Actually i have a springboot based micro-service , and i have used kafka to produce/consume data from different system.
Now my question is i have two different topics and based on topics i have two different consumer classes to consume data,
how to define multiple consumer properties in application.yml file ?
I configured for one consumer in application.yml like below :-
spring:
kafka:
consumer:
bootstrapservers: http://199.968.98.101:9092
group-id: groupid-QA-02
auto-offset-reset: latest
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
I am using #KafkaListener in my consumer classes
example of consumer method which i used in code
#KafkaListener(topics = "${app.topic.b2b_tf_ta_req}", groupId = "${app.topic.groupoId}")
public void consume(String message) throws Exception {
}
As far as I know bootstrap-servers accept comma separated list of servers
i.e. if you set it to server1:9092,server2:9092 kafka should connect to all of them
Related
I am new to KAFKA and would like help
I have 2 applications (springboot), they are identical/copies only with different ports.
http://localhost:8080/
http://localhost:8081/
They are both consumers
the two listen to the topic XXX
I have another APP that plays the role of producer.
whenever I send something to topic XXX.
only one of them consumes the message and the other does not.
I have tested both individually and they listen normally if they are listening alone, but if they are listening together only one of them will listen.
I'm using
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-stream-binder-kafka</artifactId>
<version>3.0.0.RELEASE</version>
</dependency>
spring.cloud.stream.kafka.binder.autoCreateTopics=true
spring.cloud.stream.kafka.binder.headers=type
spring.cloud.stream.kafka.default.consumer.ackEachRecord=true
spring.cloud.stream.kafka.default.consumer.enableDlq=true
spring.cloud.stream.kafka.default.consumer.standardHeaders=both
spring.cloud.stream.kafka.default.consumer.dlqName=api***.d**.api***
my listener
#StreamListener(target=SomeString.TOPIC, condition = "headers['type']=='***' or headers['type']=='***'")
public void handle(GenericMessage<String> message) throws BusinessException {
***
}
The Apache Kafka Binder implementation maps each destination to an
Apache Kafka topic. The consumer group maps directly to the same
Apache Kafka concept. Partitioning also maps directly to Apache Kafka
partitions as well.
check kafka consumer group behavior -> https://kafka.apache.org/documentation/#consumerconfigs_group.id
if kafka consumers have same groupId just one of listen message, you should give them different groupId
app in 8080 -> spring.cloud.stream.bindings.<channelName>.group=consumer-group-1
app in 8081 -> spring.cloud.stream.bindings.<channelName>.group=consumer-group-2
Need some help in integrating kafka with spring cloud stream. The application is very simple, with 2 parts(run as separate java processes)
A consumer- puts request into RequestTopic and gets response from ResponseTopic
A producer- gets the request from the RequestTopic and puts the response back in ResponseTopic.
I have created RequestSenderChannel and ResponseReceiverChannel interfaces for consumer and RequestReceiverChannel and ResponseSenderChannel
for the producer application. both of them share the same yaml file.
As per the documentation spring.cloud.stream.bindings..destination should specify the topic to which the message is sent or received.
But when i run the application, the application creates topics as 'RequestSender', 'RequestReceiver', 'ResponseSender' and 'ResponseReceiver' in the kafka
My assumption was: since destination in the YAML file specifies only two topics 'RequestTopic' and 'ResponseTopic', it should have created those topics.
but it creates Kafka topics for attributes specified at 'spring.cloud.stream.bindings' in the YAML file.
can someone please point out the issue in the configruation/code?
public interface RequestReceiverChannel
{
String requestReceiver ="RequestReceiver";
#Input(requestReceiver)
SubscribableChannel pathQueryRequest();
}
public interface RequestSenderChannel
{
String RequestSender ="RequestSender";
#Output(RequestSender)
MessageChannel pathQueryRequestSender();
}
public interface ResponseReceiverChannel
{
String ResponseReceiver = "ResponseReceiver";
#Input(ResponseReceiver)
SubscribableChannel pceResponseServiceReceiver();
}
public interface ResponseSenderChannel
{
String ResponseSender = "ResponseSender";
#Output(ResponseSender)
MessageChannel pceResponseService();
}
'''
The YAML configuration file
spring:
cloud:
stream:
defaultBinder: kafka
bindings:
RequestSender:
binder: kafka
destination: RequestTopic
content-type: application/protobuf
group: consumergroup
ResponseSender:
binder: kafka
destination: ResponseTopic
content-type: application/protobuf
group: consumergroup
RequestReceiver:
binder: kafka
destination: RequestTopic
content-type: application/protobuf
group: consumergroup
ResponseReceiver:
binder: kafka
destination: ResponseTopic
content-type: application/protobuf
group: consumergroup
kafka:
bindings:
RequestTopic:
consumer:
autoCommitOffset: false
ResponseTopic:
consumer:
autoCommitOffset: false
binder:
brokers: ${SERVICE_KAFKA_HOST:localhost}
zkNodes: ${SERVICE_ZOOKEEPER_HOST:127.0.0.1}
defaultZkPort: ${SERVICE_ZOOKEEPER_PORT:2181}
defaultBrokerPort: ${SERVICE_KAFKA_PORT:9092}
By doing spring.cloud.stream.bindings.<binding-name>.destination=foo you are expressing desire to map binding specified by <binding-name> (e.g., RequestSender) to a broker destination named foo. If such destination does not exist it will be auto-provisioned.
