All generic questions around Reactor. For advanced questions you can also try #reactor-core and #reactor-netty
Hi, I want help in understanding wether we can maintain trace/span id's in the entire pipeline.
For e.g.,
Flux.just(1,2,3)
.map(i -> i * 2)
.filter(i -> i > 3)
.subscribe(System.out::println);I want to send signal all the way to the down stream kind of unique-ids (span/trace ids) for each element emitted.I am guessing it becomes tricky in case of flatMaps or schedulers?
I tried using Hooks and MutableContext?
I don't want to change the existing pipeline thats why I thought Hooks are best for my problem.Any idea is highly appreciated..
1 reply
hello!
I need to take an object, send it to a server (using a WebClient), log the response, then do some work with it
Mono.just(something)
.doOnNext(this::sendAsyncAndLogResponse)
.doOnNext(this::doSomeWork)
.subscribe()Problem is I don't see the server response in the logs
I assume I should not be calling WebClient.exchange() inside a .doOnNext()
What would be the correct way to do this?
1 reply
Hi, I am looking recommendation on (groupBy & subscribe) vs (flux multicast and filter) to take different action on different event types on the flux. Could someone please help?
https://stackoverflow.com/questions/61814106/choice-between-groupby-and-filter-with-infinite-streams-in-reactor
I am starting with reactive development and I believe the approach is share the flux and filter them in each of the pipelines. I understand that the thread count would be lower, but would this not increase the CPU as computations are lot higher. (I would use a switch case in the regular programming model)
The incoming messages are of the type
"messageType": "lightconfig",
"state": "on"/"off",
"deviceId": "A0001"
}I guess there would be like 15-20 categories eventually. So the common part is retrieving the device details. After that, I see 2 options,
Do the common part of the pipeline and share the observable. Then each subscriber can listen to this. Say there are 20 observers and 100 events. We would be running the filter computation 2000 times.
Do the common part of the pipeline, use group-by to group the observable and subscribe the grouped observable with an observer. the observer will receive the Map<messageType,Observable<Message>>.
5 replies
Hi, I am using reactor.retry.Retry from io.projectreactor.addons:reactor-extra:3.3.4.RELEASE lib to include retries in my reactive chain.Everthing works as expected, but when I run againist blockhound I get a blocking exception as follows.Is there any recommended way to fix this, or is it a bug in the library itself.
at java.io.FileInputStream.readBytes(FileInputStream.java)
at java.io.FileInputStream.read(FileInputStream.java:255)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:246)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:286)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at java.time.zone.TzdbZoneRulesProvider.load(TzdbZoneRulesProvider.java:187)
at java.time.zone.TzdbZoneRulesProvider.<init>(TzdbZoneRulesProvider.java:113)
at java.time.zone.ZoneRulesProvider$1.run(ZoneRulesProvider.java:157)
at java.security.AccessController.doPrivileged(Native Method)
at java.time.zone.ZoneRulesProvider.<clinit>(ZoneRulesProvider.java:144)
at java.time.ZoneRegion.ofId(ZoneRegion.java:120)
at java.time.ZoneId.of(ZoneId.java:411)
at java.time.ZoneId.of(ZoneId.java:359)
at java.time.ZoneId.of(ZoneId.java:315)
at java.util.TimeZone.toZoneId(TimeZone.java:556)
at java.time.ZoneId.systemDefault(ZoneId.java:274)
at reactor.scheduler.clock.SchedulerClock.of(SchedulerClock.java:166)
at reactor.retry.AbstractRetry.<init>(AbstractRetry.java:66)
at reactor.retry.DefaultRetry.<init>(DefaultRetry.java:48)
at reactor.retry.DefaultRetry.create(DefaultRetry.java:58)
at reactor.retry.Retry.allBut(Retry.java:107)
Hi, i'm using the spring framework org.springframework.web.reactive.socket.WebSocketSession, and i create a UnicastProcessor reactor.core.publisher.UnicastProcessor to send messages. LIke this:
publisher = UnicastProcessor.create();
session.send(publisher).subscribe();
// [...] stuff
WebSocketMessage message = new WebSocketMessage(WebSocketMessage.Type.BINARY, dataBuffer);
publisher.onNext(message);It is working perfectly, however i'm curious what happens, if i produce too many messages, and my network can't keep up with the sent messages.
- How do i detect such a thing?
- What happens to my application by default?
- What can i do if that happens? Should implement some kind of backpressure?
