
}
func B(file string) (r result) {
r.file = file
fmt.Println(file, "is processing in func B()...")
if strings.Contains(file, "file3") {
r.err = fmt.Errorf("Test error")
}
return
}
func worker(wg *sync.WaitGroup, incoming <-chan string, results chan<- result) {
defer wg.Done()
for file := range incoming {
results <- B(A(file))
}
}
type result struct {
file string
err error
}
func main() {
// assuming that this is the file list read from a directory
fileList := []string{
"/path/to/file1",
"/path/to/file2",
"/path/to/file3",
}
incoming_work := make(chan string)
results := make(chan result)
var wg sync.WaitGroup
for i := 0; i < 5; i++ {
wg.Add(1)
go worker(&wg, incoming_work, results)
}
failures_chan := make(chan int)
go func() {
var failures int
for result := range results {
if result.err != nil {
failures++
fmt.Printf("File %s failed: %s", result.file, result.err.Error())
}
}
failures_chan <- failures
}()
for _, v := range fileList {
incoming_work <- v
}
close(incoming_work)
wg.Wait()
close(results)
if failures := <-failures_chan; failures > 0 {
os.Exit(1)
}
}
And when we run it, we get:
/path/to/file1 is processing in func A()...
/path/to/fileGenByA1//path/to/file1 is processing in func B()...
/path/to/file2 is processing in func A()...
/path/to/fileGenByA1//path/to/file2 is processing in func B()...
/path/to/file3 is processing in func A()...
/path/to/fileGenByA1//path/to/file3 is processing in func B()...
File /path/to/fileGenByA1//path/to/file3 failed: Test error
Program exited.
A final thought: buffered channels.
There is nothing wrong with buffered channels. Especially if you know the overall size of incoming work and results, buffered channels can obviate the results collector goroutine because you can allocate a buffered channel big enough to hold all results. However, I think it's more straightforward to understand this pattern if the channels are unbuffered. The key takeaway is that you don't need to know the number of incoming or outgoing results, which could indeed be different numbers or based on something that can't be predetermined.

Any concurrency issues when multiple goroutines access different fields of the same struct

Are there are any concurrency issues if we access mutually exclusive fields of a struct inside different go co-routines?
I remember reading somewhere that if two parallel threads access same object they might get run on different cores of the cpu both having different cpu level caches with different copies of the object in question. (Not related to Go)
Will the below code be sufficient to achieve the functionality correctly or does additional synchronization mechanism needs to be used?
package main
import (
"fmt"
"sync"
)
type structure struct {
x string
y string
}
func main() {
val := structure{}
wg := new(sync.WaitGroup)
wg.Add(2)
go func1(&val, wg)
go func2(&val, wg)
wg.Wait()
fmt.Println(val)
}
func func1(val *structure, wg *sync.WaitGroup) {
val.x = "Test 1"
wg.Done()
}
func func2(val *structure, wg *sync.WaitGroup) {
val.y = "Test 2"
wg.Done()
}
Edit: - for people who ask why not channels unfortunately this is not the actual code I am working on. Both the func has calls to different api and get the data in a struct, those struct has a pragma.DoNotCopy in them ask protobuf auto generator why they thought it was a good idea. So those data can't be sent over the channel, or else i have to create another struct to send the data over or ask the linter to stop complaining. Or i can send a pointer to the object but feel that is also sharing the memory.
You must synchronize when at least one of accesses to shared resources is a write.
Your code is doing write access, yes, but different struct fields have different memory locations. So you are not accessing shared variables.
If you run your program with the race detector, eg. go run -race main.go it will not print a warning.
Now add fmt.Println(val.y) in func1 and run again, it will print:
WARNING: DATA RACE
Write at 0x00c0000c0010 by goroutine 8:
... rest of race warning
The preferred way in Go would be to communicate memory as opposed to share the memory.
