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Batch consumer camel kafka

I am unable to read in batch with the kafka camel consumer, despite following an example posted here. Are there changes I need to make to my producer, or is the problem most likely with my consumer configuration?
The application in question utilizes the kafka camel component to ingest messages from a rest endpoint, validate them, and place them on a topic. I then have a separate service that consumes them from the topic and persists them in a time-series database.
The messages were being produced and consumed one at a time, but the database expects the messages to be consumed and committed in batch for optimal performance. Without touching the producer, I tried adjusting the consumer to match the example in the answer to this question:
How to transactionally poll Kafka from Camel?
I wasn't sure how the messages would appear, so for now I'm just logging them:
from(kafkaReadingConsumerEndpoint).routeId("rawReadingsConsumer").process(exchange -> {
// simple approach to generating errors
String body = exchange.getIn().getBody(String.class);
if (body.startsWith("error")) {
throw new RuntimeException("can't handle the message");
}
log.info("BODY:{}", body);
}).process(kafkaOffsetManager);
But the messages still appear to be coming across one at a time with no batch read.
My consumer config is this:
kafka:
host: myhost
port: myport
consumer:
seekTo: beginning
maxPartitionFetchBytes: 55000
maxPollRecords: 50
consumerCount: 1
autoOffsetReset: earliest
autoCommitEnable: false
allowManualCommit: true
breakOnFirstError: true
Does my config need work, or are there changes I need to make to the producer to have this work correctly?

At the lowest layer, the KafkaConsumer#poll method is going to return an Iterator<ConsumerRecord>; there's no way around that.
I don't have in-depth experience with Camel, but in order to get a "batch" of records, you'll need some intermediate collection to "queue" the data that you want to eventually send downstream to some "collection consumer" process. Then you will need some "switch" processor that says "wait, process this batch" or "continue filling this batch".
As far as databases go, that process is exactly what Kafka Connect JDBC Sink does with batch.size config.

We solved a similar requirement by using the Aggregation [1] capability provided by Camel
A rough code snippet
#Override
public void configure() throws Exception {
// 1. Define your Aggregation Strat
AggregationStrategy agg = AggregationStrategies.flexible(String.class)
.accumulateInCollection(ArrayList.class)
.pick(body());
from("kafka:your-topic?and-other-params")
// 2. Define your Aggregation Strat Params
.aggregate(constant(true), agg)
.completionInterval(1000)
.completionSize(100)
.parallelProcessing(true)
// 3. Generate bulk insert statement
.process(exchange -> {
List<String> body = (List<String>) exchange.getIn().getBody();
String query = generateBulkInsertQueryStatement("target-table", body);
exchange.getMessage().setBody(query);
})
.to("jdbc:dataSource");
}
There are a variety of strategies that you can implement, but we chose this particular one because it allows you to create a List of strings for the message contents that we need to ingest into the db. [2]
We set a variety of different params such as completionInterval & completionSize. The most important one for us was to set parallellProcessing(true) [3] ; without that our performance wasn't nearly getting the required throughput.
Once the aggregation has either collected 100 messages or 1000 ms has passed, then the processor generates a bulk insert statement, which then gets sent to the db.
[1] https://camel.apache.org/components/3.18.x/eips/aggregate-eip.html
[2] https://camel.apache.org/components/3.18.x/eips/aggregate-eip.html#_aggregating_into_a_list
[3] https://camel.apache.org/components/3.18.x/eips/aggregate-eip.html#_worker_pools