I tried to search on google, but no luck, so any help is appreciated
for reactivegridfs: It seems to run out of memory. I am not able to apply backpressure...any hints pls
for (Map<String, Object> metadata : mdList){saveObject(dataBuffer, metadata)
.onErrorContinue((e, a)-> log.error(e.getMessage()))
.subscribe(new BackpressureReadySubscriber());}
public class BackpressureReadySubscriber<T> extends BaseSubscriber<T> {
int limit =100;
int factor = limit;
int delay = 5000;
int consumed;
@Override
protected void hookOnError(Throwable throwable) {
log.error(throwable.getMessage());
}
@Override
public void hookOnSubscribe(Subscription subscription) {
// log.info("Size of request"+ factor);
// initial request, but why it is called everytime
//further request data
request(factor);
}
@Override
@SneakyThrows
public void hookOnNext(T value) {
consumed++;
log.info("Consumed"+consumed);
if (consumed == limit) {
consumed = 0;
log.info("Sleeping for "+delay/1000+" sec");
Thread.sleep(delay);
log.info("woke up after "+delay/1000+" sec");
request(factor);
}
}}
Context values for all publisher chains. This is what I came up with, not sure if I'm terribly ruining everything by doing so:Hooks.onLastOperator("test-hook", publisher -> {
if (publisher instanceof Mono) {
return ((Mono<Object>) publisher).subscriberContext(SomeClass::initContext);
}
return ((Flux<Object>) publisher).subscriberContext(SomeClass::initContext);
});
Hello! I am using Kafka reactor. I consume batch of messages from Kafka and store it in DB asynchronously and the operation returns completableFutures.
This is what I have so far:
Flux<K> flux = receiver.receiveAtmostOnce()
flux
.bufferTimeout(maxBatchSize, batchTimeout)
.onBackpressureBuffer()
.publishOn(Schedulers.boundedElastic())
.doOnError(th -> {
LOG.warn("Exception while handling records", th);
latch.countDown();
})
.doOnCancel(() -> LOG.info("Kafka receiver stopped"))
.subcribe(records ->
completetableFutureArray = processRecords(records)
//Blocking call that I want to avoid//
completetableFutureArray.join()
)I understand using a blocking call is bad but
- If I don't block, how will back pressure work? Won't the subscriber continuously fetch more items before finishing processing of the existing items?
- Mine is a slow consumer fast producer problem and that is why back pressure is important.
Any help/suggestion would be appreciated
need help to read the field value from ServiceRequest object and this object hold only "Part.class" file content.
when i iterate the "partFile" object, it doesn't hold the Form-fields values.
public Mono<ServerResponse> getUploadFiles(ServerRequest request){
return request.multipartData()
.flux()
.flatMap(map -> Flux.fromIterable(map.values()))
.collectList()
.flatMap((partFile) -> ServerResponse.ok()
.body(Mono.just(fileStorageService.storeZipFile(partFile.get(0), "", "")), String.class))
.onErrorResume(
JsonProcessingException.class,
(e) -> ServerResponse.status(HttpStatus.INTERNAL_SERVER_ERROR)
.contentType(MediaType.APPLICATION_JSON)
.body(Mono.just(e.getMessage()), String.class));
}how do i read those form fields, Could you please anyone help me on this
Hello, I'm trying to understand how gRPC Client Cancellation works when using https://github.com/salesforce/reactive-grpc. I have an example program that creates a simple service, something like the following:
@Slf4j
@GrpcService
public class Service extends ReactorServiceGrpc.ServiceImplBase {
@Override
public Mono<User> getUser(Mono<GetUserRequest> requestMono) {
return requestMono
.doOnNext(__-> log.info("Got a request"))
.thenReturn(User.newBuilder().build())
.delayElement(Duration.ofSeconds(5))
.doOnTerminate(() -> log.info("Terminated"));
}
}I expect that I will see get "Terminated" shortly after "Got a request!" if I cancel the call from the client. I, however, see the following output:
2020-10-25 16:17:09.633 [ault-executor-0] : Got request!
2020-10-25 16:17:14.634 [ parallel-2] : Terminated
2020-10-25 16:17:14.637 [ parallel-2] r.c.p.Operators : Operator called default onErrorDropped
io.grpc.StatusRuntimeException: CANCELLED: call already cancelledAny ideas on why this happens and why I don't get the expected behavior?
Hi! Dear reactor team, I cannot understand why this test case does not pass?
when:
//def scheduler = VirtualTimeScheduler.getOrSet();
def rp = Sinks.many().replay().limit(Duration.ofSeconds(1))
def flux = rp.asFlux().doOnNext({
log.info it.toString()
})
for (int i = 0; i < 5; i++) {
rp.emitNext(i, Sinks.EmitFailureHandler.FAIL_FAST);
}
Thread.sleep(2000L)
// scheduler.advanceTimeBy(Duration.ofSeconds(2))
for (int i = 5; i < 10; i++) {
rp.emitNext(i, Sinks.EmitFailureHandler.FAIL_FAST);
}
then:
StepVerifier.create(flux)
.expectNext(5,6,7,8,9)
.thenCancel()
.verify()This test case passes only if I uncomment virual scheduler.
