Besides a few tutorials on Go I have no actual experience in it. I'm trying to take a project written in Go and converting it into a windows service.
I honestly haven't tried anything besides trying to find things to read over. I have found a few threads and choosen the best library I felt covered all of our needs
https://github.com/golang/sys
// Copyright 2012 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
// +build windows
package main
import (
"fmt"
"strings"
"time"
"golang.org/x/sys/windows/svc"
"golang.org/x/sys/windows/svc/debug"
"golang.org/x/sys/windows/svc/eventlog"
)
var elog debug.Log
type myservice struct{}
func (m *myservice) Execute(args []string, r <-chan svc.ChangeRequest, changes chan<- svc.Status) (ssec bool, errno uint32) {
const cmdsAccepted = svc.AcceptStop | svc.AcceptShutdown | svc.AcceptPauseAndContinue
changes <- svc.Status{State: svc.StartPending}
fasttick := time.Tick(500 * time.Millisecond)
slowtick := time.Tick(2 * time.Second)
tick := fasttick
changes <- svc.Status{State: svc.Running, Accepts: cmdsAccepted}
loop:
for {
select {
case <-tick:
beep()
elog.Info(1, "beep")
case c := <-r:
switch c.Cmd {
case svc.Interrogate:
changes <- c.CurrentStatus
// Testing deadlock from https://code.google.com/p/winsvc/issues/detail?id=4
time.Sleep(100 * time.Millisecond)
changes <- c.CurrentStatus
case svc.Stop, svc.Shutdown:
// golang.org/x/sys/windows/svc.TestExample is verifying this output.
testOutput := strings.Join(args, "-")
testOutput += fmt.Sprintf("-%d", c.Context)
elog.Info(1, testOutput)
break loop
case svc.Pause:
changes <- svc.Status{State: svc.Paused, Accepts: cmdsAccepted}
tick = slowtick
case svc.Continue:
changes <- svc.Status{State: svc.Running, Accepts: cmdsAccepted}
tick = fasttick
default:
elog.Error(1, fmt.Sprintf("unexpected control request #%d", c))
}
}
}
changes <- svc.Status{State: svc.StopPending}
return
}
func runService(name string, isDebug bool) {
var err error
if isDebug {
elog = debug.New(name)
} else {
elog, err = eventlog.Open(name)
if err != nil {
return
}
}
defer elog.Close()
elog.Info(1, fmt.Sprintf("starting %s service", name))
run := svc.Run
if isDebug {
run = debug.Run
}
err = run(name, &myservice{})
if err != nil {
elog.Error(1, fmt.Sprintf("%s service failed: %v", name, err))
return
}
elog.Info(1, fmt.Sprintf("%s service stopped", name))
}
So I spent some time going over this code. Tested it out to see what it does. It performs as it should.
The question I have is we currently have a Go program that takes in arguments and for our service we pass in server. Which spins up our stuff on a localhost webpage.
I believe the code above may have something to do with that but I'm lost at how I would actually get it spin off our exe with the correct arguements. Is this the right spot to call main?
Im sorry if this is vague. I dont know exactly how to make this interact with our already exisiting exe.
I can get that modified if I know what needs to be changed. I appreacite any help.
OK, that's much clearer now. Well, ideally you should start with some tutorial on what constitutes a Windows service—I bet tihis might have solved the problem for you. But let's try anyway.
Some theory
A Windows service sort of has two facets: it performs some useful task and it communicates with the SCM facility. When you manipulate a service using the sc command or through the Control Panel, you have that piece of software to talk with SCM on your behalf, and SCM talks with that service.
The exact protocol the SCM and a service use is low-level and complicated
and the point of the Go package you're using is to hide that complexity from you
and offer a reasonably Go-centric interface to that stuff.
As you might gather from your own example, the Execute method of the type you've created is—for the most part—concerned with communicating with SCM: it runs an endless for loop which on each iteration sleeps on reading from the r channel, and that channel delivers SCM commands to your service.
