I am trying to do a simple POC with Kafka Streams. However I am getting exception while starting the application. I am using Spring-Kafka, Kafka-Streams 2.5.1 with Spring boot 2.3.5 Kafka stream configuration
@Configuration
public class KafkaStreamsConfig {
private static final Logger log = LoggerFactory.getLogger(KafkaStreamsConfig.class);
@Bean
public Function<KStream<String, String>, KStream<String, String>> processAAA() {
return input -> input.peek((key, value) -> log
.info("AAA Cloud Stream Kafka Stream processing : {}", input.toString().length()));
}
@Bean
public Function<KStream<String, String>, KStream<String, String>> processBBB() {
return input -> input.peek((key, value) -> log
.info("BBB Cloud Stream Kafka Stream processing : {}", input.toString().length()));
}
@Bean
public Function<KStream<String, String>, KStream<String, String>> processCCC() {
return input -> input.peek((key, value) -> log
.info("CCC Cloud Stream Kafka Stream processing : {}", input.toString().length()));
}
/*
@Bean
public KafkaStreams kafkaStreams(KafkaProperties kafkaProperties) {
final Properties props = new Properties();
props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, kafkaProperties.getBootstrapServers());
props.put(StreamsConfig.APPLICATION_ID_CONFIG, "groupId-1"););
props.put(StreamsConfig.PROCESSING_GUARANTEE_CONFIG, StreamsConfig.EXACTLY_ONCE);
props.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
props.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, JsonSerde.class);
props.put(JsonDeserializer.VALUE_DEFAULT_TYPE, JsonNode.class);
final KafkaStreams kafkaStreams = new KafkaStreams(kafkaStreamTopology(), props);
kafkaStreams.start();
return kafkaStreams;
}
@Bean
public Topology kafkaStreamTopology() {
final StreamsBuilder streamsBuilder = new StreamsBuilder();
streamsBuilder.stream(Arrays.asList(AAATOPIC, BBBInputTOPIC, CCCInputTOPIC));
return streamsBuilder.build();
} */
}
application.yaml configured is like below. The idea is that I have 3 input and 3 output topics. The component takes input from input topic and gives output to outputtopic.
spring:
application.name: consumerapp-1
cloud:
function:
definition: processAAA;processBBB;processCCC
stream:
kafka.binder:
brokers: 127.0.0.1:9092
autoCreateTopics: true
auto-add-partitions: true
kafka.streams.binder:
configuration:
commit.interval.ms: 1000
default.key.serde: org.apache.kafka.common.serialization.Serdes$StringSerde
default.value.serde: org.apache.kafka.common.serialization.Serdes$StringSerde
bindings:
processAAA-in-0:
destination: aaaInputTopic
processAAA-out-0:
destination: aaaOutputTopic
processBBB-in-0:
destination: bbbInputTopic
processBBB-out-0:
destination: bbbOutputTopic
processCCC-in-0:
destination: cccInputTopic
processCCC-out-0:
destination: cccOutputTopic
Exception thrown is
Caused by: java.lang.IllegalArgumentException: Trying to prepareConsumerBinding public abstract void org.apache.kafka.streams.kstream.KStream.to(java.lang.String,org.apache.kafka.streams.kstream.Produced) but no delegate has been set.
at org.springframework.util.Assert.notNull(Assert.java:201)
at org.springframework.cloud.stream.binder.kafka.streams.KStreamBoundElementFactory$KStreamWrapperHandler.invoke(KStreamBoundElementFactory.java:134)
Can anyone help me with Kafka Streams Spring-Kafka code samples for processing with multiple input and output topics.
