In my Spring Boot/Kafka project I have the following listener:
#KafkaListener(topics = "${kafka.topic.update}", containerFactory = "updateKafkaListenerContainerFactory")
public void onUpdateReceived(ConsumerRecord<String, Update> consumerRecord, Acknowledgment ack) {
// do some logic
ack.acknowledge();
}
Inside of the listener I need to check some condition according to my business logic and if it is not met - skip processing of this certain message and let Kafka know to redeliver this message one more time.
The reason I need this - according to the business logic of my application I need to avoid sending more than one post per second into the particular Telegram chat. This why I'd like to check the chatLastSent time in the Kafka listener and postpone message sending if needed(via message redelivery to this Kafka topic)
How to properly do it? Do I only need to not perform the ack.acknowledge(); this time or there is another, more proper way in order to achieve it?
Use the SeekToCurrentErrorHandler.
When you throw an exception, the container will invoke the error handler which will re-seek the unprocessed messages so they will be fetched again on the next poll.
You can use a RecordFilterStrategy.
See doc here : https://docs.spring.io/spring-kafka/docs/2.0.5.RELEASE/reference/html/_reference.html#_filtering_messages
Related
We have implemented sqslistner as the documentation suggests, the best way to receive AWS SQS message Cloud Spring Doc.
There are two ways for receiving SQS messages, either use the receive
methods of the QueueMessagingTemplate or with annotation-driven
listener endpoints. The latter is by far the more convenient way to
receive messages.
Everything is working as expected. If business process failed, we throw a runtime exception. The particular message is sent back to the SQS queue for retry. When visibility timeout passed the message reappears to the worker for processing.
Sample Code is here:
#SqsListener(value="sample-standard-queue",deletionPolicy = SqsMessageDeletionPolicy.ON_SUCCESS)
public void receiveMessage(String message) {
log.info("Message Received **************************** "+message );
log.info("After Conversion"+new JSONObject(message).getString("payload"));
throw new RuntimeException("An exception was thrown during the execution of the SQS listener method and Message will be still available in Queue");
}
But there are some examples where "Acknowledgment" is used instead of throwing run time exception. Documentation doesn't suggest that.
Which one is the best way to deal with a business logic failure scenario?Is Acknowledgment necessary?
Thanks in advance.
One way is to keep a track of messages being processed in some RDS table. If any message gets retried then increase the retry count in the table for that particular message.
There should be some configured numbers of retries that you want to retry one particular message and then you may want to move that to a dead-letter-queue or you may log it and just simply discard it.
There can be multiple ways of handling it: One way can be:
#SqsListener(value="sample-standard-queue",deletionPolicy = SqsMessageDeletionPolicy.ON_SUCCESS)
public void receiveMessage(String message) {
try{
log.info("Message Received **************************** "+message );
log.info("After Conversion"+new JSONObject(message).getString("payload"));
}catch(Exception e){
// check if its retry count has exhausted or not
// if exhausted - then acknowledge it (push it into dead-letter-queue) and dont throw the exception
// If not exhausted - increase the retry count in the table before throwing exception
throw new RuntimeException("An exception was thrown during the execution of the SQS listener method and Message will be still available in Queue");
}
}
I have jms message endpoint like:
#Bean
public JmsMessageDrivenEndpoint fsJmsMessageDrivenEndpoint(ConnectionFactory fsConnectionFactory,
Destination fsInboundDestination,
MessageConverter fsMessageConverter) {
return Jms.messageDrivenChannelAdapter(fsConnectionFactory)
.destination(fsInboundDestination)
.jmsMessageConverter(fsMessageConverter)
.outputChannel("fsChannelRouter.input")
.errorChannel("fsErrorChannel.input")
.get();
}
So, my questions is did I get next message before current message will be processed? If it will...Did it will get all messages in mq queue until it fills up all the memory? How to avoid it?
The JmsMessageDrivenEndpoint is based on the JmsMessageListenerContainer, its threading model and MessageListener callback for pulled messages. As long as your MessageListener blocks, it doesn't go to the next message in the queue to pull. When we build an integration flow starting with JmsMessageDrivenEndpoint, it becomes as a MessageListener callback. As long as we process the message downstream in the same thread (DirectChannel by default in between endpoints), we don't pull the next message from JMS queue. If you place a QueueChannel or an ExecutorChannel in between, you shift a processing to a different thread. The current one (JMS listener) gets a control back and it is ready to pull the next message. And in this case your concern about the memory is correct. You can still use QueueChannel with limited size or your ExecutorChannel can be configured with limited thread pool.
