I am taking my first steps in kotlin coroutines and I have a problem.
In order to create Foo and return it from a function I need to call two heavy service methods asynchronously to get some values for Foo creating. This is my code:
return runBlocking {
val xAsync = async {
service.calculateX()
}
val yAsync = async {
service.calculateY()
}
Foo(xAsync.await(), yAsync.await())
};
However, after reading logs is seems to me that calculateX() and calculateY() are called synchronously. Is my code correct?
Your code isn't perfect, but it is correct in terms of making calculateX() and calculateY() run concurrently. However, since it launches this concurrent work on the runBlocking dispatcher which is single-threaded, and since your heavyweight operations are blocking instead of suspending, they will not be parallelized.
The first observation to make is that blocking operations cannot gain anything from coroutines compared to the old-school approach with Java executors, apart from a bit simpler API.
The second observation is that you can at least make them run in parallel, each blocking its own thread, by using the IO dispatcher:
return runBlocking {
val xAsync = async(Dispatchers.IO) {
service.calculateX()
}
val yAsync = async(Dispatchers.IO) {
service.calculateY()
}
Foo(xAsync.await(), yAsync.await())
};
Compared to using the java.util.concurrent APIs, here you benefit from the library's IO dispatcher instead of having to create your own thread pool.
Related
I have this piece of code:
// this method is used to evaluate the input string, and it returns evaluation result in string format
fun process(input: String): String {
val timeoutMillis = 5000L
val page = browser.newPage()
try {
val result = runBlocking {
withTimeout(timeoutMillis) {
val result = page.evaluate(input).toString()
return#withTimeout result
}
}
return result
} catch (playwrightException: PlaywrightException) {
return "Could not parse template! '${playwrightException.localizedMessage}'"
} catch (timeoutException: TimeoutCancellationException) {
return "Could not parse template! (timeout)"
} finally {
page.close()
}
}
It should throw exception after 5 seconds if the method is taking too long to execute (example: input potentially contains infinite loop) but it doesent (becomes deadlock I assume) coz coroutines should be cooperative. But the method I am calling is from another library and I have no control over its computation (for sticking yield() or smth like it).
So the question is: is it even possible to timeout such coroutine? if yes, then how?
Should I use java thread insted and just kill it after some time?
But the method I am calling is from another library and I have no control over its computation (for sticking yield() or smth like it).
If that is the case, I see mainly 2 situations here:
the library is aware that this is a long-running operation and supports thread interrupts to cancel it. This is the case for Thread.sleep and some I/O operations.
the library function really does block the calling thread for the whole time of the operation, and wasn't designed to handle thread interrupts
Situation 1: the library function is interruptible
If you are lucky enough to be in situation 1, then simply wrap the library's call into a runInterruptible block, and the coroutines library will translate cancellation into thread interruptions:
fun main() {
runBlocking {
val elapsed = measureTimeMillis {
withTimeoutOrNull(100.milliseconds) {
runInterruptible {
interruptibleBlockingCall()
}
}
}
println("Done in ${elapsed}ms")
}
}
private fun interruptibleBlockingCall() {
Thread.sleep(3000)
}
Situation 2: the library function is NOT interruptible
In the more likely situation 2, you're kind of out of luck.
Should I use java thread insted and just kill it after some time?
There is no such thing as "killing a thread" in Java. See Why is Thread.stop deprecated?, or How do you kill a Thread in Java?.
In short, in that case you do not have a choice but to block some thread.
I do not know a solution to this problem that doesn't leak resources. Using an ExecutorService would not help if the task doesn't support thread interrupts - the threads will not die even with shutdownNow() (which uses interrupts).
Of course, the blocked thread doesn't have to be your thread. You can technically launch a separate coroutine on another thread (using another dispatcher if yours is single-threaded), to wrap the libary function call, and then join() the job inside a withTimeout to avoid waiting for it forever. That is however probably bad, because you're basically deferring the problem to whichever scope you use to launch the uncancellable task (this is actually why we can't use a simple withContext here).
If you use GlobalScope or another long-running scope, you effectively leak the hanging coroutine (without knowing for how long).
If you use a more local parent scope, you defer the problem to that scope. This is for instance the case if you use the scope of an enclosing runBlocking (like in your example), which makes this solution pointless:
fun main() {
val elapsed = measureTimeMillis {
doStuff()
}
println("Completely done in ${elapsed}ms")
}
private fun doStuff() {
runBlocking {
val nonCancellableJob = launch(Dispatchers.IO) {
uncancellableBlockingCall()
}
val elapsed = measureTimeMillis {
withTimeoutOrNull(100.milliseconds) {
nonCancellableJob.join()
}
}
println("Done waiting in ${elapsed}ms")
} // /!\ runBlocking will still wait here for the uncancellable child coroutine
}
// Thread.sleep is in fact interruptible but let's assume it's not for the sake of the example
private fun uncancellableBlockingCall() {
Thread.sleep(3000)
}
Outputs something like:
Done waiting in 122ms
Completely done in 3055ms
So the bottom line is either live with this long thing potentially hanging, or ask the developers of that library to handle interruption or make the task cancellable.