In practice that would mean you should use the Go channels as I show in this blogpost.
https://marcofranssen.nl/concurrency-in-go
If you really want to stick with sharing memory you will have to use a Mutex.
https://tour.golang.org/concurrency/9
However that would cause context switching and Go routines synchronization that slows down your program.
Example using channels
package main
import (
"fmt"
"time"
)
type structure struct {
x string
y string
}
func main() {
val := structure{}
c := make(chan structure)
go func1(c)
go func2(c)
func(c chan structure) {
for {
select {
case v, ok := <-c:
if !ok {
return
}
if v.x != "" {
fmt.Printf("Received %v\n", v)
val.x = v.x
}
if v.y != "" {
fmt.Printf("Received %v\n", v)
val.y = v.y
}
if val.x != "" && val.y != "" {
close(c)
}
}
}
}(c)
fmt.Printf("%v\n", val)
}
func func1(c chan<- structure) {
time.Sleep(1 * time.Second)
c <- structure{x: "Test 1"}
}
func func2(c chan<- structure) {
c <- structure{y: "Test 2"}
}

Multiple Go routines reading from the same channel

Hi I'm having a problem with a control channel (of sorts).
The essence of my program:
I do not know how many go routines I will be running at runtime
I will need to restart these go routines at set times, however, they could also potentially error out (and then restarted), so their timing will not be predictable.
These go routines will be putting messages onto a single channel.
So What I've done is created a simple random message generator to put messages onto a channel.
When the timer is up (random duration for testing) I put a message onto a control channel which is a struct payload, so I know there was a close signal and which go routine it was; in reality I'd then do some other stuff I'd need to do before starting the go routines again.
My problem is:
I receive the control message within my reflect.Select loop
I do not (or unable to) receive it in my randmsgs() loop
Therefore I can not stop my randmsgs() go routine.
I believe I'm right in understanding that multiple go routines can read from a single channel, therefore I think I'm misunderstanding how reflect.SelectCases fit into all of this.
My code:
package main
import (
"fmt"
"math/rand"
"reflect"
"time"
)
type testing struct {
control bool
market string
}
func main() {
rand.Seed(time.Now().UnixNano())
// explicitly define chanids for tests.
var chanids []string = []string{"GR I", "GR II", "GR III", "GR IV"}
stream := make(chan string)
control := make([]chan testing, len(chanids))
reflectCases := make([]reflect.SelectCase, len(chanids)+1)
// MAKE REFLECT SELECTS FOR 4 CONTROL CHANS AND 1 DATA CHANNEL
for i := range chanids {
control[i] = make(chan testing)
reflectCases[i] = reflect.SelectCase{Dir: reflect.SelectRecv, Chan: reflect.ValueOf(control[i])}
}
reflectCases[4] = reflect.SelectCase{Dir: reflect.SelectRecv, Chan: reflect.ValueOf(stream)}
// START GO ROUTINES
for i, val := range chanids {
runningFunc(control[i], val, stream, 1+rand.Intn(30-1))
}
// READ DATA
for {
o, recieved, ok := reflect.Select(reflectCases)
if !ok {
fmt.Println("You really buggered this one up...")
}
ty, err := recieved.Interface().(testing)
if err == true {
fmt.Printf("Read from: %v, and recieved close signal from: %s\n", o, ty.market)
// close control & stream here.
} else {
ty := recieved.Interface().(string)
fmt.Printf("Read from: %v, and recieved value from: %s\n", o, ty)
}
}
}
// THE GO ROUTINES - TIMER AND RANDMSGS
func runningFunc(q chan testing, chanid string, stream chan string, dur int) {
go timer(q, dur, chanid)
go randmsgs(q, chanid, stream)
}
func timer(q chan testing, t int, message string) {
for t > 0 {
time.Sleep(time.Second)
t--
}
q <- testing{true, message}
}
func randmsgs(q chan testing, chanid string, stream chan string) {
for {
select {
case <-q:
fmt.Println("Just sitting by the mailbox. :(")
return
default:
secondsToWait := 1 + rand.Intn(5-1)
time.Sleep(time.Second * time.Duration(secondsToWait))
stream <- fmt.Sprintf("%s: %d", chanid, secondsToWait)
}
}
}
I apologise for the wall of text, but I'm all out of ideas :(!
