I'm trying to inject a KafkaTemplate to send a single message. I'm developing a small function that lies outside the reactive approach.
I can only find examples that use #Ingoing and #Outgoing from Smallrye but I don't need a KafkaStream.
I tried with Kafka-CDI but I'm unable to inject the SimpleKafkaProducer.
Any ideas?
For Clement's answer
It seems the right direction, but executing orders.send("hello"); I receive this error:
(vert.x-eventloop-thread-3) Unhandled exception:java.lang.IllegalStateException: Stream not yet connected
I'm consuming from my topic by command line, Kafka is up and running, if I produce manually I can see the consumed messages.
It seems relative to this sentence by the doc:
To use an Emitter for the stream hello, you need a #Incoming("hello")
somewhere in your code (or in your configuration).
I have this code in my class:
#Incoming("orders")
public CompletionStage<Void> consume(KafkaMessage<String, String> msg) {
log.info("Received message (topic: {}, partition: {}) with key {}: {}", msg.getTopic(), msg.getPartition(), msg.getKey(), msg.getPayload());
return msg.ack();
}
Maybe I've forgotten some configurations?
So, you just need to use an Emitter:
#Inject
#Stream("orders") // Emit on the channel 'orders'
Emitter<String> orders;
// ...
orders.send("hello");
And in your application.properties, declare:
## Orders topic (WRITE)
mp.messaging.outgoing.orders.type=io.smallrye.reactive.messaging.kafka.Kafka
mp.messaging.outgoing.orders.topic=orders
mp.messaging.outgoing.orders.bootstrap.servers=localhost:9092
mp.messaging.outgoing.orders.key.serializer=org.apache.kafka.common.serialization.StringSerializer
mp.messaging.outgoing.orders.value.serializer=org.apache.kafka.common.serialization.StringSerializer
mp.messaging.outgoing.orders.acks=1
To avoid Stream not yet connected exception, as suggested by doc:
To use an Emitter for the stream hello, you need a #Incoming("hello")
somewhere in your code (or in your configuration).
Assuming you have something like this in your application.properties:
# Orders topic (READ)
smallrye.messaging.source.orders-r-topic.type=io.smallrye.reactive.messaging.kafka.Kafka
smallrye.messaging.source.orders-r-topic.topic=orders
smallrye.messaging.source.orders-r-topic.bootstrap.servers=0.0.0.0:9092
smallrye.messaging.source.orders-r-topic.key.deserializer=org.apache.kafka.common.serialization.StringDeserializer
smallrye.messaging.source.orders-r-topic.value.deserializer=org.apache.kafka.common.serialization.StringDeserializer
smallrye.messaging.source.orders-r-topic.group.id=my-group-id
Add something like this:
#Incoming("orders-r-topic")
public CompletionStage<Void> consume(KafkaMessage<String, String> msg) {
log.info("Received message (topic: {}, partition: {}) with key {}: {}", msg.getTopic(), msg.getPartition(), msg.getKey(), msg.getPayload());
return msg.ack();
}
Since Clement's answer the #Stream annotation has been deprecated. The #Channel annotation
must be used instead.
You can use an Emitter provided by the quarkus-smallrye-reactive-messaging-kafka dependency to produce message to a Kafka topic.
A simple Kafka producer implementation:
public class MyKafkaProducer {
#Inject
#Channel("my-topic")
Emitter<String> myEmitter;
public void produce(String message) {
myEmitter.send(message);
}
}
And the following configuration must be added to the application.properties file:
mp.messaging.outgoing.my-topic.connector=smallrye-kafka
mp.messaging.outgoing.my-topic.bootstrap.servers=localhost:9092
mp.messaging.outgoing.my-topic.value.serializer=org.apache.kafka.common.serialization.StringSerializer
This will produce string serialized messages to a kafka topic named my-topic.
Note that by default the name of the channel is also the name of the kafka topic in which the data will be produced. This behavior can be changed through the configuration. The supported configuration attributes are described in the reactive Messaging documentation
Related
I have a spring boot camel app.
I am reading from an incoming Kafka topic queue and running a processor that lookup a new destination topic from the Redis cache. In the processor, I add this as a new camel header.
exchange.getIn().setHeader("destTopic", cachelookupvalue);
LOG.info ("RouterProcessor Dest Topic set to:= {}", exchange.getIn().getHeader("destTopic"));
This seems to work, and the log shows it set.
