I'm replacing my current implementation using RxJava to Coroutines and Flow. I'm having some trouble using some Flow operators.
I'm trying to filter the list of items inside a Flow before providing it to be collected. (Flow<List<TaskWithCategory>>)
Here is the example on Rx2:
repository.findAllTasksWithCategory()
.flatMap {
Flowable.fromIterable(it)
.filter { item -> item.task.completed }
.toList()
.toFlowable()
In the implementation above, I provide a list of TaskWithCategory filtering by Tasks that are already completed.
How can I achieve this using Flow?
Given that the only operator in use is filter the inner flowable is unnecessary, making the flow implementation quite straightforward:
repository.findAllTasksWithCategoryFlow()
.map { it.filter { item -> item.task.completed } }
If the inner transformation is more involved (lets use transform: suspend (X) -> TaskWithCategory):
repository.findAllTasksWithCategoryFlow()
// Pick according to desired backpressure behavior
.flatMap(Latest/Concat/Merge) {
// Scope all transformations together
coroutineScope {
it.map { item ->
// Perform transform in parallel
async {
transform(item)
}
}.awaitAll() // Return when all async are finished.
}
}
Related
I have a requirement, where we want to asynchronously handle some upstream request/payload via coroutine. I see that there are several ways to do this, but wondering which is the right approach -
Provide explicit spring service class that implements CoroutineScope
Autowire singleton scope-context backed by certain defined thread-pool dispatcher.
Define method local CoroutineScope object
Following on this question, I'm wondering whats the trade-off if we define method local scopes like below -
fun testSuspensions(count: Int) {
val launchTime = measureTimeMillis {
val parentJob = CoroutineScope(Dispatchers.IO).launch {
repeat(count) {
this.launch {
process() //Some lone running process
}
}
}
}
}
Alternative approach to autowire explicit scope object backed by custom dispatcher -
#KafkaListener(
topics = ["test_topic"],
concurrency = "1",
containerFactory = "someListenerContainerConfig"
)
private fun testKafkaListener(consumerRecord: ConsumerRecord<String, ByteArray>, ack: Acknowledgment) {
try {
this.coroutineScope.launch {
consumeRecordAsync(consumerRecord)
}
} finally {
ack.acknowledge()
}
}
suspend fun consumeRecordAsync(record: ConsumerRecord<String, ByteArray>) {
println("[${Thread.currentThread().name}] Starting to consume record - ${record.key()}")
val statusCode = initiateIO(record) // Add error-handling depending on kafka topic commit semantics.
// Chain any-other business logic (depending on status-code) as suspending functions.
consumeStatusCode(record.key(), statusCode)
}
suspend fun initiateIO(record: ConsumerRecord<String, ByteArray>): Int {
return withContext(Dispatchers.IO) { // Switch context to IO thread for http.
println("[${Thread.currentThread().name}] Executing network call - ${record.key()}")
delay(1000 * 2) // Simulate IO call
200 // Return status-code
}
}
suspend fun consumeStatusCode(recordKey: String, statusCode: Int) {
delay(1000 * 1) // Simulate work.
println("[${Thread.currentThread().name}] consumed record - $recordKey, status-code - $statusCode")
}
Autowiring bean as follows in some upstream config class -
#Bean(name = ["testScope"])
fun defineExtensionScope(): CoroutineScope {
val threadCount: Int = 4
return CoroutineScope(Executors.newFixedThreadPool(threadCount).asCoroutineDispatcher())
}
It depends on what your goal is. If you just want to avoid the thread-per-request model, you can use Spring's support for suspend functions in controllers instead (by using webflux), and that removes the need from even using an external scope at all:
suspend fun testSuspensions(count: Int) {
val execTime = measureTimeMillis {
coroutineScope {
repeat(count) {
launch {
process() // some long running process
}
}
}
}
// all child coroutines are done at this point
}
If you really want your method to return immediately and schedule coroutines that outlive it, you indeed need that extra scope.
Regarding option 1), making custom classes implement CoroutineScope is not encouraged anymore (as far as I understood). It's usually suggested to use composition instead (declare a scope as a property instead of implementing the interface by your own classes). So I would suggest your option 2.
