This is the 6th post taken from a WIP project called Learn Go by writing tests, the aim of which is to get a familiarity with Go and learn techniques
around TDD.
The first post got you up to speed with TDD
The second post discusses arrays and slices
The third post teaches structs, methods, interfaces & table driven tests
The fourth post shows how to do errors and why pointers are useful
The fifth post showed you how and why to do dependency injection
This chapter is all about concurrency.
Concurrency
Here's the setup: a colleague has written a function, CheckWebsites
, that
checks the status of a list of URLs.
package concurrency
type WebsiteChecker func(string) bool
func CheckWebsites(wc WebsiteChecker, urls []string) map[string]bool {
results := make(map[string]bool)
for _, url := range urls {
results[url] = wc(url)
}
return results
}
It returns a map of each URL checked to a boolean value - true
for a good
response, false
for a bad response.
You also have to pass in a WebsiteChecker
which takes a single URL and returns
a boolean. This is used by the function to check all the websites.
Using dependency injection has allowed them to test the function
without making real HTTP calls, making it reliable and fast.
Here's the test they've written:
package concurrency
import (
"reflect"
"testing"
)
func mockWebsiteChecker(url string) bool {
if url == "waat://furhurterwe.geds" {
return false
}
return true
}
func TestCheckWebsites(t *testing.T) {
websites := []string{
"http://google.com",
"http://blog.gypsydave5.com",
"waat://furhurterwe.geds",
}
actualResults := CheckWebsites(mockWebsiteChecker, websites)
want := len(websites)
got := len(actualResults)
if want != got {
t.Fatalf("Wanted %v, got %v", want, got)
}
expectedResults := map[string]bool{
"http://google.com": true,
"http://blog.gypsydave5.com": true,
"waat://furhurterwe.geds": false,
}
if !reflect.DeepEqual(expectedResults, actualResults) {
t.Fatalf("Wanted %v, got %v", expectedResults, actualResults)
}
}
The function is in production and being used to check hundreds of websites. But your colleague has started to get complaints that it's slow, so they've asked you to help speed it up.
Write a test
Let's use a benchmark to test the speed of CheckWebsites
so that we can see the effect of our changes.
package concurrency
import (
"testing"
"time"
)
func slowStubWebsiteChecker(_ string) bool {
time.Sleep(20 * time.Millisecond)
return true
}
func BenchmarkCheckWebsites(b *testing.B) {
urls := make([]string, 100)
for i := 0; i < len(urls); i++ {
urls[i] = "a url"
}
for i := 0; i < b.N; i++ {
CheckWebsites(slowStubWebsiteChecker, urls)
}
}
The benchmark tests CheckWebsites
using a slice of one hundred urls and uses a new fake implementation of WebsiteChecker
. slowStubWebsiteChecker
is deliberately slow. It uses time.Sleep
to wait exactly twenty milliseconds and then it returns true.
When we run the benchmark using go test -bench=.
:
pkg: github.com/gypsydave5/learn-go-with-tests/concurrency/v0
BenchmarkCheckWebsites-4 1 2249228637 ns/op
PASS
ok github.com/gypsydave5/learn-go-with-tests/concurrency/v0 2.268s
CheckWebsites
has been benchmarked at 2249228637 nanoseconds - about two and a quarter seconds.
Let's try and make this faster.
Write enough code to make it pass
Now we can finally talk about concurrency which, for the purposes of the following, means 'having more than one thing in progress'. This is something that we do naturally everyday.
For instance, this morning I made a cup of tea. I put the kettle on and then, while I was waiting for it to boil, I got the milk out of the fridge, got the tea out of the cupboard, found my favourite mug, put the teabag into the cup and then, when the kettle had boiled, I put the water in the cup.
What I didn't do was put the kettle on and then stand there blankly staring at the kettle until it boiled, then do everything else once the kettle had boiled.
If you can understand why it's faster to make tea the first way, then you can understand how we will make CheckWebsites
faster. Instead of waiting for a website to respond before sending a request to the next website, we will tell our computer to make the next request while it is waiting.
