I am new to Streaming Broker [like Kafka], and coming from Queueing Messaging System [like JMS, Rabbit MQ].
I read from Kafka docs that, messages are stored in Kafka partitions in offset as record. And consumer reads from offset.
What is the difference between message and record [does multiple/partial messages constitute a record?]
When comsumer reads from offset, is there a possibility that consumer reads partial message? IS there a need for consumer to string these parital messages based on some logic?
OR
1 message = 1 record = 1 offset
EDIT1:
The question was popped because, the "batch size" decides how many bytes of message should be published on to the borker. Lets say there are 2 messages with message1 = 100bytes and message2= 200 bytes and batchsize is set to 150bytes. Does this mean 100 bytes from message1 and 50 bytes from message2 are sent to broker at once? If yes, how are these 2 messages stored in offset?
In Kafka, a Producer sends messages or records (both terms can be used interchangeably) to Topics. A topic is divided into one or more Partitions that are distributed among the Kafka Cluster, which is generally composed of at least three Brokers.
A message/record is sent to a leader partition (which is owned by a single broker) and associated to an Offset. An Offset is a monotonically increasing numerical identifier used to uniquely identify a record inside a topic/partition, e.g. the first message stored in a record partition will have the offset 0 and so on.
Offsets are used both to identify the position of a message in a topic/partition as well as for the position of a Consumer Group.
For optimisation purpose , a producer will batch messages per partition. A batch is considered to be ready when either the configured batch.sized or linger.ms are reached. For example, if you have a batch.size set to 200KB and you send two messages (150KB and 100KB), they will be part potentially of the same batch. But the producer will never fragment a single message into chuncks.
No, a consumer cannot read partial messages.
Related
From the kafka faq page
In Kafka producer, a partition key can be specified to indicate the destination partition of the message. By default, a hashing-based partitioner is used to determine the partition id given the key
So all the messages with a particular key will always go to the same partition in a topic:
How does the consumer know which partition the producer wrote to, so it can consume directly from that partition?
If there are more producers than partitions, and multipe producers are writing to the same partition, how are the offsets ordered so that the consumers can consume messages from specific producers?
How does the consumer know which partition the producer wrote to
Doesn't need to, or at least shouldn't, as this would create a tight coupling between clients. All consumer instances should be responsible for handling all messages for the subscribed topic. While you can assign a Consumer to a list of TopicPartition instances, and you can call the methods of the DefaultPartitioner for a given key to find out what partition it would have gone to, I've personally not run across a need for that. Also, keep in mind, that Producers have full control over the partitioner.class setting, and do not need to inform Consumers about this setting.
If there are more producers than partitions, and multipe producers are writing to the same partition, how are the offsets ordered...
Number of producers or partitions doesn't matter. Batches are sequentially written to partitions. You can limit the number of batches sent at once per Producer client (and you only need one instance per application) with max.in.flight.requests, but for separate applications, you of course cannot control any ordering
so that the consumers can consume messages from specific producers?
Again, this should not be done.
Kafka is distributed event streaming, one of its use cases is decoupling services from producers to consumers, the producer producing/one application messages to topics and consumers /another application reads from topics,
If you have more then one producer, the order that data would be in the kafka/topic/partition is not guaranteed between producers, it will be the order of the messages that are written to the topic, (even with one producer there might be issues in ordering , read about idempotent producer)
The offset is atomic action which will promise that no two messages will get same offset.
The offset is running number, it has a meaning only in the specific topic and specfic partition
If using the default partioner it means you are using murmur2 algorithm to decide to which partition to send the messages, while sending a record to kafka that contains a key , the partioner in the producer runs the hash function which returns a value, the value is the number of the partition that this key would be sent to, this is same murmur2 function, so for the same key, with different producer you'll keep getting same partition value
The consumer is assigned/subscribed to handle topic/partition, it does not know which key was sent to each partition, there is assignor function which decides in consumer group, which consumer would handle which partition
I new to Kafka and i have a configuration where i have a source Kafka topic which has messages with a default retention for 7 days. I have 3 brokers with 1 partition and 1 replication.