Spring Cloud Stream - notice and handle errors in broker

I am fairly new to developing distributed applications with messaging, and to Spring Cloud Stream in particular. I am currently wondering about best practices on how to deal with errors on the broker side.
In our application, we need to both consume and produce messages from/to multiple sources/destinations like this:
Consumer side
For consuming, we have defined multiple #Beans of type java.util.function.Consumer. The configuration for those looks like this:
spring.cloud.stream.bindings.consumeA-in-0.destination=inputA
spring.cloud.stream.bindings.consumeA-in-0.group=$Default
spring.cloud.stream.bindings.consumeB-in-0.destination=inputB
spring.cloud.stream.bindings.consumeB-in-0.group=$Default
This part works quite well - wenn starting the application, the exchanges "inputA" and "inputB" as well as the queues "inputA.$Default" and "inputB.$Default" with corresponding binding are automatically created in RabbitMQ.
Also, in case of an error (e.g. a queue is suddenly not available), the application gets notified immediately with a QueuesNotAvailableException and continuously tries to re-establish the connection.
My only question here is: Is there some way to handle this exception in code? Or, what are best practices to deal with failures like this on broker side?
Producer side
This one is more problematic. Producing messages is triggered by some internal logic, we cannot use function #Beans here. Instead, we currently rely on StreamBridge to send messages. The problem is that this approach does not trigger creation of exchanges and queues on startup. So when our code calls streamBridge.send("outputA", message), the message is sent (result is true), but it just disappears into the void since RabbitMQ automatically drops unroutable messages.
I found that with this configuration, I can at least get RabbitMQ to create exchanges and queues as soon as the first message is sent:
spring.cloud.stream.source=produceA;produceB
spring.cloud.stream.default.producer.requiredGroups=$Default
spring.cloud.stream.bindings.produceA-out-0.destination=outputA
spring.cloud.stream.bindings.produceB-out-0.destination=outputB
I need to use streamBridge.send("produceA-out-0", message) in code to make it work, which is not too great since it means having explicit configuration hardcoded, but at least it works.
I also tried to implement the producer in a Reactor style as desribed in this answer, but in this case the exchange/queue also is not created on application startup and the sent message just disappears even though the return status of the sending method is "OK".
Failures on the broker side are not registered at all with this approach - when I simulate one e.g. by deleting the queue or the exchange, it is not registered by the application. Only when another message is sent, I get in the logs:
ERROR 21804 --- [127.0.0.1:32404] o.s.a.r.c.CachingConnectionFactory : Shutdown Signal: channel error; protocol method: #method<channel.close>(reply-code=404, reply-text=NOT_FOUND - no exchange 'produceA-out-0' in vhost '/', class-id=60, method-id=40)
But still, the result of StreamBridge#send was true in this case. But we need to know that sending did actually fail at this point (we persist the state of the sent object using this boolean return value). Is there any way to accomplish that?
Any other suggestions on how to make this producer scenario more robust? Best practices?
EDIT
I found an interesting solution to the producer problem using correlations:
...
CorrelationData correlation = new CorrelationData(UUID.randomUUID().toString());
messageHeaderAccessor.setHeader(AmqpHeaders.PUBLISH_CONFIRM_CORRELATION, correlation);
Message<String> message = MessageBuilder.createMessage(payload, messageHeaderAccessor.getMessageHeaders());
boolean sent = streamBridge.send(channel, message);
try {
final CorrelationData.Confirm confirm = correlation.getFuture().get(30, TimeUnit.SECONDS);
if (correlation.getReturned() == null && confirm.isAck()) {
// success logic
} else {
// failed logic
}
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
// failed logic
} catch (ExecutionException | TimeoutException e) {
// failed logic
}
using these additional configurations:
spring.cloud.stream.rabbit.default.producer.useConfirmHeader=true
spring.rabbitmq.publisher-confirm-type=correlated
spring.rabbitmq.publisher-returns=true
This seems to work quite well, although I'm still clueless about the return value of StreamBridge#send, it is always true and I cannot find information in which cases it would be false. But the rest is fine, I can get information on issues with the exchange or the queue from the correlation or the confirm.
But this solution is very much focused on RabbitMQ, which causes two problems:
our application should be able to connect to different brokers (e.g. Azure Service Bus)
in tests we use Kafka binder and I don't know how to configure the application context to make it work in this case, too
Any help would be appreciated.

On the consumer side, you can listen for an event such as the ListenerContainerConsumerFailedEvent.
https://docs.spring.io/spring-amqp/docs/current/reference/html/#consumer-events
On the producer side, producers only know about exchanges, not any queues bound to them; hence the requiredGroups property which causes the queue to be bound.
You only need spring.cloud.stream.default.producer.requiredGroups=$Default - you can send to arbitrary destinations using the StreamBridge and the infrastructure will be created.
#SpringBootApplication
public class So70769305Application {
public static void main(String[] args) {
SpringApplication.run(So70769305Application.class, args);
}
#Bean
ApplicationRunner runner(StreamBridge bridge) {
return args -> bridge.send("foo", "test");
}
}
spring.cloud.stream.default.producer.requiredGroups=$Default