On returning to the route builder class
public class RouterBuilder extends RouteBuilder {
...
//setup env properties etc
#Override
public void configure() {
from("kafka:" + SRC_TOPIC + "?brokers=" + SRC_BROKER).routeId("myRoute")
.log("Sending message to kafka: ${header.destTopic}" )
.process(processor)
.to("kafka:${header.destTopic}?brokers="+DEST_BROKER) //not working
but
//.to("kafka:webhook-channel_1-P101?brokers="+DEST_BROKER) //this works syntax
If i hardcode the the ${header.destTopic} expression it work but not if i try to use the header in the .to dsl it does not.
The Log .log("Sending message to kafka: ${header.destTopic}" seems to be right topic.
I am not sure if it's a syntax problem or if I'm missing a step.
The error output is
Failed delivery for (MessageId: 972B795CF230E52-0000000000000001 on
ExchangeId: 972B795CF230E52-0000000000000001). Exhausted after
delivery attempt: 1 caught:
org.apache.kafka.common.errors.InvalidTopicException:
${header.destTopic}
Headers , properties and body ..etc are dynamic values in camel so you must use toD(to Dynamic)
.toD("kafka:${headers.destTopic}?brokers="+DEST_BROKER) //not working
I'm using Spring Cloud Stream with Kafka Streams. Let's say I have a processor which is a Function which converts a KStream of Strings to a KStream of CityProgrammes. It invokes an API to find the City by name and an other transformation which finds any events near that city.
Now the problem is that any error happens during the transformation, the whole application stops. I want to send that one particular message to a DLQ and move along. I've been reading for days and everyone suggests to handle errors within the called services but that is a nonesense in my opinion, plus I still need to return a KStream: how do I do that within a catch?
I also looked at UncaughtExeptionHandler but it is not aware of the message and only able to restart the processing which won't skip this invalid message.
This might sound like an A-B problem so the question rephrased: how do I maintain the flow in a KStream when an exception occurs and send the invalid item to the DLQ?
When it comes to the application-level errors you have, it is up to the application itself how the error is handled. Kafka Streams and the Spring Cloud Stream binder mainly support deserialization and serialization errors at the framework level. Although that is the case, I think your scenario can be handled. If you are using Kafka Client prior to 2.8, here is an SO answer I gave before on something similar: https://stackoverflow.com/a/66749750/2070861
If you are using Kafka/Streams 2.8, here is an idea that you can use. However, the code below should only be used as a starting point. Adjust it according to your use case. Read more on how branching works in Kafka Streams 2.8. The branching API is significantly refactored in 2.8 from the prior versions.
public Function<KStream<?, String>, KStream<?, Foo>> convert() {
Foo[] foo = new Foo[0];
return input -> {
final Map<String, ? extends KStream<?, String>> branches =
input.split(Named.as("foo-")).branch((key, value) -> {
try {
foo[0] = new Foo(); // your API call for CitiProgramme converion here, possibly.
return true;
}
catch (Exception e) {
Message<?> message = MessageBuilder.withPayload(value).build();
streamBridge.send("to-my-dlt", message);
return false;
}
}, Branched.as("bar"))
.defaultBranch();
final KStream<?, String> kStream = branches.get("foo-bar");
return kStream.map((key, value) -> new KeyValue<>("", foo[0]));
};
}
}
The default branch is ignored in this code because that only contains the records that threw exceptions. Those were handled by the catch statement above in which we send the records to a DLT programmatically. Finally, we get the good records and map them to a new KStream and send it through the outbound.
I am implementing POC of request/reply scenario in order to move event-based microservice stack with using Kafka.
There is 2 options in spring.
I wonder which one is better to use. ReplyingKafkaTemplate or cloud-stream
First is ReplyingKafkaTemplate which can be easily configured to have dedicated channel to reply topics for each instance.
record.headers().add(new RecordHeader(KafkaHeaders.REPLY_TOPIC, provider.getReplyChannelName().getBytes()));
Consumer should not need to know replying topic name, just listens a topic and returns with given reply topic.