K/Regards,
C.
Your channels q in the second half are the same as control[0...3] in the first.
Your reflect.Select that you are running also reads from all of these channels, with no delay.
The problem I think comes down to that your reflect.Select is simply running too fast and "stealing" all the channel output right away. This is why randmsgs is never able to read the messages.
You'll notice that if you remove the default case from randmsgs, the function is able to (potentially) read some of the messages from q.
select {
case <-q:
fmt.Println("Just sitting by the mailbox. :(")
return
}
This is because now that it is running without delay, it is always waiting for a message on q and thus has the chance to beat the reflect.Select in the race.
If you read from the same channel in multiple goroutines, then the data passed will simply go to whatever goroutine reads it first.
This program appears to just be an experiment / learning experience, but I'll offer some criticism that may help.
Again, generally you don't have multiple goroutines reading from the same channel if both goroutines are doing different tasks. You're creating a mostly non-deterministic race as to which goroutine fetches the data first.
Second, this is a common beginner's anti-pattern with select that you should avoid:
for {
select {
case v := <-myChan:
doSomething(v)
default:
// Oh no, there wasn't anything! Guess we have to wait and try again.
time.Sleep(time.Second)
}
This code is redundant because select already behaves in such a way that if no case is initially ready, it will wait until any case is ready and then proceed with that one. This default: sleep is effectively making your select loop slower and yet spending less time actually waiting on the channel (because 99.999...% of the time is spent on time.Sleep).

Can't get map of channels to work

This might be a rookies mistake. I have a slice with a string value and a map of channels. For each string in the slice, a channel is created and a map entry is created for it, with the string as key.
I watch the channels and pass a value to one of them, which is never found.
package main
import (
"fmt"
"time"
)
type TestStruct struct {
Test string
}
var channelsMap map[string](chan *TestStruct)
func main() {
stringsSlice := []string{"value1"}
channelsMap := make(map[string](chan *TestStruct))
for _, value := range stringsSlice {
channelsMap[value] = make(chan *TestStruct, 1)
go watchChannel(value)
}
<-time.After(3 * time.Second)
testStruct := new(TestStruct)
testStruct.Test = "Hello!"
channelsMap["value1"] <- testStruct
<-time.After(3 * time.Second)
fmt.Println("Program ended")
}
func watchChannel(channelMapKey string) {
fmt.Println("Watching channel: " + channelMapKey)
for channelValue := range channelsMap[channelMapKey] {
fmt.Printf("Channel '%s' used. Passed value: '%s'\n", channelMapKey, channelValue.Test)
}
}
Playground link: https://play.golang.org/p/IbucTqMjdGO
Output:
Watching channel: value1
Program ended
How do I execute something when the message is fed into the channel?
There are many problems with your approach.
The first one is that you're redeclaring ("shadowing") the global
variable channelsMap in your main function.
(Had you completed at least some
most basic intro to Go, you should have had no such problem.)
This means that your watchChannel (actually, all the goroutines which execute that function) read the global channelsMap while your main function writes to its local channelsMap.
What happens next, is as follows:
The range statement
in the watchChannel has a simple
map lookup expression as its source—channelsMap[channelMapKey].
In Go, this form of map lookup
never fails, but if the map has no such key (or if the map is not initialized, that is, it's nil), the so-called
"zero value"
of the appropriate type is returned.
Since the global channelsMap is always empty, any call to watchChannel performs a map lookup which always returns
the zero value of type chan *TestStruct.
The zero value for any channel is nil.
The range statement executed over a nil channel
produces zero iterations.
In other words, the for loop in watchChannel always executes
zero times.