I have a Kotlin Backend/server API using Ktor, and inside a certain endpoint's service logic I need to concurrently get details for a list of ids and then return it all to the client with the 200 response.
The way I wanted to do it is by using async{} and awaitAll()
However, I can't understand whether I should use runBlocking or GlobalScope.
What is really the difference here?
fun getDetails(): List<Detail> {
val fetched: MutableList<Details> = mutableListOf()
GlobalScope.launch { --> Option 1
runBlocking { ---> Option 2
Dispatchers.IO --> Option 3 (or any other dispatcher ..)
myIds.map { id ->
async {
val providerDetails = getDetails(id)
fetched += providerDetails
}
}.awaitAll()
}
return fetched
}
launch starts a coroutine that runs in parallel with your current code, so fetched would still be empty by the time your getDetails() function returns. The coroutine will continue running and mutating the List that you have passed out of the function while the code that retrieved the list already has the reference back and will be using it, so there's a pretty good chance of triggering a ConcurrentModificationException. Basically, this is not a viable solution at all.
runBlocking runs a coroutine while blocking the thread that called it. The coroutine will be completely finished before the return fetched line, so this will work if you are OK with blocking the calling thread.
Specifying a Dispatcher isn't an alternative to launch or runBlocking. It is an argument that you can add to either to determine the thread pool used for the coroutine and its children. Since you are doing IO and parallel work, you should probably be using runBlocking(Dispatchers.IO).
Your code can be simplified to avoid the extra, unnecessary mutable list:
fun getDetails(): List<Detail> = runBlocking(Dispatchers.IO) {
myIds.map { id ->
async {
getDetails(id)
}
}.awaitAll()
}
Note that this function will rethrow any exceptions thrown by getDetails().
If your project uses coroutines more generally, you probably have higher level coroutines running, in which case this should probably be a suspend function (non-blocking) instead:
suspend fun getDetails(): List<Detail> = withContext(Dispatchers.IO) {
myIds.map { id ->
async {
getDetails(id)
}
}.awaitAll()
}
In Vert.x, suppose I have functions like this:
fun caller() {
runBlocking {
val job = GlobalScope.launch(vertx.dispatcher()) {
val r = suspendPart()
println(r) // never execute
}
println(1) // printed
job.join()
println(2) // never execute
}
}
suspend fun asyncPart(): Future<Int> {
val promise: Promise<Int> = Promise.promise()
delay(500)
promise.complete(0)
return promise.future()
}
suspend fun suspendPart(): Int {
return asyncPart().await()
}
r(which is 0) and 2 will never be printed, only 1 is printed. How should I fix it?
My intention is to wait for asyncPart completes (I have a AsyncResult inside actually).
Presumably your caller() method is called by vert.x and this means you're breaking one of the pivotal rules of vert.x:
Don’t block me!
Vert.x is mostly based on very fast single-threaded work, what this means is that when you block the thread in caller, it is unable to execute the coroutine scheduled with launch leading to a deadlock.
The proper way to solve this is to remove your blocking code through the integration vert.x provides for kotlin coroutines.
Alternatively using a different dispatcher for launch would also work since the other thread would unblock the vert.x dispatcher. But this would not solve the primary issue of blocking calls in the vert.x dispatcher.
I need to process all of the results from a paged API endpoint. I'd like to present all of the results as a sequence.
I've come up with the following (slightly psuedo-coded):
suspend fun getAllRowsFromAPI(client: Client): Sequence<Row> {
var currentRequest: Request? = client.requestForNextPage()
return withContext(Dispatchers.IO) {
sequence {
while(currentRequest != null) {
var rowsInPage = runBlocking { client.makeRequest(currentRequest) }
currentRequest = client.requestForNextPage()
yieldAll(rowsInPage)
}
}
}
}
This functions but I'm not sure about a couple of things:
Is the API request happening inside runBlocking still happening with the IO dispatcher?
Is there a way to refactor the code to launch the next request before yielding the current results, then awaiting on it later?
Question 1: The API-request will still run on the IO-dispatcher, but it will block the thread it's running on. This means that no other tasks can be scheduled on that thread while waiting for the request to finish. There's not really any reason to use runBlocking in production-code at all, because:
If makeRequest is already a blocking call, then runBlocking will do practically nothing.
If makeRequest was a suspending call, then runBlocking would make the code less efficient. It wouldn't yield the thread back to the pool while waiting for the request to finish.