So you basically have what could be called "an SCM command processing loop".
Now recall those two facets above. You already have one of them: your service interacts with SCM, so you need another one—the code which actually performs useful tasks.
In fact, it's already partially there: the example code you've grabbed creates a time ticker which provides a channel on which it delivers a value when another tick passes. The for loop in the Execute method reads from that channel as well, "doing work" each time another tick is signalled.
OK, this is fine for a toy example but lame for a real work.
Approaching the solution
So let's pause for a moment and think about our requirements.
We need some code running and doing our actual task(s).
We need the existing command processing loop to continue working.
We need these two pieces of code to work concurrently.
In this toy example the 3rd point is there "for free" because a time ticker carries out the task of waiting for the next tick automatically and fully concurrently with the rest of the code.
Your real code most probably won't have that luxury, so what do you do?
In Go, when you need to do something concurrently with something else,
an obvious answer is "use a goroutine".
So the first step is to grab your existing code, turn it into a callable function
and then call it in a separate goroutine right before entering the for loop.
This way, you'll have both pieces run concurrently.
The hard parts
OK, that wasn't hard.
The hard parts are:
How to configure the code which performs the tasks.
How to make the SCM command processing loop and the code carrying out tasks communicate.
Configuration
This one really depends on the policies at your $dayjob or of your $current_project, but there are few hints:
A Windows service may receive command-line arguments—either for a single run or permanently (passed to the service on each of its runs).
The downside is that it's not convenient to work with them from the UI/UX standpoint.
Typically Windows services used to read the registry.
These days (after the advent of .NET and its pervasive xml-ity) the services tend to read configuration files.
The OS environment most of the time is a bad fit for the task.
You may combine several of these venues.
I think I'd start with a configuration file but then again, you should pick the path of the least resistance, I think.
One of the things to keep in mind is that the reading and processing of the configuration should better be done before the service signals the SCM it started OK: if the configuration is invalid or cannot be loaded, the service should extensively log that and signal it failed, and not run the actual task processing code.
Communication between the command processing loop and the tasks carrying code
This is IMO the hardest part.
It's possible to write a whole book here but let's keep it simple for now.
To make it as simple as possible I'd do the following:
Consider pausing, stopping and shutting down mostly the same: all these signals must tell your task processing code to quit, and then wait for it to actually do that.
Consider the "continue" signal the same as starting the task processing function: run it again—in a new goroutine.
Have a one-directional communication: from the control loop to the tasks processing code, but not the other way—this will greatly simplify service state management.
This way, you may create a single channel which the task processing code listens on—or checks periodically, and when a value comes from that channel, the code stops running, closes the channel and exits.
The control loop, when the SCM tells it to pause or stop or shut down, sends anything on that channel then waits for it to close. When that happens, it knows the tasks processing code is finished.
In Go, a paradigm for a channel which is only used for signaling, is to have a channel of type struct{} (an empty struct).
The question of how to monitor this control channel in the tasks running code is an open one and heavily depends on the nature of the tasks it performs.
Any further help here would be reciting what's written in the Go books on concurrency so you should have that covered first.
There's also an interesting question of how to have the communication between the control loop and the tasks processing loop resilient to the possible processing stalls in the latter, but then again, IMO it's too early to touch upon that.
Related
Go's documentation says that
Gosched yields the processor, allowing other goroutines to run. It does not suspend the current goroutine, so execution resumes automatically.
Based on that definition if I have a series of long running go routines being created and executed concurrently, would it be advantageous to write a select statement the following way:
for {
select {
case msg := <- msgch :
fmt.Println(msg)
default:
runtime.Gosched()
}
}
I assume based on the documentation, this code can result in more go routines being run. Is my assumption correct?
No, it isn't necessary here, because whenever Go is waiting on a channel or waiting for I/O, it allows other goroutines to run automatically. That's been the case since Go 1.0.
