I have data coming in through RabbitMQ. The data is coming in constantly, multiple messages per second.
I need to forward that data to Kafka.
In my RabbitMQ delivery callback where I am getting the data from RabbitMQ I have a Kafka producer that immediately sends the recevied messages to Kafka.
My question is very simple. Is it better to create a Kafka producer outside of the callback method and use that one producer for all messages or should I create the producer inside the callback method and close it after the message is sent, which means that I am creating a new producer for each message?
It might be a naive question but I am new to Kafka and so far I did not find a definitive answer on the internet.
EDIT : I am using a Java Kafka client.
Creating a Kafka producer is an expensive operation, so using Kafka producer as a singleton will be a good practice considering performance and utilizing resources.
For Java clients, this is from the docs:
The producer is thread safe and should generally be shared among all threads for best performance.
For librdkafka based clients (confluent-dotnet, confluent-python etc.), I can link this related issue with this quote from the issue:
Yes, creating a singleton service like that is a good pattern. you definitely should not create a producer each time you want to produce a message - it is approximately 500,000 times less efficient.
Kafka producer is stateful. It contains meta info(periodical synced from brokers), send message buffer etc. So create producer for each message is impracticable.
Related
I am new to kafka.I have a Kafka Stream using java microservice that consumes the messages from kafka topic produced by producer and processes. The kafka commit interval has been set using the auto.commit.interval.ms . My question is, before commit if the microservice crashes , what will happen to the messages that got processed but didn't get committed? will there be duplicated records? and how to resolve this duplication, if happens?
Kafka has exactly-once-semantics which guarantees the records will get processed only once. Take a look at this section of Spring Kafka's docs for more details on the Spring support for that. Also, see this section for the support for transactions.
Kafka provides various delivery semantics. These delivery semantics can be decided on the basis of your use-case you've implemented.
If you're concerned that your messages should not get lost by consumer service - you should go ahead with at-lease once delivery semantic.
Now answering your question on the basis of at-least once delivery semantics:
If your consumer service crashes before committing the Kafka message, it will re-stream the message once your consumer service is up and running. This is because the offset for a partition was not committed. Once the message is processed by the consumer, committing an offset for a partition happens. In simple words, it says that the offset has been processed and Kafka will not send the committed message for the same partition.
at-least once delivery semantics are usually good enough for use cases where data duplication is not a big issue or deduplication is possible on the consumer side. For example - with a unique key in each message, a message can be rejected when writing duplicate data to the database.
There are mainly three types of delivery semantics,
At most once-
Offsets are committed as soon as the message is received at consumer.
It's a bit risky as if the processing goes wrong the message will be lost.
At least once-
Offsets are committed after the messages processed so it's usually the preferred one.
If the processing goes wrong the message will be read again as its not been committed.
The problem with this is duplicate processing of message so make sure your processing is idempotent. (Yes your application should handle duplicates, Kafka won't help here)
Means in case of processing again will not impact your system.
Exactly once-
Can be achieved for kafka to kafka communication using kafka streams API.
Its not your case.
You can choose semantics from above as per your requirement.
I wish to describe the following scenario:
I have a node.js backend application (It uses a single thread event loop).
This is the general architecture of the system:
Producer -> Kafka -> Consumer -> Database
Let's say that the producer sends a message to Kafka, and the purpose of this message is the make a certain query in database and retrieve the query result.
However, as we all know Kafka is an asynchronous system. If the producer sends a message to Kafka, it gets a response that the message has been accepted by a Kafka broker. Kafka broker doesn't wait until the consumer polls the message and processes it.
In this case, how can the producer get the query result operated on the database?
The flow using Kafka will look like this:
The only way of the Producer A be aware of what happened with the message consumed by the Consumer A is producing another message. Which will be handled accordingly by any other consumer available (in this case, Consumer B).
As you already mentioned, this flow is asynchronous. This can be useful when you have a very heavy processing on your query, like a report generation or something like that, and the second producer will notify an user inbox for example.
If that is not the case, perhaps you should use HTTP, which is synchronous and you will have the response at the end of processing.