Whether makeRequest is a blocking or non-blocking call depends on the client you're using. Here's a non-blocking http-client I can recommend: https://ktor.io/clients/
Question 2: I would use a Flow for this purpose. You can think of it as a suspendable variant of Sequence. Flows are cold, which means that it won't run before the consumer asks for its contents (in contrary to being hot, which means the producer will push new values no matter if the consumer wants it or not). A Kotlin Flow has an operator called buffer which you can use to make it request more pages before it has fully consumed the previous page.
The code could look quite similar to what you already have:
suspend fun getAllRowsFromAPI(client: Client): Flow<Row> = flow {
var currentRequest: Request? = client.requestForNextPage()
while(currentRequest != null) {
val rowsInPage = client.makeRequest(currentRequest)
emitAll(rowsInPage.asFlow())
currentRequest = client.requestForNextPage()
}
}.flowOn(Dispatchers.IO)
.buffer(capacity = 1)
The capacity of 1 means that will only make 1 more request while processing an earlier page. You could increase the buffer size to make more concurrent requests.
You should check out this talk from KotlinConf 2019 to learn more about flows: https://www.youtube.com/watch?v=tYcqn48SMT8
Sequences are definitely not the thing you want to use in this case, because they are not designed to work in asynchronous environment. Perhaps you should take a look at flows and channels, but for your case the best and simplest choice is just a collection of deferred values, because you want to process all requests at once (flows and channels process them one-by-one, maybe with limited buffer size).
The following approach allows you to start all requests asynchronously (assuming that makeRequest is suspended function and supports asynchronous requests). When you'll need your results, you'll need to wait only for the slowest request to finish.
fun getClientRequests(client: Client): List<Request> {
val requests = ArrayList<Request>()
var currentRequest: Request? = client.requestForNextPage()
while (currentRequest != null) {
requests += currentRequest
currentRequest = client.requestForNextPage()
}
return requests
}
// This function is not even suspended, so it finishes almost immediately
fun getAllRowsFromAPI(client: Client): List<Deferred<Page>> =
getClientRequests(client).map {
/*
* The better practice would be making getAllRowsFromApi an extension function
* to CoroutineScope and calling receiver scope's async function.
* GlobalScope is used here just for simplicity.
*/
GlobalScope.async(Dispatchers.IO) { client.makeRequest(it) }
}
fun main() {
val client = Client()
val deferredPages = getAllRowsFromAPI(client) // This line executes fast
// Here you can do whatever you want, all requests are processed in background
Thread.sleep(999L)
// Then, when we need results....
val pages = runBlocking {
deferredPages.map { it.await() }
}
println(pages)
// In your case you also want to "unpack" pages and get rows, you can do it here:
val rows = pages.flatMap { it.getRows() }
println(rows)
}
I happened across suspendingSequence in Kotlin's coroutines-examples:
https://github.com/Kotlin/coroutines-examples/blob/090469080a974b962f5debfab901954a58a6e46a/examples/suspendingSequence/suspendingSequence.kt
This is exactly what I was looking for.
I'm currently writing a test-function which should run a block or (when a certain timeout is reached) throws an exception.
I was trying this with Coroutines in Kotlin but ended up with a mixture of Coroutines and CompletableFuture:
fun <T> runBlockWithTimeout(maxTimeout: Long, block: () -> T ): T {
val future = CompletableFuture<T>()
// runs the coroutine
launch { block() }
return future.get(maxTimeout, TimeUnit.MILLISECONDS)
}
This works, but I'm not sure if this is the intended way to solve that problem in kotlin.
I also tried other approaches:
runBlocking {
withTimeout(maxTimeout) {
block()
}
}
But this seems not to work as soon as the block calls e.g. Thread.sleep(...)
So is the CompletableFuture approach the way to go or is there a better one?
update 1
What I want to achieve:
Async Integration-Test code (like receiving data from RabbitMq) should be tested somehow like this:
var rabbitResults: List = ... // are filled async via RabbitListeners
...
waitMax(1000).toSucceed {
assertThat(rabbitResults).hasSize(1)
}
waitMax(1000).toSucceed {
assertThat(nextQueue).hasSize(3)
}
...
withTimeout { ... } is designed to cancel the ongoing operation on timeout, which is only possible if the operation in question is cancellable.
The reason it works with future.get(timeout, unit) is because it only waits with timeout. It does not actually cancel or abort in any way your background operation which still continues to execute after timeout had elapsed.
If you want to mimick similar behavior with coroutines, then you should wait with timeout, like this:
val d = async { block() } // run the block code in background
withTimeout(timeout, unit) { d.await() } // wait with timeout
It works properly because await is a cancellable function which you can verify by reading its API documentation.
However, if you want to actually cancel the ongoing operation on timeout, then then you should implement your code in asyncronous and cancellable way. Cancellation is cooperative, so, to start, the underlying library that you are using in your code has to provide asynchronous API that supports cancellation of ongoing operation.
You can read more about cancellation and timeouts in the corresponding section of the coroutines guide and watch the KotlinConf's Deep Dive into Coroutines on how to integrate coroutines with asynchronous libraries.