In Go 1.2 the Go runtime's scheduler added automatic preemption points whenever you called a function. Prior to that if you had a CPU-bound loop (even with a function call) it could starve the scheduler and you might need runtime.Gosched.
And then in Go 1.14, they made this aspect of the runtime even better, and even tight CPU-bound loops with no functions calls are automatically pre-empted.
So with any Go version, you don't need to call runtime.Gosched when you're just waiting on a channel or on I/O; before 1.14, you may have wanted to call it if you were doing a long-running calculation. But with Go 1.14+, I don't see why you'd ever need to call it manually.
If I was reviewing your actual code, I'd suggest changing it to a simple for ... range loop:
for msg := range msgCh {
fmt.Println(msg)
}
This will wait for each message to come in and print it, and stop if/when the channel is closed. However, you would want a switch if you're waiting on another channel or done signal, for example a context. Something like this:
for {
select {
case msg := <- msgCh:
fmt.Println(msg)
case <-ctx.Done():
return
}
}
Does using runtime.Gosched() [anywhere] make any sense?
No. It basically is never needed or sensible to use Gosched.
I'm trying to understand best practices for Golang concurrency. I read O'Reilly's book on Go's concurrency and then came back to the Golang Codewalks, specifically this example:
https://golang.org/doc/codewalk/sharemem/
This is the code I was hoping to review with you in order to learn a little bit more about Go. My first impression is that this code is breaking some best practices. This is of course my (very) unexperienced opinion and I wanted to discuss and gain some insight on the process. This isn't about who's right or wrong, please be nice, I just want to share my views and get some feedback on them. Maybe this discussion will help other people see why I'm wrong and teach them something.
I'm fully aware that the purpose of this code is to teach beginners, not to be perfect code.
Issue 1 - No Goroutine cleanup logic
func main() {
// Create our input and output channels.
pending, complete := make(chan *Resource), make(chan *Resource)
// Launch the StateMonitor.
status := StateMonitor(statusInterval)
// Launch some Poller goroutines.
for i := 0; i < numPollers; i++ {
go Poller(pending, complete, status)
}
// Send some Resources to the pending queue.
go func() {
for _, url := range urls {
pending <- &Resource{url: url}
}
}()
for r := range complete {
go r.Sleep(pending)
}
}
The main method has no way to cleanup the Goroutines, which means if this was part of a library, they would be leaked.
Issue 2 - Writers aren't spawning the channels
I read that as a best practice, the logic to create, write and cleanup a channel should be controlled by a single entity (or group of entities). The reason behind this is that writers will panic when writing to a closed channel. So, it is best for the writer(s) to create the channel, write to it and control when it should be closed. If there are multiple writers, they can be synced with a WaitGroup.
func StateMonitor(updateInterval time.Duration) chan<- State {
updates := make(chan State)
urlStatus := make(map[string]string)
ticker := time.NewTicker(updateInterval)
go func() {
for {
select {
case <-ticker.C:
logState(urlStatus)
case s := <-updates:
urlStatus[s.url] = s.status
}
}
}()
return updates
}
This function shouldn't be in charge of creating the updates channel because it is the reader of the channel, not the writer. The writer of this channel should create it and pass it to this function. Basically saying to the function "I will pass updates to you via this channel". But instead, this function is creating a channel and it isn't clear who is responsible of cleaning it up.
Issue 3 - Writing to a channel asynchronously
This function:
func (r *Resource) Sleep(done chan<- *Resource) {
time.Sleep(pollInterval + errTimeout*time.Duration(r.errCount))
done <- r
}
Is being referenced here:
for r := range complete {
go r.Sleep(pending)
}
And it seems like an awful idea. When this channel is closed, we'll have a goroutine sleeping somewhere out of our reach waiting to write to that channel. Let's say this goroutine sleeps for 1h, when it wakes up, it will try to write to a channel that was closed in the cleanup process. This is another example of why the writters of the channels should be in charge of the cleanup process. Here we have a writer who's completely free and unaware of when the channel was closed.