Flux.sample(Duration), but which emits an element immediately if no previous element was received in the preceding sample window, and then resets the sample window from that point. As far as I can see, the Flux.sample(Duration) operator will always wait until the current sample window expires before emitting, even if nothing was emitted in the previous window. Does something like this already exist? I suspect it might be possible to implement what I need with the Flux.sample(Publisher) method but I'm not sure how to approach it, so any pointers here would be much appreciated. Thanks!
Hello!
I've discovered something strange
Server side:
GET("/flux") {
val flux = Flux.range(0, 5)
// .map(Int::toString)
.delayElements(Duration.ofSeconds(1))
ServerResponse.ok().body(flux)
}Client side:
WebClient.create("http://localhost:8080")
.get()
.uri("/flux")
.exchange()
.doOnNext { logger.info(it.statusCode().toString()) }
.doOnNext { it.headers().asHttpHeaders().forEach { logger.info("${it.key}: ${it.value}") } }
.flatMapMany { it.bodyToFlux<String>() }
.subscribe(logger::info)If the server returns a flux of integers,
then response content-type is set to application/json,
client waits for 5 seconds, then receives the response and body together
body is an array of integers
2020-11-01 23:44:00 - GET /flux
2020-11-01 23:44:06 - 200 OK
2020-11-01 23:44:06 - transfer-encoding: [chunked]
2020-11-01 23:44:06 - Content-Type: [application/json]
2020-11-01 23:44:06 - [0,1,2,3,4]If the server returns a flux of strings,
then response content-type is set to text/plain,
client receives response immediately, then waits for 5 seconds, and receives the response body
body is a concatenated string
2020-11-01 23:45:07 - GET /flux
2020-11-01 23:45:08 - 200 OK
2020-11-01 23:45:08 - transfer-encoding: [chunked]
2020-11-01 23:45:08 - Content-Type: [text/plain;charset=UTF-8]
2020-11-01 23:45:12 - 01234Hi there, i'm trying to implement a customQueue for a UnicastProcessor inside a Spring application, to handle bursts (i just want to drop the incoming message, if there is too many). My problem is, if i do
UnicastProcessor<WebSocketMessage> publisher = UnicastProcessor.create(myCustomqueue);then my application totaly freezes overtime, and NOTHING works. there are no more logs, or anything like that. However if i create a UnicastProcessor with 0 parameter in the constructor, then everything is working fine.
Here's my custom queue implementation, it's really simple:
public class LimitedQueue<E> extends ArrayDeque<E> {
private final int limit;
public LimitedQueue(int limit) {
this.limit = limit;
}
@Override
public boolean offer(E o) {
if (size() >= limit) {
return false;
}
return super.offer(o);
}
}I found a really similiar question from 8 months ago here as well:
https://stackoverflow.com/questions/60193240/reactor-unicastprocessor-drop-on-backpressure-when-queue-is-full
Could anyone help me out?
1 reply
Hi everyone, I'm trying reactor Kafka (I'm basicaly a newbie at it), and made the samples work. However the consumer keeps spamming the following logs:
2020-11-04 10:01:36.007+0100 DEBUG 3856 --- [-sample-group-1] o.a.k.c.FetchSessionHandler : [Consumer clientId=sample-consumer, groupId=sample-group] Node 0 sent an incremental fetch response for session 569816377 with 0 response partition(s), 1 implied partition(s)
2020-11-04 10:01:36.008+0100 DEBUG 3856 --- [-sample-group-1] o.a.k.c.c.i.Fetcher : [Consumer clientId=sample-consumer, groupId=sample-group] Added READ_UNCOMMITTED fetch request for partition test2-0 at position FetchPosition{offset=1, offsetEpoch=Optional.empty, currentLeader=LeaderAndEpoch{leader=abbelfynsrv:9092 (id: 0 rack: null), epoch=0}} to node abbelfynsrv:9092 (id: 0 rack: null)
2020-11-04 10:01:36.008+0100 DEBUG 3856 --- [-sample-group-1] o.a.k.c.FetchSessionHandler : [Consumer clientId=sample-consumer, groupId=sample-group] Built incremental fetch (sessionId=569816377, epoch=35) for node 0. Added 0 partition(s), altered 0 partition(s), removed 0 partition(s) out of 1 partition(s)
2020-11-04 10:01:36.008+0100 DEBUG 3856 --- [-sample-group-1] o.a.k.c.c.i.Fetcher : [Consumer clientId=sample-consumer, groupId=sample-group] Sending READ_UNCOMMITTED IncrementalFetchRequest(toSend=(), toForget=(), implied=(test2-0)) to broker abbelfynsrv:9092 (id: 0 rack: null)Is there a way to disable this? I can show my consumer's code if needed.