The more complex problem, still, is not shadowing of the global variable but rather the complete absense of synchronization between the goroutines. You're using "sleeping" as a sort of band-aid in an attempt to perform implicit synchronization between goroutines
but while this does appear to be okay judged by so-called
"common sense", it's not going to work in practice for two
reasons:
Sleeping is always a naïve approach to synchronization as it solely depens of the fact all the goroutines will run relatively freely and uncontended. This is far from being true in many (if not most) production settings and hence is always the reason for subtle bugs. Don't ever do that again, please.
Nothing in the Go memory model
says that waiting against wall-clock timing is considered by the runtime as establishing the order on how execution of different goroutines relate to each other.
There exist various ways to synchronize execution between goroutines. Basically they amount to sends and receives over channels and using the types provided by the sync package.
In your particular case the simplest approach is probably using the sync.WaitGroup type.
Here is what we would
have after fixing the problems explained above:
- Initialize the map variable right at the point of its
definition and not mess with it in main.
- Use sync.WaitGroup to make main properly wait for all
the goroutines it spawned to singal they're done:
package main
import (
"fmt"
"sync"
)
type TestStruct struct {
Test string
}
var channelsMap = make(map[string](chan *TestStruct))
func main() {
stringsSlice := []string{"value1"}
var wg sync.WaitGroup
wg.Add(len(stringsSlice))
for _, value := range stringsSlice {
channelsMap[value] = make(chan *TestStruct, 1)
go watchChannel(value, &wg)
}
testStruct := new(TestStruct)
testStruct.Test = "Hello!"
channelsMap["value1"] <- testStruct
wg.Wait()
fmt.Println("Program ended")
}
func watchChannel(channelMapKey string, wg *sync.WaitGroup) {
defer wg.Done()
fmt.Println("Watching channel: " + channelMapKey)
for channelValue := range channelsMap[channelMapKey] {
fmt.Printf("Channel '%s' used. Passed value: '%s'\n", channelMapKey, channelValue.Test)
}
}
The next two problems with your code become apparent once we will
have fixed the former two—after you make the "watcher" goroutines
use the same map variable as the goroutine running main, and
make the latter properly wait for the watchers:
There is a data race
over the map variable between the
code which updates the map after the for loop spawning the
watcher goroutines ended and the code which accesses this
variable in all the watcher goroutines.
There is a deadlock
between the watcher goroutines and the main goroutine which waits for them to complete.
The reason for the deadlock is that the watcher goroutines
never receive any signal they have to quit processing and
hence are stuck forever trying to read from their respective
channels.
The ways to fix these two new problems are simple but they
might actually "break" your original idea of structuring
your code.
First, I'd remove the data race by simply making the watchers
not access the map variable. As you can see, each call to
watchChannel receives a single value to use as the key to
read a value off the shared map, and hence each watcher always
reads a single value exactly once during its run time.
The code would become much clearer if we remove this extra
map access altogether and instead pass the appropriate channel
value directly to each watcher.
A nice byproduct of this is that we do not need a global
map variable anymore.
Here's what we'll get:
package main
import (
"fmt"
"sync"
)
type TestStruct struct {
Test string
}
func main() {
stringsSlice := []string{"value1"}
channelsMap := make(map[string](chan *TestStruct))
var wg sync.WaitGroup
wg.Add(len(stringsSlice))
for _, value := range stringsSlice {
channelsMap[value] = make(chan *TestStruct, 1)
go watchChannel(value, channelsMap[value], &wg)
}
testStruct := new(TestStruct)
testStruct.Test = "Hello!"
channelsMap["value1"] <- testStruct
wg.Wait()
fmt.Println("Program ended")
}
func watchChannel(channelMapKey string, ch <-chan *TestStruct, wg *sync.WaitGroup) {
defer wg.Done()
fmt.Println("Watching channel: " + channelMapKey)
for channelValue := range ch {
fmt.Printf("Channel '%s' used. Passed value: '%s'\n", channelMapKey, channelValue.Test)
}
}
Okay, we still have the deadlock.