Please
If I missed any issues from that code (related to concurrency), please list them. It doesn't have to be an objective issue, if you'd have designed the code in a different way for any reason, I'm also interested in learning about it.
Biggest lesson from this code
For me the biggest lesson I take from reviewing this code is that the cleanup of channels and the writing to them has to be synchronized. They have to be in the same for{} or at least communicate somehow (maybe via other channels or primitives) to avoid writing to a closed channel.
It is the main method, so there is no need to cleanup. When main returns, the program exits. If this wasn't the main, then you would be correct.
There is no best practice that fits all use cases. The code you show here is a very common pattern. The function creates a goroutine, and returns a channel so that others can communicate with that goroutine. There is no rule that governs how channels must be created. There is no way to terminate that goroutine though. One use case this pattern fits well is reading a large resultset from a
database. The channel allows streaming data as it is read from the
database. In that case usually there are other means of terminating the
goroutine though, like passing a context.
Again, there are no hard rules on how channels should be created/closed. A channel can be left open, and it will be garbage collected when it is no longer used. If the use case demands so, the channel can be left open indefinitely, and the scenario you worry about will never happen.
As you are asking about if this code was part of a library, yes it would be poor practice to spawn goroutines with no cleanup inside a library function. If those goroutines carry out documented behaviour of the library, it's problematic that the caller doesn't know when that behaviour is going to happen. If you have any behaviour that is typically "fire and forget", it should be the caller who chooses when to forget about it. For example:
func doAfter5Minutes(f func()) {
go func() {
time.Sleep(5 * time.Minute)
f()
log.Println("done!")
}()
}
Makes sense, right? When you call the function, it does something 5 minutes later. The problem is that it's easy to misuse this function like this:
// do the important task every 5 minutes
for {
doAfter5Minutes(importantTaskFunction)
}
At first glance, this might seem fine. We're doing the important task every 5 minutes, right? In reality, we're spawning many goroutines very quickly, probably consuming all available memory before they start dropping off.
We could implement some kind of callback or channel to signal when the task is done, but really, the function should be simplified like so:
func doAfter5Minutes(f func()) {
time.Sleep(5 * time.Minute)
f()
log.Println("done!")
}
Now the caller has the choice of how to use it:
// call synchronously
doAfter5Minutes(importantTaskFunction)
// fire and forget
go doAfter5Minutes(importantTaskFunction)
This function arguably should also be changed. As you say, the writer should effectively own the channel, as they should be the one closing it. The fact that this channel-reading function insists on creating the channel it reads from actually coerces itself into this poor "fire and forget" pattern mentioned above. Notice how the function needs to read from the channel, but it also needs to return the channel before reading. It therefore had to put the reading behaviour in a new, un-managed goroutine to allow itself to return the channel right away.
func StateMonitor(updates chan State, updateInterval time.Duration) {
urlStatus := make(map[string]string)
ticker := time.NewTicker(updateInterval)
defer ticker.Stop() // not stopping the ticker is also a resource leak
for {
select {
case <-ticker.C:
logState(urlStatus)
case s := <-updates:
urlStatus[s.url] = s.status
}
}
}
Notice that the function is now simpler, more flexible and synchronous. The only thing that the previous version really accomplishes, is that it (mostly) guarantees that each instance of StateMonitor will have a channel all to itself, and you won't have a situation where multiple monitors are competing for reads on the same channel. While this may help you avoid a certain class of bugs, it also makes the function a lot less flexible and more likely to have resource leaks.
I'm not sure I really understand this example, but the golden rule for channel closing is that the writer should always be responsible for closing the channel. Keep this rule in mind, and notice a few points about this code:
The Sleep method writes to r
The Sleep method is executed concurrently, with no method of tracking how many instances are running, what state they are in, etc.