Normally in Go when we call a function doSomething()
we wait for it to return (even if it has no value to return, we still wait for it to finish). We say that this operation is blocking - it makes us wait for it to finish. An operation that does not block in Go will run in a separate process called a goroutine. Think of a process as reading down the page of Go code from top to bottom, going 'inside' each function when it gets called to read what it does. When a separate process starts it's like another reader begins reading inside the function, leaving the original reader to carry on going down the page.
To tell Go to start a new goroutine we turn a function call into a go
statement by putting the keyword go
in front of it: go doSomething()
.
package concurrency
type WebsiteChecker func(string) bool
func CheckWebsites(wc WebsiteChecker, urls []string) map[string]bool {
results := make(map[string]bool)
for _, url := range urls {
go func() {
results[url] = wc(url)
}()
}
return results
}
Because the only way to start a goroutine is to put go
in front of a function call, we often use anonymous functions when we want to start a goroutine. An anonymous function literal looks just the same as a normal function declaration, but without a name (unsurprisingly). You can see one above in the body of the for
loop.
Anonymous functions have a number of features which make them useful, two of which we're using above. Firstly, they can be executed at the same time that the're declared - this is what the ()
at the end of the anonymous function is doing. Secondly they maintain access to the lexical scope they are defined in - all the variables that are available at the point when you declare the anonymous function are also available in the body of the function.
The body of the anonymous function above is just the same as the loop body was before. The only difference is that each iteration of the loop will start a new goroutine, concurrent with the current process (the WebsiteChecker
function) each of which will add its result to the results map.
But when we run go test
:
-------- FAIL: TestCheckWebsites (0.00s)
CheckWebsites_test.go:31: Wanted map[http://google.com:true http://blog.gypsydave5.com:true waat://furhurterwe.geds:false], got map[]
FAIL
exit status 1
FAIL github.com/gypsydave5/learn-go-with-tests/concurrency/v1 0.010s
A quick aside into a parallel(ism) universe...
You might not get this result. You might get a panic message that we're going to talk about in a bit. Don't worry if you got that, just keep running the test until you do get the result above. Or pretend that you did. Up to you. Welcome to concurrency: when it's not handled correctly it's hard to predict what's going to happen. Don't worry - that's why we're writing tests, to help us know when we're handling concurrency predictably.
... and we're back.
We are caught by the original tests WebsiteChecker
is now returning an empty map. What went wrong?
None of the goroutines that our for
loop started had enough time to add their result to the results
map; the WebsiteChecker
function is too fast for them, and it returns the still empty map.
To fix this we can just wait while all the goroutines do their work, and then return. Two seconds ought to do it, right?
package concurrency
import "time"
type WebsiteChecker func(string) bool
func CheckWebsites(wc WebsiteChecker, urls []string) map[string]bool {
results := make(map[string]bool)
for _, url := range urls {
go func() {
results[url] = wc(url)
}()
}
time.Sleep(2 * time.Second)
return results
}
Now when we run the tests you get (or or don't get - see above):
-------- FAIL: TestCheckWebsites (0.00s)
CheckWebsites_test.go:31: Wanted map[http://google.com:true http://blog.gypsydave5.com:true waat://furhurterwe.geds:false], got map[waat://furhurterwe.geds:false]
FAIL
exit status 1
FAIL github.com/gypsydave5/learn-go-with-tests/concurrency/v1 0.010s
This isn't great - why only one result? We might try and fix this by increasing the time we wait - try it if you like. It won't work. The problem here is that the variable url
is reused for each iteration of the for
loop - it takes a new value from urls
each time. But each of our goroutines have a reference to the url
variable - they don't have their own independent copy. So they're all writing the value that url
has at the end of the iteration - the last url. Which is why the one result we have is the last url.
To fix this:
package concurrency
import (
"time"
)
type WebsiteChecker func(string) bool
func CheckWebsites(wc WebsiteChecker, urls []string) map[string]bool {
results := make(map[string]bool)
for _, url := range urls {
go func(u string) {
results[u] = wc(u)
}(url)
}
time.Sleep(2 * time.Second)
return results
}
By giving each anonymous function a parameter for the url - u
- and then calling the anonymous function with the url
as the argument, we make sure that the value of u
is fixed as the value of url
for the iteration of the loop that we're launching the goroutine in. u
is a copy of the value of url
, and so can't be changed.
