I am new for Vert.x async programming. I have event_bus consumer, once it receives a message, then it needs to call a Async. method async_method_to_access_database to get database records from Database. async_method_to_access_database will return a Future. The code looks like following.
Here I have one questions:
Inside event_bus consumer, could it run a Async. method? I doubt whether consumer handler supports to run Async. method? In Vertx, I understand Vertilce contains event loop, it supports Async. method, I am not sure if event_bus consumer handler supports it?
EventBus eb = vertx.eventBus();
MessageConsumer<String> consumer = eb.consumer("my_address");
consumer.handler(message -> {
Future<List<DataRecord>> listFuture = async_method_to_access_database();
listFuture.onSuccess(ar->{
doSomething();
});
});
You can have async code in the handler. The important part to understand that you have two ways of sending messages on the eventbus: request/publish.
With publish you just fire-and-forget
And with request you will register a handler wich waits until the consumer answers the message by calling message.reply().
In both cases your async code in the consumer will be executed, but when you use send, you have the option to have additional logic on the sender side, (e.g: repeat on error, validate response, etc)
EventBus eb = vertx.eventBus();
// sender
eb.request("my_address","testmessage", h -> {
if(h.succeeded()){
System.out.println("successful access to db");
}else{
System.out.println(h.cause());
}
});
// consumer
MessageConsumer<String> consumer = eb.consumer("my_address");
consumer.handler(message -> {
Future<List<DataRecord>> listFuture = async_method_to_access_database();
listFuture.onComplete(ar->{
if (ar.succeeded()) {
message.reply("updated elements successfully" + listFuture.size());
}
message.fail(1,"critical error") // will trigger error in sender
});
});
Related
We have a non clustered vertx application, and we use the event bus to internally communicate between verticles.
Verticle A consumes from the bus, performs a HTTP request, and sends the response back through the bus.
Verticle B just request to perform that HTTP request.
The problem appears when a "high" request volume is performed by Verticle B. Then, the consumer starts receiving the events slower and slower (presumably because they are getting queued in the event bus). For 8 requests/second the bus takes up to 3-4 seconds to consume the event. When the requests/second are elevated, it can take more than 30 seconds to consume it, so the bus timeout is triggered.
The thing is, Verticle A is really fast performing the HTTP operation (~200ms) so I don't really understand why the requests get stuck in the bus.
We've tried many solutions but none ot then worked:
Deploy multiple instances of Verticle A as workers
Use vertx.executeBlocking() to perform the HTTP request
The only thing that worked was commenting the HTTP request and returning a mock object through the bus. But again, the HTTP request doesn't take more than 200ms, so it shouldn't be blocking the bus.
Additional information: We use an autogenerated rest client that uses Retrofit + OkHttpClient. Due to company policy, we cannot use Vertx WebClient, so I didn't try this solution.
EXAMPLE
This is a really simplified version of our code so you can check if I'm missing something.
VERTICLE A
// Instantiated in Verticle A
public class EmailSender {
private final Vertx vertx;
private final EmailApiClient emailApiClient;
public EmailSender(Vertx vertx) {
this.vertx = vertx;
emailApiClient = ClientFactory.createEmailApiClient();
}
public void start() {
vertx.eventBus().consumer("sendEmail", this::sendEmail);
}
public void sendEmail(Message<EmailRequest> message) {
EmailRequest emailRequest = message.body();
emailApiClient.sendEmail(emailRequest).subscribe(
response -> {
if (response.code() == 200) {
EmailResponse emailResponse = response.body();
message.reply(emailResponse);
} else {
message.fail(500, "Error sending email");
}
});
}
}
VERTICLE B
// Instantiated in Verticle B
public class EmailCommunications {
private final Vertx vertx;
public EmailCommunications(Vertx vertx) {
this.vertx = vertx;
}
public Single<EmailResponse> sendEmail(EmailRequest emailRequest) {
SingleSubject<EmailResponse> emailSent = SingleSubject.create();
vertx.eventBus().request(
"sendEmail",
emailRequest,
busResult -> {
if (busResult.succeded()) {
emailSent.onSuccess(busResult.result().body())
} else {
emailSent.onError(busResult.cause())
}
}
);
return emailSent;
}
}
We fixed the issue changing our OkHttpClient configuration so HTTP requests won't get stuck
default void configureOkHttpClient(OkHttpClient.Builder okHttpClientBuilder) {
ConnectionPool connectionPool = new ConnectionPool(40, 5, TimeUnit.MINUTES);
Dispatcher dispatcher = new Dispatcher();
dispatcher.setMaxRequestsPerHost(200);
dispatcher.setMaxRequests(200);
okHttpClientBuilder
.readTimeout(60, TimeUnit.SECONDS)
.retryOnConnectionFailure(true)
.connectionPool(connectionPool)
.dispatcher(dispatcher);
}
I am new to netty and trying to understand how the channel future for writeAndFlush works. Consider the following code running on a netty client:
final ChannelFuture writeFuture = abacaChannel.writeAndFlush("Test");
writeFuture.addListener(new ChannelFutureListener() {
#Override
public void operationComplete(ChannelFuture future) throws Exception {
if (writeFuture.isSuccess()) {
LOGGER.debug("Write successful");
} else {
LOGGER.error("Error writing message to Abaca host");
}
}
});
When does this writeFuture operationComplete callback executed?