You must generate new flow for communicate the query result:
Consumer (now its a producer) -> Kafka topic -> Producer (now its a consumer)
You should consider using another synchronous communication mechanism like HTTP.
I have the following situation:
I have 5 instances of the same service, all in the same kafka consumer group. One of them has a websocket connection to the client (the graphql subscription). I use graphql-java and Spring Boot.
When that connection is opened, I produce events from any of the 5 instances (with a message key defined so they go to the same partition and ordered) and I need for all those events to be consumed by the same instance that opened that connection. Not by the other 4.
Even if the partition assignment plays in my favor, a reassignment can by done at any time, leaving me without luck
My implementation is using reactor-kafka but I think it's just an implementation detail.
The options I see are:
Start to listen on that topic with a new group id each time, so that service always receives the messages from that topic (but the 5 in the other group id too)
Create a new topic for each websocket connection, so only the producer knows that topic (but the topic id should be sent in the kafka events so that the producers of those events know where to publish them)
If I receive the message and I'm not the one with the connection, don't ACK it. But this would make things slow and seems hacky
Start using something different altogether like Redis PubSub to receive all messages in all consumers and check for the connection.
I see there's an implementation for node but I don't see how it is solving the problem.
A similar question explains how to program a subscription but doesn't talk about this distributed thing.
Is the cleanest approach any of the one I suggested? Is there an approach with Kafka that I'm not seeing? Or am I misunderstanding some piece?
I ended up using 1 consumer group id per listener with a topic specifically for those events.
I have one kafka producer and consumer.The kafka producer is publishing to one topic and the data is taken and some processing is done. The kafka consumer is reading from another topic about whether the processing of data from topic 1 was successful or not ie topic 2 has success or failure messages.Now Iam starting my consumer and then publishing the data to topic 1 .I want to make the producer and consumer synchronous ie once the producer publishes the data the consumer should read the success or failure message for that data and then the producer should proceed with the next set of data .
Apache Kafka and Publish/Subscribe messaging in general seeks to de-couple producers and consumers through the use of streaming async events. What you are describing is more like a batch job or a synchronous Remote Procedure Call (RPC) where the Producer and Consumer are explicitly coupled together. The standard Apache Kafka Producers/Consumer APIs do not support this Message Exchange Pattern but you can always write your own simple wrapper on top of the Kafka API's that uses Correlation IDs, Consumption ACKs, and Request/Response messages to make your own interface that behaves as you wish.
Short Answer : You can't do that, Kafka doesn't provide that support.
Long Answer: As Hans explained, Publish/Subscribe messaging model keeps Publish and subscribe completely unaware of each other and I believe that is where the power of this model lies. Producer can produce without worrying about if there is any consumer and consumer can consume without worrying about how many producers are there.
The closest you can do is, you can make your producer synchronous. Which means you can wait till your message is received and acknowledged by broker.
if you want to do that, flush after every send.
In my kafka consumer threads(high level), after I consumed a message I am applying some business logic to this message and forwarding this to a WS. But this webservice may be down sometimes and since I consumed this object from kafka and offset is moved forward, i would missed this object.
One way get rid of from this problem is to disabling autocommit in zookeeper and committing offset by calling programmaticaly but i expect that this is a very costly operation. I will be producing to kafka at about 2000 tps and may increase later times.
Another way - which i am not sure if it is a good idea - is if i face with any problem, producing this consumed object to kafka again but i didn't see any post related to this across all my googleings. Is this a thing which is even not considerable?
Can you please give me some insights about handling this situation.
Thanks
You can post back the failed message to the same topic or another of your choice.
If you use the same topic, you will push the messages at the end of the topic and they will be picked up after the others (so if order matters to you don't do this). Also if the action that you perform before sending the message is not idempotent you will have to something to identifying this records so they don't perform the action twice.
If you use a failed_topic, you can push the messages that you can't send to this topic and when the WS is healthy again you need to create a consumer that consumes all the messages there and sends them to the WS.
Hope it helps!
Moving such messages to an error queue and retrying them later is a well known approach.
See Dead letter channel