Http Websocket as Akka Stream Source

I'd like to listen on a websocket using akka streams. That is, I'd like to treat it as nothing but a Source.
However, all official examples treat the websocket connection as a Flow.
My current approach is using the websocketClientFlow in combination with a Source.maybe. This eventually results in the upstream failing due to a TcpIdleTimeoutException, when there are no new Messages being sent down the stream.
Therefore, my question is twofold:
Is there a way – which I obviously missed – to treat a websocket as just a Source?
If using the Flow is the only option, how does one handle the TcpIdleTimeoutException properly? The exception can not be handled by providing a stream supervision strategy. Restarting the source by using a RestartSource doesn't help either, because the source is not the problem.
Update
So I tried two different approaches, setting the idle timeout to 1 second for convenience
application.conf
akka.http.client.idle-timeout = 1s
Using keepAlive (as suggested by Stefano)
Source.<Message>maybe()
.keepAlive(Duration.apply(1, "second"), () -> (Message) TextMessage.create("keepalive"))
.viaMat(Http.get(system).webSocketClientFlow(WebSocketRequest.create(websocketUri)), Keep.right())
{ ... }
When doing this, the Upstream still fails with a TcpIdleTimeoutException.
Using RestartFlow
However, I found out about this approach, using a RestartFlow:
final Flow<Message, Message, NotUsed> restartWebsocketFlow = RestartFlow.withBackoff(
Duration.apply(3, TimeUnit.SECONDS),
Duration.apply(30, TimeUnit.SECONDS),
0.2,
() -> createWebsocketFlow(system, websocketUri)
);
Source.<Message>maybe()
.viaMat(restartWebsocketFlow, Keep.right()) // One can treat this part of the resulting graph as a `Source<Message, NotUsed>`
{ ... }
(...)
private Flow<Message, Message, CompletionStage<WebSocketUpgradeResponse>> createWebsocketFlow(final ActorSystem system, final String websocketUri) {
return Http.get(system).webSocketClientFlow(WebSocketRequest.create(websocketUri));
}
This works in that I can treat the websocket as a Source (although artifically, as explained by Stefano) and keep the tcp connection alive by restarting the websocketClientFlow whenever an Exception occurs.
This doesn't feel like the optimal solution though.

No. WebSocket is a bidirectional channel, and Akka-HTTP therefore models it as a Flow. If in your specific case you care only about one side of the channel, it's up to you to form a Flow with a "muted" side, by using either Flow.fromSinkAndSource(Sink.ignore, mySource) or Flow.fromSinkAndSource(mySink, Source.maybe), depending on the case.
as per the documentation:
Inactive WebSocket connections will be dropped according to the
idle-timeout settings. In case you need to keep inactive connections
alive, you can either tweak your idle-timeout or inject ‘keep-alive’
messages regularly.
There is an ad-hoc combinator to inject keep-alive messages, see the example below and this Akka cookbook recipe. NB: this should happen on the client side.
src.keepAlive(1.second, () => TextMessage.Strict("ping"))

I hope I understand your question correctly. Are you looking for asSourceOf?
path("measurements") {
entity(asSourceOf[Measurement]) { measurements =>
// measurement has type Source[Measurement, NotUsed]
...
}
}

Incompatibility between app instances: prevent rabbitmq to consume messages with particular header

I have two instances of the same java application using spring and rabbitmq.
An instance sends a message to a queue but I can't predict which instance will consume it (as expected).
I updated the java application. For some reasons, the is no compatibility between the old and the new version: the new version can't consume the messages from the old one and vice versa.
We can't offer disruption of service while deploying a new version, so we can't stop both instances at the same time. We have to stop instance A, restart instance A with updates, then stop B and restart it with updates.
When I have the new instance of A and the old instance of B, A cannot consume the messages as expected if they were produced by B.
To solve this, the idea was to add a header to the rabbitmq messages. I created a custom rabbitmq template:
#Override
protected Message convertMessageIfNecessary(final Object object) {
Message message = super.convertMessageIfNecessary(object);
MessageProperties messageProperties = new MessageProperties();
messageProperties.setHeader("version", version);
return new Message(message.getBody(), messageProperties);
}
This adds a new header with the version of the application. Then I would like to check this header before ack a message.
E.g.:
A sends a message with version 4
B receives the message -> does not consume nor ack because B version is 3.
A receives the message -> consumes because A version is 4.
Is such a configuration possible?
I also had a look at #RabbitListener group properties but I am not sure what to do with this.
Thanks for any help

You could do that, but it wouldn't be very efficient. When a B(3) instance rejects the message, there's no guarantee that the redelivery will go to a B(4) instance; while it's likely that will eventually happen, depending on circumstances, it might go to a B(3) many times first.
It's probably easier/better to simply bind a new queue to the exchange; have A(4)s publish to the new queue and B(4)s consume from it while the old B(3)s consume from the old queue.
When all A(3) instances have been undeployed, and all messages consumed from the old queue, remove the last B(3) and delete the queue.