#KafkaListener(topics = "${kafka.topic.concat-request}")
#SendTo
public ConcatReply listen(ConcatModel request) {
.....
}
Second option is using combination of StreamListener, spring-integration and IntegrationFlows. Gateway should be configured and reply topics should be filtered.
#MessagingGateway
public interface StreamGateway {
#Gateway(requestChannel = START, replyChannel = FILTER, replyTimeout = 5000, requestTimeout = 2000)
String process(String payload);
}
#Bean
public IntegrationFlow headerEnricherFlow() {
return IntegrationFlows.from(START)
.enrichHeaders(HeaderEnricherSpec::headerChannelsToString)
.enrichHeaders(headerEnricherSpec -> headerEnricherSpec.header(Channels.INSTANCE_ID ,instanceUUID))
.channel(Channels.REQUEST)
.get();
}
#Bean
public IntegrationFlow replyFiltererFlow() {
return IntegrationFlows.from(GatewayChannels.REPLY)
.filter(Message.class, message -> Channels.INSTANCE_ID.equals(message.getHeaders().get("instanceId")) )
.channel(FILTER)
.get();
}
Building reply
#StreamListener(Channels.REQUEST)
#SendTo(Channels.REPLY)
public Message<?> process(Message<String> request) {
Specifying reply channel is mandatory. So receieved reply topics are filtered according to instanceID which a kind of workaround (might bloat up the network). On the other hand, DLQ scenario is enabled with adding
consumer:
enableDlq: true
Using spring cloud streams looks promising in terms of interoperability with RabbitMQ and other features, but not officially supports request reply scenario right away. Issue is still open, not rejected also. (https://github.com/spring-cloud/spring-cloud-stream/issues/1800)
Any suggestions are welcomed.
Spring Cloud Stream is not designed for request/reply; it can be done, it is not straightforward and you have to write code.
With #KafkaListener the framework takes care of everything for you.
If you want it to work with RabbitMQ too, you can annotate it with #RabbitListener as well.
I am trying to create an aggregator wherein I listen for multiple records and consolidate them into one. After consolidation, I wait for a process event by joining a stream and aggregated application in listen() method. On arrival of the process event, some business logic is triggered. I have defined both aggregator and process listener in a single spring boot project.
#Bean
public Function<KStream<FormUUID, FormData>, KStream<UUID, Application>> process()
{
return formEvent -> formEvent.groupByKey()
.reduce((k, v) -> v)
.toStream()
.selectKey((k, v) -> k.getReferenceNo())
.groupByKey()
.aggregate(Application::new, (key, value, aggr) -> aggr.performAggregate(value),
Materialized.<UUID, Application, KeyValueStore<Bytes, byte[]>> as("appStore")
.withKeySerde(new JsonSerde<>(UUID.class))
.withValueSerde(new JsonSerde<>(Application.class)))
.toStream();
}
#Bean
public BiConsumer<KStream<String, ProcessEvent>, KTable<String, Application>> listen()
{
return (eventStream, appTable) ->
{
eventStream.join(appTable, (event, app) -> app)
.foreach((k, app) -> app.createQuote());
};
}
However, now I am facing SerializationException. The first part(aggregation) works fine however the join is failing with exception
java.lang.ClassCastException: com.xxxxx.datamapper.domain.FormData cannot be cast to com.xxxxx.datamapper.domain.Application
at org.apache.kafka.streams.kstream.internals.KStreamPeek$KStreamPeekProcessor.process(KStreamPeek.java:42) ~[kafka-streams-2.3.1.jar:?]
at org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:117) ~[kafka-streams-2.3.1.jar:?]
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:201) ~[kafka-streams-2.3.1.jar:?]
at org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:180) ~[kafka-streams-2.3.1.jar:?]
org.apache.kafka.streams.errors.ProcessorStateException: task [0_0] Failed to flush state store APPLICATION_TOPIC-STATE-STORE-0000000001
at org.apache.kafka.streams.processor.internals.ProcessorStateManager.flush(ProcessorStateManager.java:280) ~[kafka-streams-2.3.1.jar:?]
at org.apache.kafka.streams.processor.internals.AbstractTask.flushState(AbstractTask.java:204) ~[kafka-streams-2.3.1.jar:?]
at org.apache.kafka.streams.processor.internals.StreamTask.flushState(StreamTask.java:519) ~[kafka-streams-2.3.1.jar:?]