Now if you're lucky you'll get:
PASS
ok github.com/gypsydave5/learn-go-with-tests/concurrency/v1 2.012s
But if you're unlucky (this is more likely if you run them with go test -bench=.
)
fatal error: concurrent map writes
goroutine 8 [running]:
runtime.throw(0x12c5895, 0x15)
/usr/local/Cellar/go/1.9.3/libexec/src/runtime/panic.go:605 +0x95 fp=0xc420037700 sp=0xc4200376e0 pc=0x102d395
runtime.mapassign_faststr(0x1271d80, 0xc42007acf0, 0x12c6634, 0x17, 0x0)
/usr/local/Cellar/go/1.9.3/libexec/src/runtime/hashmap_fast.go:783 +0x4f5 fp=0xc420037780 sp=0xc420037700 pc=0x100eb65
github.com/gypsydave5/learn-go-with-tests/concurrency/v3.WebsiteChecker.func1(0xc42007acf0, 0x12d3938, 0x12c6634, 0x17)
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:12 +0x71 fp=0xc4200377c0 sp=0xc420037780 pc=0x12308f1
runtime.goexit()
/usr/local/Cellar/go/1.9.3/libexec/src/runtime/asm_amd64.s:2337 +0x1 fp=0xc4200377c8 sp=0xc4200377c0 pc=0x105cf01
created by github.com/gypsydave5/learn-go-with-tests/concurrency/v3.WebsiteChecker
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:11 +0xa1
... many more scary lines of text ...
This is long and scary, but all we need to do is take a breath and read the error: fatal error: concurrent map writes
. Sometimes, when we run our tests, two of the goroutines write to the results map at exactly the same time. Maps in Go don't like it when more than one thing tries to write to them at once, and so fatal error
.
This is a race condition, a bug that occurs when the output of our software is
dependent on the timing and sequence of events that we have no control over. Because we cannot control exactly when each goroutine writes to the results map, we are vulnerable to two goroutines writing to it at the same time.
Go can help us to spot race conditions with its built in race detector. To enable this feature, run the tests with the race
flag: go test -race
.
You should get some output that looks like this:
==================
WARNING: DATA RACE
Write at 0x00c420084d20 by goroutine 8:
runtime.mapassign_faststr()
/usr/local/Cellar/go/1.9.3/libexec/src/runtime/hashmap_fast.go:774 +0x0
github.com/gypsydave5/learn-go-with-tests/concurrency/v3.WebsiteChecker.func1()
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:12 +0x82
Previous write at 0x00c420084d20 by goroutine 7:
runtime.mapassign_faststr()
/usr/local/Cellar/go/1.9.3/libexec/src/runtime/hashmap_fast.go:774 +0x0
github.com/gypsydave5/learn-go-with-tests/concurrency/v3.WebsiteChecker.func1()
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:12 +0x82
Goroutine 8 (running) created at:
github.com/gypsydave5/learn-go-with-tests/concurrency/v3.WebsiteChecker()
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:11 +0xc4
github.com/gypsydave5/learn-go-with-tests/concurrency/v3.TestWebsiteChecker()
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker_test.go:27 +0xad
testing.tRunner()
/usr/local/Cellar/go/1.9.3/libexec/src/testing/testing.go:746 +0x16c
Goroutine 7 (finished) created at:
github.com/gypsydave5/learn-go-with-tests/concurrency/v3.WebsiteChecker()
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:11 +0xc4
github.com/gypsydave5/learn-go-with-tests/concurrency/v3.TestWebsiteChecker()
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker_test.go:27 +0xad
testing.tRunner()
/usr/local/Cellar/go/1.9.3/libexec/src/testing/testing.go:746 +0x16c
==================
The details are, again, hard to read - but WARNING: DATA RACE
is pretty unambiguous. Reading into the body of the error we can see two different goroutines performing writes on a map:
Write at 0x00c420084d20 by goroutine 8:
is writing to the same block of memory as
Previous write at 0x00c420084d20 by goroutine 7:
On top of that we can see the line of code where the write is happening:
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:12
and the line of code where goroutines 7 an 8 are started:
/Users/gypsydave5/go/src/github.com/gypsydave5/learn-go-with-tests/concurrency/v3/websiteChecker.go:11
Everything you need to know is printed to your terminal - all you have to do is be patient enough to read it.