I would say option 3) is out of the question, because there is no point in using CoroutineScope(Dispatchers.IO).launch { ... }. It's no better than using GlobalScope.launch(Dispatchers.IO) { ... } (it has the same pitfalls) - you can read about the pitfalls of GlobalScope in its documentation.
The main problem being that you run your coroutines outside structured concurrency (your running coroutines are not children of a parent job and may accumulate and hold resources if they are not well behaved and you forget about them). In general it's better to define a scope that is cancelled when you no longer need any of the coroutines that are run by it, so you can clean rogue coroutines.
That said, in some circumstances you do need to run coroutines "forever" (for the whole life of your application). In that case it's ok to use GlobalScope, or a custom application-wide scope if you need to customize things like the thread pool or exception handler. But in any case don't create a scope on the spot just to launch a coroutine without keeping a handle to it.
In your case, it seems you have no clear moment when you wouldn't care about the long running coroutines anymore, so you may be ok with the fact that your coroutines can live forever and are never cancelled. In that case, I would suggest a custom application-wide scope that you would wire in your components.
I am working on spring reactive and need to call multiple calls sequentially to other REST API using webclient. The issue is I am able to call multiple calls to other Rest API but response am not able to read without subscribe or block. I can't use subscribe or block due to non reactive programming. Is there any way, i can merge while reading the response and send it as flux.
Below is the piece of code where I am stuck.
private Flux<SeasonsDto> getSeasonsInfo(List<HuntsSeasonsMapping> l2, String seasonsUrl) {
for (HuntsSeasonsMapping s : l2)
{
List<SeasonsJsonDto> list = huntsSeasonsProcessor.appendSeaosonToJson(s.getSeasonsRef());
for (SeasonsJsonDto sjdto:list)
{
Mono<SeasonsDto> mono =new SeasonsAdapter("http://localhost:8087/").callToSeasonsAPI(sjdto.getSeasonsRef());
//Not able to read stream without subscribe an return as Flux object
}
public Mono<SeasonsDto> callToSeasonsAPI(Long long1) {
LOGGER.debug("Seasons API call");
return this.webClient.get().uri("hunts/seasonsInfo/"
+long1).header("X-GoHunt-LoggedIn-User",
"a4d4b427-c716-458b-9bb5-9917b6aa30ff").retrieve().bodyToMono(SeasonsDto.class);
}
Please help to resolve this.
You need to combine the reactive streams using operators such as map, flatMap and concatMap.
private Flux<SeasonsDto> getSeasonsInfo(List<HuntsSeasonsMapping> l2, String seasonsUrl) {
List<Mono<SeasonsDto>> monos = new ArrayList<>();
for (HuntsSeasonsMapping s : l2) {
List<SeasonsJsonDto> list = huntsSeasonsProcessor.appendSeaosonToJson(s.getSeasonsRef());
for (SeasonsJsonDto sjdto:list) {
Mono<SeasonsDto> mono =new SeasonsAdapter("http://localhost:8087/").callToSeasonsAPI(sjdto.getSeasonsRef());
//Not able to read stream without subscribe an return as Flux object
monos.add(mono);
}
}
return Flux.fromIterable(monos).concatMap(mono -> mono);
}
This can further be improved using the steam API, which I suggest you look into, but I didn't want to change too much of your existing code.
I have figured how to do this. I have completely rewrite the code and change in reactive. It means all the for loop has been removed. Below is the code for the same and may be help for others.
public Flux<SeasonsDto> getAllSeasonDetails(String uuid) {
return hunterRepository.findByUuidAndIsPrimaryAndDeleted(uuid, true, false).next().flatMapMany(h1 -> {
return huntsMappingRepository.findByHunterIdAndDeleted(h1.getId(), false).flatMap(k -> {
return huntsMappingRepository.findByHuntReferrenceIdAndDeleted(k.getHuntReferrenceId(), false)
.flatMap(l2 -> {
return huntsSeasonsProcessor.appendSeaosonToJsonFlux(l2.getSeasonsDtl()).flatMap(fs -> {
return seasonsAdapter.callSeasonsAPI(fs.getSeasonsRef(), h1.getId(), uuid).map(k->{
return k;
});
});
});
});
});
}
Is it possible to allow emitting values from a Flux conditionally based on a global boolean variable?
I'm working with Flux delayUntil(...) but not able to fully grasp the functionality or my assumptions are wrong.