After netty hands over the data to the OS send buffers (or)
After the OS writes the data to the network socket. (or)
After this data is actually received by the server.
TIA
1. After netty hands over the data to the OS send buffers (or)
Listener will be notified after data is removed from ChannelOutboundBuffer (netty's send buffer)
i've an observable that I create with the following code.
Observable.create(new Observable.OnSubscribe<ReturnType>() {
#Override
public void call(Subscriber<? super ReturnType> subscriber) {
try {
if (!subscriber.isUnsubscribed()) {
subscriber.onNext(performRequest());
}
subscriber.onCompleted();
} catch (Exception e) {
subscriber.onError(e);
}
}
});
performRequest() will perform a long running task as you might expect.
Now, since i might be launching the same Observable twice or more in a very short amount of time, I decided to write such transformer:
protected Observable.Transformer<ReturnType, ReturnType> attachToRunningTaskIfAvailable() {
return origObservable -> {
synchronized (mapOfRunningTasks) {
// If not in maps
if ( ! mapOfRunningTasks.containsKey(getCacheKey()) ) {
Timber.d("Cache miss for %s", getCacheKey());
mapOfRunningTasks.put(
getCacheKey(),
origObservable
.doOnTerminate(() -> {
Timber.d("Removed from tasks %s", getCacheKey());
synchronized (mapOfRunningTasks) {
mapOfRunningTasks.remove(getCacheKey());
}
})
.cache()
);
} else {
Timber.d("Cache Hit for %s", getCacheKey());
}
return mapOfRunningTasks.get(getCacheKey());
}
};
}
Which basically puts the original .cache observable in a HashMap<String, Observable>.
This basically disallows multiple requests with the same getCacheKey() (Example login) to call performRequest() in parallel. Instead, if a second login request arrives while another is in progress, the second request observable gets "discarded" and the already-running will be used instead. => All the calls to onNext are going to be cached and sent to both subscribers actually hitting my backend only once.
Now, suppouse this code:
// Observable loginTask
public void doLogin(Observable<UserInfo> loginTask) {
loginTask.subscribe(
(userInfo) -> {},
(throwable) -> {
if (userWantsToRetry()) {
doLogin(loinTask);
}
}
);
}
Where loginTask was composed with the previous transformer. Well, when an error occurs (might be connectivity) and the userWantsToRetry() then i'll basically re-call the method with the same observable. Unfortunately that has been cached and I'll receive the same error without hitting performRequest() again since the sequence gets replayed.
Is there a way I could have both the "same requests grouping" behavior that the transformer provides me AND the retry button?
Your question has a lot going on and it's hard to put it into direct terms. I can make a couple recommendations though. Firstly your Observable.create can be simplified by using an Observable.defer(Func0<Observable<T>>). This will run the func every time a new subscriber is subscribed and catch and channel any exceptions to the subscriber's onError.
Observable.defer(() -> {
return Observable.just(performRequest());
});
Next, you can use observable.repeatWhen(Func1<Observable<Void>, Observable<?>>) to decide when you want to retry. Repeat operators will re-subscribe to the observable after an onComplete event. This particular overload will send an event to a subject when an onComplete event is received. The function you provide will receive this subject. Your function should call something like takeWhile(predicate) and onComplete when you do not want to retry again.
