Suppose I have a Kafka cluster of 1000 nodes. Let's say that some producer sends produces a message to certain topic, what is the first node in the cluster that receives this message? Is there any load balancer inside the Kafka cluster? Let's say that this node doesn't have the lead partition that the message should be pushed to, can it forward the message to the broker that includes this partition?
The client knows all brokers of the cluster, and can only produce to the leader topic partition, which it can identify, and is only hosted on a single broker. The Controller defines leadership How many Kafka controllers are there in a cluster and what is the purpose of a controller?
There's no load balancer, all brokers are equal with respect to what requests they can receive and don't redirect events to others outside of replication
The partitioner instance within the prouder client will hash the key of the message (by default, and if key is non null), and modulo by the number of partitions in the topic. With that value, it'll produce to the specific broker hosting that partition number
Related
I tried to follow
https://medium.com/#iet.vijay/kafka-multi-brokers-multi-consumers-and-message-ordering-b61ad7841875
to create multiple brokers and consumer.
I am able to produce message and consume the same.
when i try to describe the topic the below is the output which I got.
Can some one explain me about the partitions and leader and replicas here in above image.
All producer and consumer requests are sent to the leader broker, which is elected by the Kafka Controller.
Replicas are the non-leader broker. Replicas can be in or out of sync with the leader (ISR = "in sync replica")
The numbers that are shown are each of the broker.id values from the broker properties, which default to increment from 0 if not set
More details at https://kafka.apache.org/documentation/#replication
Worth pointing out that running multiple brokers on a single host is less than ideal; you still have a single point of failure and you're causing unnecessary duplicate writes on single hard drive for each replica
Consider the below scenario:
I have a Kakfa broker cluster(localhost:9002,localhost:9003,localhost:9004,localhost:9005).
Let's say localhost:9002 is my primary(leader) for the cluster.
Now my producer is producing data and sending it to the broker(localhost:9002).
If my primary broker(localhost:9002) goes down, with the help of Zookeeper or some other consensus algorithm new leader will be elected(consider localhost:9003 is now the new leader).
So, in the above scenario can someone please explain to me how the Kafka client(producer) will get notified about the new broker configuration(localhost:9003) and how it will connect to the new leaders and start producing data again.
Kafka clients are receiving the necessary meta information from the cluster automatically on each request when reading from or writing to a topic in case of a leadership change.
In general, the client sends a (read/write) request to one of the bootstrap server, listed in the configuration bootstrap.servers. This initial request (hence called bootstrap) returns the details on which broker the topic partition leader is located so that the client can communicate directly with that broker. Each individual broker contains all meta information for the entire cluster, meaning also having the knowledge on the partition leader of other brokers.
Now, if one of your broker goes down and the leadership of a topic partition switches, your producer will get notified about it through that mechanism.
There is a KafkaProducer configuration called metadata.max.age.ms which you can modify to update metadata on your producer even if there is no leadership change happening:
"Controls how long the producer will cache metadata for a topic that's idle. If the elapsed time since a topic was last produced to exceeds the metadata idle duration, then the topic's metadata is forgotten and the next access to it will force a metadata fetch request."
Just a few notes on your question:
The term "Kafka broker cluster" does not really exists. You have a Kafka cluster containing one or multiple Kafka brokers.
You do not have a broker as a "primary(leader) for the cluster" but you have for each TopicPartition a leader. Maybe you mean the Controller which is located on one of the brokers within your cluster.
I have Kafka cluster with three brokers and zookeeper instances. Kept the replication factor of 2 for each partition.
i want to understand the impact of publishing messages to single node in a cluster by giving one broker address. Will this broker sends message to other brokers if messages fit into partitions hold by other brokers?
can someone explain how internal sync works or else point to resources.
giving one broker address
Even if you give one address, the bootstrap protocol returns all brokers to the client.
The partitioner logic determines which partition in which broker to send the data to - you target partitions, not brokers in the client.
I understand producer/consumers need to talk to brokers to know leader for partition. Brokers talk to zk to tell they joined the cluster.
Is it true that
Brokers know who is the leader for a given partition from zk
zk detects broker left/died. Then it re-elects leader and sends new leader info to all brokers
Question:
why do we need brokers to communicate with each other? Is it just
so tehy can move partitions around or do they also query metadata from each other. If so what would be example of metadata exchange
Producers/ consumers request metadata from one of the brokers ( as each one of them caches it) and that is how they know who is the leader for a partition.
Regarding "is it true that" section:
Brokers know who is the leader for the given partition thanks to zk and one of them. To be more precise, one of them decides who will be a leader. That broker is called controller. The first broker that connects to zookeeper becomes a controller and his role is to decide which broker will be a leader and which ones will be replicas and to inform them about it. Controller itself is not excluded from this process. It is a broker like any other with this special responsibilities of choosing leaders and replicas
zk indeed detects when a broker dies/ leaves but it doesn't reelect leader. It is controller responsibility. When one of the brokers leaves a cluster, controller gets information from zk and it starts reassignment
About your question - brokers do communicate with each other ( replicas are reading the messages from leaders, controller is informing other brokers about changes), but they do not exchange metadata among themselves - they write metadata to a zookeeper
A Broker is a Kafka server that runs in a Kafka Cluster
"A Kafka cluster is made up of multiple Kafka Brokers. Each Kafka Broker has a unique ID (number). Kafka Brokers contain topic log partitions. Connecting to one broker bootstraps a client to the entire Kafka cluster"
Each broker holds a number of partitions and each of these partitions can be either a leader or a replica for a topic. All writes and reads to a topic go through the leader and the leader coordinates updating replicas with new data. If a leader fails, a replica takes over as the new leader.
The producers send messages by setting up a list of Kafka Broker as follows.
props.put("bootstrap.servers", "127.0.0.1:9092,127.0.0.1:9092,127.0.0.1:9092");
I wonder "producers" how to know that which of the three brokers knew which one had a partition leader.
For a typical distributed server, either you have a load bearing server or have a virtual IP, but for Kafka, how is it loaded?
Does the producers program try to connect to one broker at random and look for a broker with a partition leader?
A Kafka cluster contains multiple broker instances. At any given time, exactly one broker is the leader while the remaining are the in-sync-replicas (ISR) which contain the replicated data. When the leader broker is taken down unexpectedly, one of the ISR becomes the leader.
Kafka chooses one broker’s partition’s replicas as leader using ZooKeeper. When a producer publishes a message to a partition in a topic, it is forwarded to its leader.
According to Kafka documentation:
The partitions of the log are distributed over the servers in the
Kafka cluster with each server handling data and requests for a share
of the partitions. Each partition is replicated across a configurable
number of servers for fault tolerance.
Each partition has one server which acts as the "leader" and zero or
more servers which act as "followers". The leader handles all read and
write requests for the partition while the followers passively
replicate the leader. If the leader fails, one of the followers will
automatically become the new leader. Each server acts as a leader for
some of its partitions and a follower for others so load is well
balanced within the cluster.
You can find topic and partition leader using this piece of code.
EDIT:
The producer sends a meta request with a list of topics to one of the brokers you supplied when configuring the producer.
The response from the broker contains a list of partitions in those topics and the leader for each partition. The producer caches this information and therefore, it knows where to redirect the messages.
It's quite an old question but I have the same question and after researched, I want to share the answer cuz I hope it can help others.
To determine leader of a partition, producer uses a request type called a metadata request, which includes a list of topics the producer is interested in.
The broker will response specifies which partitions exist in the topics, the replicas for each partition, and which replica is the leader.
Metadata requests can be sent to any broker because all brokers have a metadata cache that contains this information.