Based on these points alone, we can say that there probably isn't anywhere in the program where it would be safe to close r, because there's seemingly no way of knowing if it will be used again.
I have small Golang package which does some work. This work suppose a high amount of errors could be produced and this is OK. Currently all errors are ignored. Yes it may look strange, but visit the link and check the main purpose of package.
I'd like to extend functionality of the package and provide ability to see errors occurred during runtime. But due to lack of software design skills I have some questions with no answers.
At first, I thought to implement logging inside the package using the existing logging (zerolog, zap or whatever else). But, will it be ok for package's users? Because they might want to use other logging packages and would like to modify output format.
Maybe it's possible to provide a way to user to inject it's own logging?
I'd like to achieve the ability to provide easy-configurable way for logging which could be switched on or off on users demands.
Some go lib use logging like this
in your packge definite a logger interface
type Yourlogging interface{
Errorf(...)
Warningf(...)
Infof(...)
Debugf(...)
}
and definite a variable for this interface
var mylogger Yourlogging
func SetLogger(l yourlogging)error{
mylogger = l
}
in your func, you can call them for logging
mylogger.Infof(..)
mylogger.Errorf(...)
you don't need implement the interface, but you can use them who implement this interface
for example:
SetLogger(os.Stdout) //logging output to stdout
SetLogger(logrus.New()) // logging output to logrus (github.com/sirupsen/logrus)
In Go, you will see some libraries implement logging interfaces like other answers have suggested. However, you could completely avoid your packages needing to log if you structured your application differently, for your example.
For example, in your example application you linked, your main application runtime calls idleexacts.Run(), which starts this function.
// startLoop starts workload using passed settings and database connection.
func startLoop(ctx context.Context, log log.Logger, pool db.DB, tables []string, jobs uint16, minTime, maxTime time.Duration) error {
rand.Seed(time.Now().UnixNano())
// Increment maxTime up to 1 due to rand.Int63n() never return max value.
maxTime++
// While running, keep required number of workers using channel.
// Run new workers only until there is any free slot.
guard := make(chan struct{}, jobs)
for {
select {
// Run workers only when it's possible to write into channel (channel is limited by number of jobs).
case guard <- struct{}{}:
go func() {
table := selectRandomTable(tables)
naptime := time.Duration(rand.Int63n(maxTime.Nanoseconds()-minTime.Nanoseconds()) + minTime.Nanoseconds())
err := startSingleIdleXact(ctx, pool, table, naptime)
if err != nil {
log.Warnf("start idle xact failed: %s", err)
}
// When worker finishes, read from the channel to allow starting another worker.
<-guard
}()
case <-ctx.Done():
return nil
}
}
}
The problem here is all of the orchestration of your logic is happening inside of your packages. Instead, this loop should be running in your main application, and this package should provide users with simple actions such as selectRandomTable() or createTempTable().
If the orchestration of code was in your main application and the package only provided simple actions. It would be much easier to return errors to the user as part of the function calls.
It would also make your packages easier for others to reuse because they have simple actions and open users to use them in other ways than you intended.
My problem can be summarized as the following snippet:
package main
import (
"fmt"
"time"
)
func main() {
done := make(chan int)
done2 := make(chan int)
go func() {
for {
fmt.Println("1")
time.Sleep(time.Duration(1) * time.Second)
}
done <- 1
}()
go func() {
for {
fmt.Println("2")
}
done2 <- 1
}()
<- done
<- done2
}
Where the go routine "1" never gets the chance to run again. After doing some research, it looks like it's because go routine "2" takes up all the CPU.
I had done something similar in java before, and thread "1" can always wake up approximately 1 sec later.
My question is how can I achieve the same behavior in go?(I'm transferring a socket program originally written in Java to Go)
I have also tried runtime.GOMAXPROCS(2), but didn't work
Go routines to someone new to Go can have a number of surprising side effects. One of the more important of these is the problems of empty infinite loops.