When i try to consume messages from source Kafka topic and to my target Kafka topic i was able to consume messages in the same order. Now my question is if i am trying to reprocess all the messages from my source Kafka and consume in ,y Target Kafka i see that my Target Kafka is not consuming any messages. I know that duplication should be avoided but lets say i have a scenario where i have 100 messages in my source Kafka and i am expecting 200 messages in my target Kafka after running it twice. But i am just getting 100 messages in my first run and my second run returns nothing.
Can some one please explain why this is happening and what is the functionality behind it ?
Kafka consumer reads data from a partition of a topic. One consumer can read from one partition at one time only.
Once a message has been read by the consumer, it can't be re-read again. Let me first explain the current offset. When we call a poll method, Kafka sends some messages to us. Let us assume we have 100 records in the partition. The initial position of the current offset is 0. We made our first call and received 100 messages. Now Kafka will move the current offset to 100.
The current offset is a pointer to the last record that Kafka has already sent to a consumer in the most recent poll and that has been committed. So, the consumer doesn't get the same record twice because of the current offset. Please go through the following diagram and URL for complete understanding.
https://www.learningjournal.guru/courses/kafka/kafka-foundation-training/offset-management/
I read a kafka documentation, but I still confused, when someone talk about data and partitions.
In documentation I see that client will send message to partition.
Then partition replicate message to replicas (across brokers).
And consumer read data from partition.
I have an topic which have 2 partitions.
Let's say I have one producer, which send message to partition#1.
But I have 2 consumers, one read from partition#1, and second from partition#2.
Is it mean that my partition#1 will have 50% messages, and partition#2 will have 50%. Or when client send data to partition#1 then partition#1 should be replicate data not only across brokers, but and for across partitions?
About your specific example ...
If your producer sends messages without a key on the message, the default partitioner (in the producer itself) will apply a round robin algorithm to send messages to partitions so: message 1 to partition 1, messages 2 to partition 2, message 3 to partition 1 and so on. It means that you are right, partition 1 will get 50% of messages. So one consumer reading from partition 1 will get 50% of sent messages; the other 50% will be got by the other consumer reading from partition 2. This is how Kafka works for having higher throughtput and handling more consumers.
It's important to add that when a partition has more replicas, one of them is defained "leader" and the other ones are "followers". The messages exchange happens always through the "leader". The "followers" are just copies. They are used in case the broker hosting the "leader" partition goes down and another broker which hosts a "follower" partition is elected as "leader".
I hope this helps.
How to find the offset of a message in Kafka Topic? Does the offset contains multiple messages or a single message?
Offsets only link to a single message within a single partition of a topic.
You could have the same offset be available in many partitions and many topics, but there is almost no correlation between those values unless you explictly made the producers do that.
There is no easy way to find the offset for a single message. You need to scan the whole topic (or at least a single partition)
Assuming you've read the message using a consume() or poll(), and you're interested in the details of this message, you can find the corresponding partition and offset using the following code:
# assuming you have a Kafka consumer in place
msg = consumer.consume()
partition = msg.partition()
offset = msg.offset()
A Kafka topic is divided into partitions. Kafka distributes the incoming messages in a round robin fashion across partitions (unless you've specified some key on which to partition). So, for a random message that you haven't read, you may have to scan all partitions to find the message, and then the corresponding offset.
I want any information/explanation on how Kafka maintains a message sequence when messages are written to topic with multiple partition.
For e.g. I have multiple message producer each producing messages sequentially and writing on the Kafka topic with more than 1 partition. In this case, how consumer group will work to consume messages.
Kafka only provides a total order over records within a partition, not between different partitions in a topic. Even within one partition, you still could encounter the out-of-order events if retries is enabled and max.in.flight.requests.per.connection is larger than 1.
Work-around is create a topic with only one partition although it means only one consumer process per consumer group.
Kafka will store messages in the partitions according to the message key given to the producer. If none is given, then the messages will be written in a round-robin style into the partitions. To keep ordering for a topic, you need to make sure the ordered sequence has the same key, or that the topic has only one partition.