So there are no issues.
That said, we've just released Horsham.RELEASE (part of cloud Hoxton.RELEASE) and we are moving away from annotation-based model you are currently using in favor of a significantly simpler functional model. You can read more about it in our release blog which also provides links to 4 posts where we elaborate and provide more examples on functional programming paradigm.
Working with kafka version: 2.0.1 & kafka-streams-scala version 2.0.1
Log DEBUG messages such as:
DEBUG 2019-05-08 09:57:53,322 [he.kafka.clients.NetworkClient] [
] [ ]: [Consumer
clientId=XXX-bd6b071d-a44f-4253-a3a5-539d60a72dd3-StreamThread-1-consumer,
groupId=XXX] Disconnecting from node YYY due to request
timeout."
led me to increase the request.timeout.ms value:
private val config: Properties = new Properties
config.put(StreamsConfig.REQUEST_TIMEOUT_MS_CONFIG, "240000")
...
private val streams: KafkaStreams = new KafkaStreams(topology, config)
However, this sets the new value to 240000ms for both the AdminClientConfig and the ConsumerConfig (The default request.timeout.ms values for AdminClientConfig and the ConsumerConfig are actually different -- 120000ms and 40000ms respectively).
Is there any way to set the Kafka Streams configuration values for either the AdminClientConfig or the ConsumerConfig without overriding the values of both?
You can prefix any config with consumer. or admin. to apply it to only one client.
There is also main.consumer., restore.consumer. and global.consumer. to distinguish the different consumers further. Using consumer. as prefix, the config is applied to all consumers.
Finally, there is also producer. prefix (just mention it for completeness).
Compare the docs: https://docs.confluent.io/current/streams/developer-guide/config-streams.html#naming
I'm trying to implement Kafka consumer with topic names as a pattern. E.g. #KafkaListener(topicPattern="${kafka.topics}") where property kafka.topics is 'sss.*'. Now when I send message to topic 'sss.test' or any other topic name like 'sss.xyz', 'sss.pqr', it's throwing error as below:
WARN o.apache.kafka.clients.NetworkClient - Error while fetching metadata with correlation id 12 : {sss.xyz-topic=LEADER_NOT_AVAILABLE}
I tried to enable listeners & advertised.listeners in the server.properties file but when I re-start Kafka it consumes messages from all old topics which were tried. The moment I use new topic name, it throws above error.
Kafka doesn't support pattern matching? Or there's some configuration which I'm missing? Please suggest.
I am using kafka with flink.
In a simple program, I used flinks FlinkKafkaConsumer09, assigned the group id to it.
According to Kafka's behavior, when I run 2 consumers on the same topic with same group.Id, it should work like a message queue. I think it's supposed to work like:
If 2 messages sent to Kafka, each or one of the flink program would process the 2 messages totally twice(let's say 2 lines of output in total).
But the actual result is that, each program would receive 2 pieces of the messages.
I have tried to use consumer client that came with the kafka server download. It worked in the documented way(2 messages processed).
I tried to use 2 kafka consumers in the same Main function of a flink programe. 4 messages processed totally.
I also tried to run 2 instances of flink, and assigned each one of them the same program of kafka consumer. 4 messages.
Any ideas?
This is the output I expect:
1> Kafka and Flink2 says: element-65
2> Kafka and Flink1 says: element-66
Here's the wrong output i always get:
1> Kafka and Flink2 says: element-65
1> Kafka and Flink1 says: element-65
2> Kafka and Flink2 says: element-66
2> Kafka and Flink1 says: element-66
And here is the segment of code:
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
ParameterTool parameterTool = ParameterTool.fromArgs(args);
DataStream<String> messageStream = env.addSource(new FlinkKafkaConsumer09<>(parameterTool.getRequired("topic"), new SimpleStringSchema(), parameterTool.getProperties()));
messageStream.rebalance().map(new MapFunction<String, String>() {
private static final long serialVersionUID = -6867736771747690202L;
#Override
public String map(String value) throws Exception {
return "Kafka and Flink1 says: " + value;
}
}).print();
env.execute();
}
I have tried to run it twice and also in the other way:
create 2 datastreams and env.execute() for each one in the Main function.
There was a quite similar question on the Flink user mailing list today, but I can't find the link to post it here. So here a part of the answer:
"Internally, the Flink Kafka connectors don’t use the consumer group
management functionality because they are using lower-level APIs
(SimpleConsumer in 0.8, and KafkaConsumer#assign(…) in 0.9) on each
parallel instance for more control on individual partition
consumption. So, essentially, the “group.id” setting in the Flink
Kafka connector is only used for committing offsets back to ZK / Kafka
brokers."
Maybe that clarifies things for you.
Also, there is a blog post about working with Flink and Kafka that may help you (https://data-artisans.com/blog/kafka-flink-a-practical-how-to).
Since there is not much use of group.id of flink kafka consumer other than commiting offset to zookeeper. Is there any way of offset monitoring as far as flink kafka consumer is concerned. I could see there is a way [with the help of consumer-groups/consumer-offset-checker] for console consumers but not for flink kafka consumers.
We want to see how our flink kafka consumer is behind/lagging with kafka topic size[total number of messages in topic at given point of time], it is fine to have it at partition level.