The way that the Go scheduler works, every function call should get a preemption point placed in the beginning of the call. This should be happening with your fmt.Println("2") call, meaning that every time a print is called, the scheduler in the background has the ability to move around what routines are running at any given time, increase memory for a goroutine, etc.
Under normal circumstances, even if it is not ideally written code, this should be enough. Given that you have stated in the comments that this is not the actual code that you are working with, its not really possible to answer why your other code might not be working.
If you are interested in learning more about how the go scheduler works, I would recommend this article which goes over preemption, and these articles which covers the scheduler at a lower level.
I would also recommend taking a look through the Tour of Go site. While some of the concepts are rather basic, there are some very complex things that you can do if you are aware of all the tools in your toolbox. I would specifically recommend the concurrency section, and the select statement, which might be able to help you refactor your program easier, and in a manner more fitting to go.
I currently have a MQTT code that can subscribe to a topic, print out the messages received, then publish further instructions to a new topic. The subscribing/printing is completed in one Goroutine, and the publishing is done in another Goroutine. Here is my code:
var wg, pg sync.WaitGroup
// All messages are handled here - printing published messages and publishing new messages
var f MQTT.MessageHandler = func(client MQTT.Client, msg MQTT.Message) {
wg.Add(1)
pg.Add(1)
go func() {
defer wg.Done()
fmt.Printf("%s\n", msg.Payload())
//fmt.Println(os.Getpid())
}()
go func(){
defer pg.Done()
message := ""
//Changing configurations
if strings.Contains(string(msg.Payload()), "arduinoLED") == true {
message = fmt.Sprintf("change configuration")
}
if strings.Contains(string(msg.Payload()), "NAME CHANGED") == true{
message = fmt.Sprintf("change back")
}
// Publish further instructions to "sensor/instruction"
token := client.Publish("sensor/instruction", 0, false, message)
//fmt.Println(os.Getpid())
token.Wait()
}()
}
func main() {
c := make(chan os.Signal, 1)
signal.Notify(c, os.Interrupt, syscall.SIGTERM)
opts := MQTT.NewClientOptions().AddBroker("tcp://test.mosquitto.org:1883")
opts.SetDefaultPublishHandler(f)
// Topic to subscribe to for sensor data
topic := "sensor/data"
opts.OnConnect = func(c MQTT.Client) {
if token := c.Subscribe(topic, 0, f); token.Wait() && token.Error() != nil {
panic(token.Error())
}
}
// Creating new client
client := MQTT.NewClient(opts)
if token := client.Connect(); token.Wait() && token.Error() != nil {
panic(token.Error())
} else {
fmt.Printf("Connected to server\n")
}
wg.Wait()
pg.Wait()
<-c
}
The commented out os.Getpid() line is to check which process I am running that Goroutine on. Right now they both display the same number (which means both are running on the same process?).
My question is: How can I run the two Goroutines on separate processes? Is there a way?
Edit: If this cannot be done, I want to write this code using channels. Here is the code I have for that:
var f MQTT.MessageHandler = func(client MQTT.Client, msg MQTT.Message) {
sensorData := make(chan []byte)
wg.Add(1)
pg.Add(1)
go func() {
defer wg.Done()
//fmt.Printf("%s\n", msg.Payload())
sensorData <- string(msg.Payload())
fmt.Println(<-sensorData) //currently not printing anything
}()
go func(){
defer pg.Done()
message := ""
//Changing configurations
if strings.Contains(<-sensorData, "arduinoLED") == true{
message = fmt.Sprintf("change configuration")
}
if strings.Contains(<-sensorData, "NAME CHANGED") == true{
message = fmt.Sprintf("change back")
}
// Publish further instructions to "sensor/instruction"
token := client.Publish("sensor/instruction", 0, false, message)
token.Wait()
}()
}
However, I am not able to print out any data using channels. What am I doing wrong?