I have a global AtomicBoolean that represents the availability of a downstream connection and only want the upstream Flux to emit if the downstream is ready to process.
To represent the scenario, created a (not working) test sample
//Randomly generates a boolean value every 5 seconds
private Flux<Boolean> signalGenerator() {
return Flux.range(1, Integer.MAX_VALUE)
.delayElements(Duration.ofMillis(5000))
.map(integer -> new Random().nextBoolean());
}
and
Flux.range(1, Integer.MAX_VALUE)
.delayElements(Duration.ofMillis(1000))
.delayUntil(evt -> signalGenerator()) // ?? Only proceed when signalGenerator returns true
.subscribe(System.out::println);
I have another scenario where a downstream process can accept only x messages a second. In the current non-reactive implementation we have a Semaphore of x permits and the thread is blocked if no more permits are available, with Semaphore permits resetting every second.
In both scenarios I want upstream Flux to emit only when there is a demand from the downstream process, and I do not want to Buffer.
You might consider using Mono.fromRunnable() as an input to delayUntil() like below;
Helper class;
public class FluxCondition {
CountDownLatch latch = new CountDownLatch(10); // it depends, might be managed somehow
Runnable r = () -> { latch.await(); }
public void lock() { Mono.fromRunnable(r) };
public void release() { latch.countDown(); }
}
Usage;
FluxCondition delayCondition = new FluxCondition();
Flux.range(1, 10).delayUntil(o -> delayCondition.lock()).subscribe();
.....
delayCondition.release(); // shall call this for each element
I guess there might be a better solution by using sink.emitNext but this might also require a condition variable for controlling Flux flow.
According my understanding, in reactive programming, your data should be considered in every operator step. So it might be better for you to design your consumer as a reactive processor. In my case I had no chance and followed the way as I described above
Similar to channels and broadcast channels, can flows also be instantiated and reused at multiple places?
General usage of creating flows is wrapping the logic to emit the data inside the flow's body and is returned.
Snippet :
fun listenToDataChanges() : Flow<T>
{
return flow {
dataSource.querySomeInfo()?.consumeEach {
data->
if (someCondition) {
emit(data)
}
}
}
}
Everytime listenToDataChanges() is called, a new flow instance is created and multiple subscriptions would be made. Instead is it possible to create and reuse the instance to avoid multiple subscriptions?
Yes, you just need to store it in a variable instead of recreating the flow each time
By the way it seems like you could simplify this way:
val customFlow = dataSource.querySomeInfo()?.filter { someCondition }
Is there a way to chain several filters in a grails application (as in Java filters)? Maybe something with spring?
I've written a couple of filters, and would like to get them to execute serially (order is not particularly important). The reason behind this? I need to write about 20, 30 filters, and don't want them all in the same file.
I've read about Spring's DelegatingFilterProxy but can't figure out on how to configure it to chain all my grails filters.
Since Grails 1.3.1 you can chain filters by using the "dependsOn" keyword:
def dependsOn = [MyOtherFilters.class]
http://jira.codehaus.org/browse/GRAILS-6229
I may not be understanding the core issue here, but the simple answer might be "they're already chained". Filters are executed based on the selector you put in the filter closure (e.g. myPreProcessorFilter(controller:'', action:'') {}). All selectors that match your controller/action will execute. I do this all the time with logging and performance measurement filters.
Here's an example. Both the logAction and measureMethodTime filters will be applied to all controllers and actions (since I left the selector wide open).
import org.springframework.web.context.request.RequestContextHolder as RCH
import com.x.y.*
class PerformanceFilters {
def filters = {
logAction(controller:'*', action:'*'){
before = {
log.debug("${controllerName}.${actionName}: entering; params=${params}")
}
}
measureMethodTime(controller:'*', action:'*'){
before = {
def session = RCH.currentRequestAttributes().getSession(false)
if (session)
{
Q.startTimer("${session.id}-${controllerName}-${actionName}", "method.${controllerName}.${actionName}")
}
}
afterView = {
def session = RCH.currentRequestAttributes().getSession(false)
if (session)
{
Q.stopTimer("${session.id}-${controllerName}-${actionName}", "method.${controllerName}.${actionName}")
}
}
}
}
}
http://grails.org/doc/latest/guide/single.html#6.6.4%20Filter%20Dependencies