There are multiple approaches to solving this but they depend
on the actual circumstances, and with this toy example, any
attempt to iterate over at least a subset of them would just
muddle the waters.
Instead, let's employ the simplest one for this case: closing
a channel makes any pending receive operation on it immediately
unblock and produce the zero value for the channel's type.
For a channel being iterated over using the range statement
it simply means the stamement terminates without producing any
value from the channel.
In other words, let's just close all the channels to unblock
the range statements being run by the watcher goroutines
and then wait for these goroutines to report their completion via the wait group.
To not make the answer overly long, I also added programmatic initialization of the string slice to make the example more interesting by having multiple watchers—not just a single one—actually do useful work:
package main
import (
"fmt"
"sync"
)
type TestStruct struct {
Test string
}
func main() {
var stringsSlice []string
channelsMap := make(map[string](chan *TestStruct))
for i := 1; i <= 10; i++ {
stringsSlice = append(stringsSlice, fmt.Sprintf("value%d", i))
}
var wg sync.WaitGroup
wg.Add(len(stringsSlice))
for _, value := range stringsSlice {
channelsMap[value] = make(chan *TestStruct, 1)
go watchChannel(value, channelsMap[value], &wg)
}
for _, value := range stringsSlice {
testStruct := new(TestStruct)
testStruct.Test = fmt.Sprint("Hello! ", value)
channelsMap[value] <- testStruct
}
for _, ch := range channelsMap {
close(ch)
}
wg.Wait()
fmt.Println("Program ended")
}
func watchChannel(channelMapKey string, ch <-chan *TestStruct, wg *sync.WaitGroup) {
defer wg.Done()
fmt.Println("Watching channel: " + channelMapKey)
for channelValue := range ch {
fmt.Printf("Channel '%s' used. Passed value: '%s'\n", channelMapKey, channelValue.Test)
}
}
Playground link.
As you can see, there are things you should actually learn
about in way more greater detail before embarking on working with
concurrency.
I'd recommend to proceed in the following order:
The Go tour would make you accustomed with the bare bones of concurrency.
The Go Programming Language has two chapters dedicated to providing the readers with a gentle introduction with tackling concurrency both using channels and the types from the sync package.
Concurrency In Go goes on with presenting more hard-core details of how one deals with concurrency in Go, including advanced topics approaching the real-world problems concurrent programs face in production—such as ways to rate-limit incoming requests.
The shadowing in main of channelsMap mentioned above was a critical bug, but aside from that, the program was playing "Russian roulette" with the calls to time.After so that main wouldn't finish before the watcher goroutines did. This is unstable and unreliable, so I recommend the following approach using a channel to signal when all watcher goroutines are done:
package main
import (
"fmt"
)
type TestStruct struct {
Test string
}
var channelsMap map[string](chan *TestStruct)
func main() {
stringsSlice := []string{"value1", "value2", "value3"}
structsSlice := []TestStruct{
{"Hello1"},
{"Hello2"},
{"Hello3"},
}
channelsMap = make(map[string](chan *TestStruct))
// Signal channel to wait for watcher goroutines.
done := make(chan struct{})
for _, s := range stringsSlice {
channelsMap[s] = make(chan *TestStruct)
// Give watcher goroutines the signal channel.
go watchChannel(s, done)
}
for _, ts := range structsSlice {
for _, s := range stringsSlice {
channelsMap[s] <- &ts
}
}
// Close the channels so watcher goroutines can finish.
for _, s := range stringsSlice {
close(channelsMap[s])
}
// Wait for all watcher goroutines to finish.
for range stringsSlice {
<-done
}
// Now we're really done!
fmt.Println("Program ended")
}
func watchChannel(channelMapKey string, done chan<- struct{}) {
fmt.Println("Watching channel: " + channelMapKey)
for channelValue := range channelsMap[channelMapKey] {
fmt.Printf("Channel '%s' used. Passed value: '%s'\n", channelMapKey, channelValue.Test)
}
done <- struct{}{}
}
(Go Playground link: https://play.golang.org/p/eP57Ru44-NW)
Of importance is the use of the done channel to let watcher goroutines signal that they're finished to main. Another critical part is the closing of the channels once you're done with them. If you don't close them, the range loops in the watcher goroutines will never end, waiting forever. Once you close the channel, the range loop exits and the watcher goruoutine can send on the done channel, signaling that it has finished working.