You might be coming from Python, right? ;-)
It has the module named
multiprocessing
in its stdlib, and this might well explain why you have used
this name in the title of your question and why you apparently
are having trouble interpreting what #JimB meant by saying
If you need a separate process, you need to exec it yourself
"Multiprocessing" in Python
The thing is, Python's multiprocessing is a quite high-level
thing which hides under its hood a whole lot of stuff.
When you spawn a multiprocessing.Process and make it run
a function, what really happens is this:
The Python interpreter creates another operating system's
process (using
fork(2) on Unix-like systems
or CreateProcess on Windows) and arranges
for it to execute a Python interpter, too.
The crucial point is that you will now have two processes
running two Python interpters.
It is arranged for that Python interpterer in the
child process to have a way to communicate with the Python
interpreter in the parent process.
This "communication link" necessarily involves some form
of IPC #JimB referred to.
There is simply no other way to communicate data and actions
between separate processes exactly because a commodity
contemporary OS provides strict process separation.
When you exchange Python objects between the processes, the two communicating Python
interpreters serialize and deserialize them behind your back
before sending them over their IPC link and after receiving
them from there, correspondingly.
This is implemented using the pickle module.
Back to Go
Go does not have any direct solution which would closely
match Python's multiprocessing, and I really doubt it could
have been sensibly implemented.
The chief reason for this mostly stems from the fact Go
is quite more lower level than Python, and hence it does not
have the Python's luxury of making sheer assumptions about
the types of values it manages, and it also strives to have
as few hidden costs in its constructs as possible.
Go also strives to steer clear of "framework-style" approaches
to solve problems, and use "library-style" solutions when
possible. (A good rundown of the "framework vs library"
is given, for instance, here.)
Go has everything in its standard library to implement
something akin to Python's multiprocessing but there is no
ready-made frakework-y solution for this.
So what you could do for this is to roll along these lines:
Use os/exec to run another copy of your own process.
Make sure the spawned process "knows" it's started
in the special "slave" mode—to act accordingly.
Use any form of IPC to communicate with the new process.
Exchanging data via the standard I/O streams
of the child process is supposedly
the simplest way to roll (except when you need to exchange
opened files but this is a harder topic, so let's not digress).
Use any suitable package in the encoding/ hierarchy — such as binary, gob, xml — to serialize
and deserialize data when exchanging.
The "go-to" solution is supposedly encoding/gob
but encoding/json will also do just fine.
Invent and implement a simple protocol to tell the
child process what to do, and with which data,
and how to communicate the results back to master.
Does it really worth the trouble?
I would say that no, it doesn't—for a number of reasons:
Go has nothing like the dreaded GIL,
so there's no need to sidestep it to achieve real parallelism
when it is naturally possible.
Memory safety is all in your hands, and achieving it is
not really that hard when you dutifully obey the principle
that what is sent over a channel is now owned by
the receiver. In other words, sending values over a channel
is also the transfer of ownership of those values.
The Go toolchain has integrated race detector, so you
may run your test suite with the -race flag and create evaluation
builds of your program using go build -race for the same
purpose: when a program instrumented in such a way runs,
the race detector crashes it as soon as it detects any
unsynchronized read/write memory access.
The printout resulting from that crash includes
explanatory messages on what, and where went wrong,
with stack traces.
IPC is slow, so the gains may well be offset by the losses.
All-in-all, I see no real reason to separate processes unless
you're writing something like an e-mail processing server
where this concept comes naturally.
Channel is used for communicating between goroutines, you shouldn't use it in same goroutine like this code:
sensorData <- string(msg.Payload())
fmt.Println(<-sensorData) //currently not printing anything
If you like to test printing by channel, you can use buffered channel in same goroutine to avoid blocking, like this:
sensorData := make(chan []byte, 1)
Cheers