In any way my recommendation do not do any thread shifting in the flow when you start from JMS listener container. It is better to block for the next message and let the current transaction to finish its job. So you won't lose a message when something crashes.
Case
Clients are ReplyingKafkaTemplate instances.
Server is a ConcurrentMessageListenerContainer created using #KafkaListener and #SendTo annotations on a method.
ContainerFactory uses ContainerStoppingErrorHandler.
Request topic has only 1 partition.
Group ids are static. eg. test-consumer-group.
Requests are sent with timeouts.
Due to an exception thrown, server goes down
but the client keeps dispatching requests which queue up on the
request topic.
Current Behavior
When the server comes back up it continues processing old requests which would have timed out.
Desired Behavior
Instead, it would be better to continue with the last message; thereby skipping past even unprocessed messages as corresponding requests would timeout and retry.
Questions
What is the recommended approach to achieve this?
From the little that I understand, it looks like I'll have to manually set the initial offset. What's the simplest way to implement this?
Your #KafkaListener class must extends AbstractConsumerSeekAware and do something like this:
#Override
public void onPartitionsAssigned(Map<TopicPartition, Long> assignments, ConsumerSeekCallback callback) {
super.onPartitionsAssigned(assignments, callback);
callback.seekToEnd(assignments.keySet());
}
So, every time when your consumer joins the group it is going to seek all the assigned partitions to the end skipping all the old records.
In a spring boot application, I have a class with jms listener.
public class PaymentNotification{
#JmsListener(destination="payment")
public void receive(String payload) throws Exception{
//mapstring conversion
....
paymentEvent = billingService.insert(paymentEvent); //transactional method
//call rest...
billingService.save(paymentEvent);
//send info to jms
}
}
I saw then when a error happen, data is inserted in the database, that ok, but it's like receive method is called again and again... but queue is empty when I check on the server.
If there is an error, I don't want method is called again, Is there something for that.
The JMS Message Headers might contain additional information to help with your processing. In particular JMSRedelivered could be of some value. The Oracle doc states that "If a client receives a message with the JMSRedelivered field set, it is likely, but not guaranteed, that this message was delivered earlier but that its receipt was not acknowledged at that time."
I ran the following code to explore what was available in my configuration (Spring Boot with IBM MQ).
#JmsListener(destination="DEV.QUEUE.1")
public void receive(Message message) throws Exception{
for (Enumeration<String> e = message.getPropertyNames(); e.hasMoreElements();)
System.out.println(e.nextElement());
}
From here I could find JMSXDeliveryCount is available in JMS 2.0. If that property is not available, then you may well find something similar for your own configuration.
One strategy would be to use JMSXDeliveryCount, a vendor specific property or maybe JMSRedelivered (if suitable for your needs) as a way to check before you process the message. Typically, the message would be sent to a specific blackout queue where the redelivery count exceeds a set threshold.
Depending on the messaging provider you are using it might also be possible to configure back out queue processing as properties of the queue.
I am trying to consume multiple message from a topic with manual ack but ack work if all message only by ack one time.
#KafkaListener(
id = "${kafka.buyers.product-sales-pricing.id}",
topics = "${kafka.buyers.product-sales-pricing.topic}",
groupId = "${kafka.buyers.group-id}",
concurrency = "${kafka.buyers.concurrency}"
)
public void listen( List<String> message, Acknowledgment ack ){}
In above code i am getting 5 message per consume if i put following configuration in spring boot property file:
kafka:
max-poll-records: 5 # Maximum number of records returned in a single call to poll()
but if i ack that listen then it ack all 5 message at same time.
Actually i want to ack separately for each message(means 5 message with 5 ack).
How can i do this in spring boot project?
When using a batch listener, the entire batch is acked when Acknowledgment.acknowledge() is called.
I would recommend using a single record listener rather than a batch listener for this use case.
listen(String msg, Acknowledgment ack)
It's not clear why you would commit offsets for only part of the batch.
If you must use a batch listener, it can still be done, but rather more complicated - you would need to get List<ConsumerRecord<?, ?>> to get topic/partition/offset information and also add Consumer<?, ?> consumer to the method parameters (and remove the Acknowledgment; you can then call commitOffsets() on the consumer however you want. But you MUST call it on the listener thread - the consumer is not thread-safe.