Parse byteBuffer in Websphere MQ Exit

I'm trying to build a custom mq exit to archive messages that hit a queue. I have the following code.
class MyMqExits implements WMQSendExit, WMQReceiveExit{
#Override
public ByteBuffer channelReceiveExit(MQCXP arg0, MQCD arg1, ByteBuffer arg2) {
// TODO Auto-generated method stub
if ( arg2){
def _bytes = arg2.array()
def results = new String(_bytes)
println results;
}
return arg2;
}
...
The content of the message (header/body) is in the byte buffer, along with some unreadable binary information. How can I parse the message (including the body and the queue name) from arg2? We've gone through IBM's documentation, but haven't found an object or anything that makes this easy.

Assuming the following two points:
1) Your sender application has not hard coded the queue name where it puts messages. So you can change the application configuration to send messages to a different object.
2) MessageId of the archived message is not important, only message body is important.
Then one alternative I can think of is to create an Alias queue that resolves to a Topic and use two subscribers to receive messages.
1) Subscriber 1: An administratively defined durable subscriber with a queue provided to receive messages. Provide the same queue name from which your existing consumer application is receiving messages.
2) Subscriber 2: Another administratively defined durable subscriber with queue provided. You can write a simple java application to get messages from this queue and archive.
3) Both subscribers subscribe to the same topic.
Here are steps:
// Create a topic
define topic(ANY.TOPIC) TOPICSTR('/ANY_TOPIC')
// Create an alias queue that points to above created topic
define qalias(QA.APP) target(ANY.TOPIC) targtype(TOPIC)
// Create a queue for your application that does business logic. If one is available already then no need to create.
define ql(Q.BUSLOGIC)
// Create a durable subscription with destination queue as created in previous step.
define sub(SB.BUSLOGIC) topicstr('/ANY_TOPIC') dest(Q.BUSLOGIC)
// Create a queue for application that archives messages.
define ql(Q.ARCHIVE)
// Create another subscription with destination queue as created in previous step.
define sub(SB.ARCHIVE) topicstr('/ANY_TOPIC') dest(Q.ARCHIVE)
Write a simple MQ Java/JMS application to get messages from Q.ARCHIVE and archive messages.

A receive exit is not going to give you the whole message. Send and receive exits operate on the transmission buffers sent/received by channels. These will contain various protocol flows which are not documented because the protocol is not public, and part of those protocol flows will be chunks of the messages broken down to fit into 32Kb chunks.
You don't give enough information in your question for me to know what type of channel you are using, but I'm guessing it's on the client side since you are writing it in Java and that is the only environment where that is applicable.
Writing the exit at the client side, you'll need to be careful you deal with the cases where the message is not successfully put to the target queue, and you'll need to manage syncpoints etc.
If you were using QMgr-QMgr channels, you should use a message exit to capture the MQXR_MSG invocations where the whole message is given to you. If you put any further messages in a channel message exit, the messages you put are included in the channel's Syncpoint and so committed if the original messages were committed.
Since you are using client-QMgr channels, you could look at an API Exit on the QMgr end (currently client side API Exits are only supported for C clients) and catch all the MQPUT calls. This exit would also give you the MQPUT return codes so you could code your exit to look out for, and deal with failed puts.
Of course, writing an exit is a complicated task, so it may be worth finding out if there are any pre-written tools that could do this for you instead of starting from scratch.

I fully agree with Morag & Shashi, wrong approach. There is an open source project called Message Multiplexer (MMX) that will get a message from a queue and output it to one or more queues. Context information is maintained across the message put(s). For more info on MMX go to: http://www.capitalware.com/mmx_overview.html
If you cannot change the source or target queues to insert MMX into the mix then an API Exit may do the trick. Here is a blog posting about message replication via an API Exit: http://www.capitalware.com/rl_blog/?p=3304

This is quite an old question but it's worth replying with an update that's relevant to MQ 9.2.3 or later. There is a new feature called Streaming Queues (see https://www.ibm.com/docs/en/ibm-mq/9.2?topic=scenarios-streaming-queues) and one of the use-cases it is designed to support is putting a copy of every message sent to a given queue, to an alternative queue. Another application can then consume the duplicate messages and archive them separately to the application that is processing the original messages.