Observable.just(1,2,3).flatMap((Integer num) -> {
final AtomicInteger tryCount = new AtomicInteger(0);
return Observable.just(num)
.repeatWhen((Observable<? extends Void> notifications) ->
notifications.takeWhile((x) -> num == 2 && tryCount.incrementAndGet() != 3));
})
.subscribe(System.out::println);
Output:
1
2
2
2
3
The above example shows that retries are aloud when the event is not 2 and up to a max of 22 retries. If you switch to a repeatWhen then the flatMap would contain your decision as to use a cached observable or the realWork observable. Hope this helps!
I our application we plan to make wire-tap as Async call but we set some login information in the SecurityContext so if we make wire-tap as Async we will loose this data so we plan to go with the Synch Channel for Wire-tap and in the Interceptor class when we log we call a Thread to log the message in the DB.
What may be the impact with this approach is there any Thread poll limit we need to take care or is there any alternative solution for this?
We are using weblogic 12c
Looks like you should take care about SecurityContext propagation (https://jira.spring.io/browse/INT-2166). Please, read all those comments carefully.
You can add that ChannelInterceptor the channel of your wire-tap and that separate thread will get SecurityContext.
For comprehensive answer I'm adding that interceptor code here:
class SecurityContextPropagationChannelInterceptor extends ChannelInterceptorAdapter {
#Override
Message<?> preSend(Message<?> message, MessageChannel channel) {
if (!(channel in AbstractPollableChannel) || message.headers.securityContext || !SecurityContextHolder.context.authentication) return message
return MessageBuilder.fromMessage(message).with {
setHeader 'securityContext', SecurityContextHolder.context
build()
}
}
#Override
Message<?> postReceive(Message<?> message, MessageChannel channel) {
if (channel in AbstractPollableChannel && message.headers.securityContext) {
SecurityContextHolder.context = message.headers.securityContext
}
return message
}
}
I am using rabbitmq and I want to make sure that if I have a connection problem in the client, the messages that I posted won't be lost. I simulate it with eclipse: I do system.exit the program of fetching after 100 messages. I posted 1000 messages. The second run I don't limit the number of messages and it returns me 840 messages with 3 times. Can you help me?
the code of the producer is:
public void run() {
String json =SimpleQueueServiceSample.getFromList();
while (!(json.equals(""))){
json =SimpleQueueServiceSample.getFromList();
try {
c.basicPublish("", "test",
MessageProperties.PERSISTENT_TEXT_PLAIN, json.getBytes());
} catch (IOException e) {
e.printStackTrace();
}
}
try {
c.waitForConfirmsOrDie();
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
the code of the consumber is:
QueueingConsumer consumer = new QueueingConsumer(channel);
channel.basicConsume(QUEUE_NAME, true, consumer);
while (true) {
System.out.println(count++);
QueueingConsumer.Delivery delivery = consumer.nextDelivery();
String message = new String(delivery.getBody());
System.out.println(" [x] Received '" + message + "'");
}
So the challenge for your scenario is how you're handling the acknowledgements.
channel.basicConsume(QUEUE_NAME, true, consumer);
Is the problem. The second parameter of true is the auto-acknowledge field.
To fix that, use:
channel.basicConsume(QUEUE_NAME, false, consumer);
while (true) {
QueueingConsumer.Delivery delivery = consumer.nextDelivery();
//...
channel.basicAck(delivery.getEnvelope().getDeliveryTag(), false);
}
It looks like you're using RabbitMQ's tutorials, and your code snippet is from part one. If you look at part two, they start talking about acknowledgements and setting up quality of service to provide round-robin dispatch.
It's worth pointing out that the basicConsume() and nextDelivery() combination rely upon a hidden queue that lives within the consumer. So when you call basicConsume() several messages are pulled down to the client to local storage.
The benefit at that approach is that it avoids additional network overhead from calling for each individual message. The problem is that it can put more messages within your local consumer than you wish and you may lose messages if the consumer drops before processing all of the messages in the local hidden queue.
If you truly want your consumers only working on one message a time so that nothing is lost, you probably want to look at the basicGet() method instead of the basicConsume().