I think, the problem is in my application.yml. Since the "spring.json.key.default.type" property is set as FormUUID the same is being used for Application object present in listen method. I want to configure the type for remaining types UUID, Application and ProcessEvent in my application.yml. but not sure how to configure the mapping type for each consumer and producer defined.
spring.cloud:
function.definition: process;listen
stream:
kafka.streams:
bindings:
process-in-0.consumer.application-id: form-aggregator
listen-in-0.consumer.application-id: event-processor
listen-in-1.consumer.application-id: event-processor
binder.configuration:
default.key.serde: org.springframework.kafka.support.serializer.JsonSerde
default.value.serde: org.springframework.kafka.support.serializer.JsonSerde
spring.json.key.default.type: com.xxxx.datamapper.domain.FormUUID
spring.json.value.default.type: com.xxxx.datamapper.domain.FormData
commit.interval.ms: 1000
bindings:
process-in-0.destination: FORM_DATA_TOPIC
process-out-0.destination: APPLICATION_TOPIC
listen-in-0.destination: PROCESS_TOPIC
listen-in-1:
destination: APPLICATION_TOPIC
consumer:
useNativeDecoding: true
If you are using the latest Horsham versions of Spring Cloud Stream Kafka Streams binder, you do not need to set any explicit Serdes for inbound and outbound. However, you still need to provide them wherever the Kafka Streams API requires them, as in the case of your aggregate method call above. If you are facing this serialization error on the inbound of the second processor, I suggest trying to remove all Serdes from the configuration. You can simplify as it below (given that you are on the latest Horsham release). The binder will infer the correct Serdes to use on the inbound/outbound. One benefit of delegating this to the binder is that you don't need to provide any explicit key/value types through configuration because the binder will introspect for the types. Make sure your POJO types that you are using are JSON friendly. See if that works. If you are still having issues, please create a small sample application where we can reproduce the issue and we will take a look.
spring.cloud:
function.definition: process;listen
stream:
kafka.streams:
bindings:
process-in-0.consumer.application-id: form-aggregator
listen-in-0.consumer.application-id: event-processor
listen-in-1.consumer.application-id: event-processor
binder.configuration:
commit.interval.ms: 1000
bindings:
process-in-0.destination: FORM_DATA_TOPIC
process-out-0.destination: APPLICATION_TOPIC
listen-in-0.destination: PROCESS_TOPIC
listen-in-1.destination: APPLICATION_TOPIC
Assuming a Record entity, CreateRecord command and a RecordCreated event. I want to invoke some command on one or more other entities (in different modules). What would be the suggested approach to achieve this?
I was thinking about sending a message from the ReadSide handler of the Record entity, which could be received by corresponding service(s), which would convert it to a command and invoke on an entity.
EDIT, thanks #ignasi35: According to Message Broker API publishing of the messages could be possible with this code.
AggregateEventTag<RecordEvent> RECORD_EVENT_TAG = AggregateEventTag.of(RecordEvent.class);
public Topic<RecordMessage> recordsTopic() {
return TopicProducer.singleStreamWithOffset(offset -> {
return persistentEntityRegistry
.eventStream(RECORD_EVENT_TAG, offset)
.map(this::convertEventToRecordMessage);
});
}
Records are created, and corresponding events are persisted, but no messages are received by the following consumer:
#Singleton
public class RecordsConsumer {
#Inject
public RecordsConsumer(RecordService recordService){
recordService.recordsTopic().subscribe()
.atLeastOnce(Flow.fromFunction(this::displayMessage));
}
}
What am I doing wrong?
Finally solved it.
I ended up with a singleton service listening to RecordCreated events from PersistentEntityRegistry.eventStream. The service converts them to RecordMessage and exposes as a Topic (see my question above).
The issue with not receiving any enents from the exposed Topic was missing dependency to kafka-broker (strange that there was no warning about this, and the topic was just not exposed), in my case this was:
<dependency>
<groupId>com.lightbend.lagom</groupId>
<artifactId>lagom-javadsl-kafka-broker_2.12</artifactId>
</dependency>