Need some help with the below error. I am trying to connect to kafka to read data from Kafka topic. I using AdminClient as well to describe Topics. Why I am seeing this error.
Java.util.concurrent.ExecutionException: org.apache.kafka.common.KafkaException: No stream name specified in the topic path or in
the default stream configuration options
at
org.apache.kafka.common.internals.Kafka Future Impl.wrapAndThrow (Kafka Future Impl.java:45)
at
org.apache.kafka.common.internals.Kafka
Future Impl.access$000 (Kafka Future Impl.java:32)
at
org.apache.kafka.common.internals.Kafka Future Impl$SingleWaiter.await (KafkaFuture Impl.java:89)
at org.apache.kafka.common.internals.Kafka Future Impl.get (Kafka Future Impl.java:258)
Related
I am new to Kafka. I have written a simple JAVA program to generate a message using avro schema. I have generated a specific record. The record is generated successfully. My schema is not yet registered with my local environment. It is currently registered with some other environment.
I am using the apache kafka producer library to publish the message to my local environment kafka topic. Can I publish the message to the local topic or the schema needs to be registered with the local schema registry as well.
Below are the producer properties -
properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, KafkaAvroSerializer.class);
properties.put(KafkaAvroSerializerConfig.SCHEMA_REGISTRY_URL_CONFIG, "https://schema-registry.xxxx.service.dev:443");```
Error I am getting while publishing the message -
``` org.apache.kafka.common.errors.SerializationException: Error registering Avro schema:
Caused by: io.confluent.kafka.schemaregistry.client.rest.exceptions.RestClientException: User is denied operation Write on Subject: xxx.avro-value; error code: **40301**
The issue was kafka producer by default tries to register the schema on topic. So, I added the below - properties.put(KafkaAvroSerializerConfig.AUTO_REGISTER_SCHEMAS, false);
and it resolved the issue.
I have built a very simple akka stream based on the alpakka project, but it doesn't read anything from kafka even though it connects and creates a consumer group. I have created an implicit Actor System and Materializer for the stream.
val done = Consumer.committableSource(consumerSettings,
Subscriptions.topics(kafkaTopic))
.map(msg => msg.committableOffset)
.mapAsync(1) { offset =>
offset.commitScaladsl()
}
.runWith(Sink.ignore)
[stream.actor.dispatcher] sends this message to KafkaConsumerActor "Requesting messages, requestId: 1, partitions: Set(kafka-topic-0)"
The KafkaConsumerActor doesn't seem to receive the message but when the supervisor asks the Actor to shutdown it does receive the message and shutdown.
Any lead on why it fails to read Kafka without an Error or Exception ?
I couldn't figure out why my akka stream wasn't consuming messages from the kafka broker, But When I implemented the same stream as a Runnable Graph, it worked.
Examples that I used - https://www.programcreek.com/scala/akka.stream.scaladsl.RunnableGraph
I'm trying to implement Kafka consumer with topic names as a pattern. E.g. #KafkaListener(topicPattern="${kafka.topics}") where property kafka.topics is 'sss.*'. Now when I send message to topic 'sss.test' or any other topic name like 'sss.xyz', 'sss.pqr', it's throwing error as below:
WARN o.apache.kafka.clients.NetworkClient - Error while fetching metadata with correlation id 12 : {sss.xyz-topic=LEADER_NOT_AVAILABLE}
I tried to enable listeners & advertised.listeners in the server.properties file but when I re-start Kafka it consumes messages from all old topics which were tried. The moment I use new topic name, it throws above error.
Kafka doesn't support pattern matching? Or there's some configuration which I'm missing? Please suggest.
Recently we are experiencing "Error from SyncGroup: The request timed out" frequently with the Java Kafka APIs.
This issue usually happens with few topic or consumer group in Kafka cluster. Does anyone can provide some pointers about this error?
As a workaround, if I change the consumer group name I don't see the error.
Broker Version : 0.9.0
Kafka client version : 0.9.0.1
Exception in thread "main" org.apache.kafka.common.KafkaException: Unexpected error from SyncGroup: The request timed out.
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$SyncGroupRequestHandler.handle(AbstractCoordinator.java:444)
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$SyncGroupRequestHandler.handle(AbstractCoordinator.java:411)
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:665)
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:644)
at org.apache.kafka.clients.consumer.internals.RequestFuture$1.onSuccess(RequestFuture.java:167)
at org.apache.kafka.clients.consumer.internals.RequestFuture.fireSuccess(RequestFuture.java:133)
at org.apache.kafka.clients.consumer.internals.RequestFuture.complete(RequestFuture.java:107)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient$RequestFutureCompletionHandler.onComplete(ConsumerNetworkClient.java:380)
at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:274)
#zer0Id0l
We have had the same problem recently. It happens because some Kafka Streams messages have meta information footprint which is more than a regular one (when you don't use Kafka Streams). To fix the issue, go to __consumer_offsets topic settings and set max.message.bytes param higher than it is by default. For example, in our case we have max.message.bytes = 20971520. That will completely solve your problem.
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.