Hi all,
I'm developing a Spring-Boot Reactor based application that we're currently performance testing. The basic data flow is:
- Fetch a lot of data from the DB using r2dbc-postgresql
- Do some heavy calculations on that data
- Return an aggregation of that data
Now, we're having issues. When the system is under load, our DB reports responding withing < 200ms is most cases, while a lot of our trace data shows that we only receive the first result from the DB in the code after ~1s. And I have no clue where that time difference is coming from.
Some things I have tried:
- moving the cpu heavy calculations to the Parallel scheduler
- even added artificial buffering to the stream to be able to measure throughput, or avoid backpressure problems, but still, the DB code seems extremely slow.
The only thing left for me to try is to throw out the r2dbc-postgresql repository and replace it with plain old jdbc and just schedule that on a boundedElastic scheduler?
Any idea is welcome...
I am developing application using Spring webflux and cassandra as database. I have use case where I want to sort data based on particular field, fetch top 10 records and display on UI. Due to cassandra limitations I cannot do directly through database query.
I have tried to fetch all data from table and sort data on Java layer and then return top 10 records to UI. Though I have millions of records in table, fetching all data and do sorting on Java layer takes significant amount of time.
Is there any better approach to achieve the same on Java layer?
8 replies
I've got a library which parses a lot of XML data and where I have to provide some callback what should be done with the parsed data. Now I try to incorporate this lib in my reactive application like this
private fun InputStream.parse(): Flux<ParsedProduct> = Flux.create { sink ->
val requested = AtomicLong(0)
sink.onRequest {
if (logger.isTraceEnabled) {
logger.trace("Requested ParsedProducts", kv("number", it))
}
requested.addAndGet(it)
}
val parser = XmlArchiveParser(ProductParser()) {
if (logger.isTraceEnabled) {
logger.trace("Parsed product", kv("productId", it.productId))
}
while (requested.get() <= 0) {
logger.trace { "Waiting for requests" }
Thread.sleep(5)
}
sink.next(it)
requested.decrementAndGet()
}
parser.importAndProcessProducts(this)
sink.complete()
}Is this a proper way to implement this hybrid push/pull backpressure mechanism? If so which Thread gets blocked currently by the Thread.sleep? Should I subscribe this stuff on boundedElastic()?
I'm using Spring WebClient (based afaik on reactor-netty-httpclient?)
I'm sending a stream or 5 values with a one second delay (Flux<Object>, content-type = application/x-ndjson) to the server, and receiving the response as a Flux as well
I expect to see it the logs something like this:
object #1 send
response #1 received
object #2 send
response #2 received
...Objects are sent one-by-one, and responses are also received one-by-one
but WebClient starts receiving the response only after it finishes to send the request
I've found a similar question on SO: https://stackoverflow.com/questions/52113235
In it, @bclozel says that Spring WebClient and Reactor Netty HttpClient only start processing the response after they're finished processing the request
Also, @violetagg told me that if the Netty server sends a response before it it finished processing the request body, then the remaining request body is discarded (?), as per the HTTP spec (?)
Could you please confirm that this is the way WebFlux and Reactor Netty work by design?
Interestingly, another answer on SO says that Jetty-based WebClient works differently, it is able to start receiving the response before finishing to process the request
Is the restriction on the client side, or server side, or both?
@mplain
Also, @violetagg told me that if the Netty server sends a response before it it finished processing the request body, then the remaining request body is discarded (?), as per the HTTP spec (?)
And this is true if you finalise the response and not if you start writing the response
HttpServer server =
HttpServer.create()
.port(PORT)
.route(r -> r.post("/echo",
(req, res) -> res.header(CONTENT_TYPE, TEXT_PLAIN)
.send(req.receive().retain())));then the remaining request body is discarded (?), as per the HTTP spec (?)
https://tools.ietf.org/html/rfc7230#section-6.3
A server MUST read
the entire request message body or close the connection after sending
its response, since otherwise the remaining data on a persistent
connection would be misinterpreted as the next request.blockhound barks at KafkaConsumer.poll being a blocking method
I've found a github issue about it: reactor/reactor-kafka#63
should I move that flux to another scheduler to make the dog happy, or is there not point really?
11 replies
Lock beforehand. After execution the Lock has to be released. Now doFinally sadly executes after the completion of the Publisher so there is no way (that I know of) that I can test this behavior. What would you suggest how I should handle this?
11 replies