Finally, back in main, you have to receive on the done channel once for each watcher goroutine you created. Since the number of watcher goroutines is equal to the number of items in stringsSlice, you simply range over stringsSlice to receive the correct amount of times from the done channel. Once that's finished, the main function can exit with a guarantee that all watchers have finished.

Golang order output of go routines

I have 16 go routines which return output , which is typically a struct.
struct output{
index int,
description string,
}
Now all these 16 go routines run in parallel, and the total expected output structs from all the go routines is expected to be a million. I have used the basic sorting of go lang it is very expensive to do that, could some one help me with the approach to take to sort the output based on the index and I need to write the "description" field on to a file based on the order of index.
For instance ,
if a go routine gives output as {2, "Hello"},{9,"Hey"},{4,"Hola"}, my output file should contain
Hello
Hola
Hey
All these go routines run in parallel and I have no control on the order of execution , hence I am passing the index to finally order the output.
One thing to consider before getting into the answer is your example code will not compile. To define a type of struct in Go, you would need to change your syntax to
type output struct {
index int
description string
}
In terms of a potential solution to your problem - if you already reliably have unique index's as well as the expected count of the result set - you should not have to do any sorting at all. Instead synchronize the go routines over a channel and insert the output in an allocated slice at the respective index. You can then iterate over that slice to write the contents to a file. For example:
ch := make(chan output) //each go routine will write to this channel
wg := new(sync.WaitGroup) //wait group to sync all go routines
//execute 16 goroutines
for i := 0; i < 16; i++ {
wg.Add(1)
go worker(ch, wg) //this is expecting each worker func to call wg.Done() when completing its portion of work
}
//create a "quit" channel that will be used to signal to the select statement below that your go routines are all done
quit := make(chan bool)
go func() {
wg.Wait()
quit <- true
}()
//initialize a slice with length and capacity to 1mil, the expected result size mentioned in your question
sorted := make([]string, 1000000, 1000000)
//use the for loop, select pattern to sync the results from your 16 go routines and insert them into the sorted slice
for {
select {
case output := <-ch:
//this is not robust - check notes below example
sorted[output.index] = output.description
case <-quit:
//implement a function you could pass the sorted slice to that will write the results
// Ex: writeToFile(sorted)
return
}
}
A couple notes on this solution: it is dependent upon you knowing the size of the expected result set. If you do not know what the size of the result set is - in the select statement you will need to check if the index is read from ch exceeds the length of the sorted slice and allocate additional space before inserting our you program will crash as a result of an out of bounds error
You could use the module Ordered-concurrently to merge your inputs and then print them in order.
https://github.com/tejzpr/ordered-concurrently
Example - https://play.golang.org/p/hkcIuRHj63h
package main
import (
concurrently "github.com/tejzpr/ordered-concurrently/v2"
"log"
"math/rand"
"time"
)
type loadWorker int
// The work that needs to be performed
// The input type should implement the WorkFunction interface
func (w loadWorker) Run() interface{} {
time.Sleep(time.Millisecond * time.Duration(rand.Intn(10)))
return w
}
func main() {
max := 10
inputChan := make(chan concurrently.WorkFunction)
output := concurrently.Process(inputChan, &concurrently.Options{PoolSize: 10, OutChannelBuffer: 10})
go func() {
for work := 0; work < max; work++ {
inputChan <- loadWorker(work)
}
close(inputChan)
}()
for out := range output {
log.Println(out.Value)
}
}
Disclaimer: I'm the module creator

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