Updates: 21-Jan-2021
After removing all kafkaStreams and kafkaStreamsTopology beans configuration iam getting below message in an infinite loop. The messages consumption is still not working. I have checked the subscription in application.yaml with the @Bean Function definitions. they all look ok to me but still I get this cross wiring error. I have replaced the application.properties with application.yaml above
[consumerapp-1-75eec5e5-2772-4999-acf2-e9ef1e69f100-StreamThread-1] [Consumer clientId=consumerapp-1-75eec5e5-2772-4999-acf2-e9ef1e69f100-StreamThread-1-consumer, groupId=consumerapp-1] We received an assignment [cccParserTopic-0] that doesn't match our current subscription Subscribe(bbbParserTopic); it is likely that the subscription has changed since we joined the group. Will try re-join the group with current subscription
2021-01-21 14:12:43,336 WARN org.apache.kafka.clients.consumer.internals.ConsumerCoordinator [consumerapp-1-75eec5e5-2772-4999-acf2-e9ef1e69f100-StreamThread-1] [Consumer clientId=consumerapp-1-75eec5e5-2772-4999-acf2-e9ef1e69f100-StreamThread-1-consumer, groupId=consumerapp-1] We received an assignment [cccParserTopic-0] that doesn't match our current subscription Subscribe(bbbParserTopic); it is likely that the subscription has changed since we joined the group. Will try re-join the group with current subscription
I have managed to solve the problem. I am writing this for the benefit of others. If you want to include multiple streams in your single app jar then the key is in defining multiple application Ids that is one per each of your streams. I knew this all along but I was not aware on how to define it. Finally the answer is something I have managed to dig out after reading the SCSt documentation. Below is how the application.yaml can be defined. application.yaml is like below
spring:
application.name: kafkaMultiStreamConsumer
cloud:
function:
definition: processAAA; processBBB; processCCC --> // needed for Imperative @StreamListener
stream:
kafka:
binder:
brokers: 127.0.0.1:9092
min-partition-count: 3
replication-factor: 2
transaction:
transaction-id-prefix: transaction-id-2000
autoCreateTopics: true
auto-add-partitions: true
streams:
binder:
functions:
// needed for functional
processBBB:
application-id: SampleBBBapplication
processAAA:
application-id: SampleAAAapplication
processCCC:
application-id: SampleCCCapplication
configuration:
commit.interval.ms: 1000
default.key.serde: org.apache.kafka.common.serialization.Serdes$StringSerde
default.value.serde: org.apache.kafka.common.serialization.Serdes$StringSerde
bindings:
// Below is for Imperative Style programming using
// the annotation namely @StreamListener, @SendTo in .java class
inputAAA:
destination: aaaInputTopic
outputAAA:
destination: aaaOutputTopic
inputBBB:
destination: bbbInputTopic
outputBBB:
destination: bbbOutputTopic
inputCCC:
destination: cccInputTopic
outputCCC:
destination: cccOutputTopic
// Functional Style programming using Function<KStream...> use either one of them
// as both are not required. If you use both its ok but only one of them works
// from what i have seen @StreamListener is triggered always.
// Below is from functional style
processAAA-in-0:
destination: aaaInputTopic
group: processAAA-group
processAAA-out-0:
destination: aaaOutputTopic
group: processAAA-group
processBBB-in-0:
destination: bbbInputTopic
group: processBBB-group
processBBB-out-0:
destination: bbbOutputTopic
group: processBBB-group
processCCC-in-0:
destination: cccInputTopic
group: processCCC-group
processCCC-out-0:
destination: cccOutputTopic
group: processCCC-group
Once above is defined we now need to define individual java classes where the Stream processing logic is implemented. Your Java class can be something like below. Create similarly for other 2 or N streams as per your requirement. One example is like below : AAASampleStreamTask.java
@Component
@EnableBinding(AAASampleChannel.class) // One Channel interface corresponding to in-topic and out-topic
public class AAASampleStreamTask {
private static final Logger log = LoggerFactory.getLogger(AAASampleStreamTask.class);
@StreamListener(AAASampleChannel.INPUT)
@SendTo(AAASampleChannel.OUTPUT)
public KStream<String, String> processAAA(KStream<String, String> input) {
input.foreach((key, value) -> log.info("Annotation AAA *Sample* Cloud Stream Kafka Stream processing {}", String.valueOf(System.currentTimeMillis())));
...
// do other business logic
...
return input;
}
/**
* Use above or below. Below style is latest startting from ScSt 3.0 if iam not
* wrong. 2 different styles of consuming Kafka Streams using SCSt. If we have
* both then above gets priority as per my observation
*/
/*
@Bean
public Function<KStream<String, String>, KStream<String, String>> processAAA() {
return input -> input.peek((key, value) -> log.info(
"Functional AAA *Sample* Cloud Stream Kafka Stream processing : {}", String.valueOf(System.currentTimeMillis())));
...
// do other business logic
...
}
*/
}
The Channel is required if you want to go with Imperative style programming not for functional. AAASampleChannel.java
public interface AAASampleChannel {
String INPUT = "inputAAA";
String OUTPUT = "outputAAA";
@Input(INPUT)
KStream<String, String> inputAAA();
@Output(OUTPUT)
KStream<String, String> outputAAA();
}