Channels
We can solve this data race by coordinating our goroutines using channels. Channels are a Go data structure that can both receive and send values. These operations, along with their details, allow communication between different processes.
In this case we want to think about the communication between the parent process and each of the goroutines that it makes to do the work of running the WebsiteChecker
function with the url.
package concurrency
type WebsiteChecker func(string) bool
type result struct {
string
bool
}
func CheckWebsites(wc WebsiteChecker, urls []string) map[string]bool {
results := make(map[string]bool)
resultChannel := make(chan result)
for _, url := range urls {
go func(u string) {
resultChannel <- result{u, wc(u)}
}(url)
}
for i := 0; i < len(urls); i++ {
result := <-resultChannel
results[result.string] = result.bool
}
return results
}
Alongside the results
map we now have a resultChannel
, which we make
in the same way. chan result
is the type of the channel - a channel of result
. The new type, result
has been made to associate the return value of the WebsiteChecker
with the url being checked - it's a struct of string
and bool
. As we don't need either value to be named, each of them is anonymous within the struct; this can be useful in when it's hard to know what to name a value.
Now when we iterate over the urls, instead of writing to the map
directly we're sending a result
struct for each call to wc
to the resultChannel
with a send statement. This uses the <-
operator, taking a channel on the left and a value on the right:
// Send statement
resultChannel <- result{u, wc(u)}
The next for
loop iterates once for each of the urls. Inside we're using a receive expression, which assigns a value received from a channel to a variable. This also uses the <-
operator, but with the two operands now reversed: the channel is now on the right and the variable that we're assigning to is on the left:
// Receive expression
result := <-resultChannel
We then use the result
received to update the map.
By sending the results into a channel, we can control the timing of each write into the results map, ensuring that it happens one at a time. Although each of the calls of wc
, and each send to the result channel, is happening in parallel inside its own process, each of the results is being dealt with one at a time as we take values out of the result channel with the receive expression.
We have paralellized the part of the code that we wanted to make faster, while making sure that the part that cannot happen in parallel still happens linearly. And we have communicated across the multiple processes involved by using channels.
When we run the benchmark:
pkg: github.com/gypsydave5/learn-go-with-tests/concurrency/v2
BenchmarkCheckWebsites-8 100 23406615 ns/op
PASS
ok github.com/gypsydave5/learn-go-with-tests/concurrency/v2 2.377s
23406615 nanoseconds - 0.023 seconds, about one hundred times as fast as
original function. A great success.
Wrapping up
This exercise has been a little lighter on the TDD than usual. In a way we've been taking part in one long refactoring of the CheckWebsites
function; the inputs and outputs never changed, it just got faster. But the tests we had in place, as well as the benchmark we wrote, allowed us to refactor CheckWebsites
in a way that maintained confidence that the software was still working, while demonstrating that it had actually become faster.
In making it faster we learned about
- goroutines, the basic unit of concurrency in Go, which let us check more than one website at the same time.
- anonymous functions, which we used to start each of the concurrent processes that check websites.
- channels, to help organize and control the communication between the different processes, allowing us to avoid a race condition bug.
- the race detector which helped us debug problems with concurrent code
Make it fast
One formulation of an agile way of building software, often misattributed to Kent Beck, is:
Where 'work' is making the tests pass, 'right' is refactoring the code, and 'fast' is optimizing the code to make it, for example, run quickly. We can only 'make it fast' once we've made it work and made it right. We were lucky that the code we were given was already demonstrated to be working, and didn't need to be refactored. We should never try to 'make it fast' before the other two steps have been performed because
Premature optimization is the root of all evil
-- Donald Knuth