a question troubled me a long time. I know the leader election exists in zookeeper. Suppose we have a Kafka cluster connected with Zookeeper ensemble .
So my understanding is like, there is a zookeeper leader in Ensemble, and there are some "partition leaders" in Kafka cluster as well. And Kafka partition leader are elected through Zookeeper API. Is it right ?
Another question, Is master/worker basically same as leader/follower ?
Zookeeper leader election has nothing to to with Kafka partition leader election, vice versa.
Kafka partition leader elect by Controller, Controller is the Broker who registers
first in Zookeeper's path /Controller/2,2 is broker.id.
When a broker crash down, the leader partition (or leader replica) in this broker will be switched by Controller and Controller will choose one replica in ISR be the partition leader.
If this partition offline (all replica not available), this partition cannot be used for write or read. If you set unclean.leader.election.enable=true, then the first available replica will be elected as partition leader, no matter it's in ISR or not.
So some messages maybe lost.
Kafka and Zookeeper use leader/follower, not master/worker
Partition leader election in Kafka is not done through zookeeper API, actually, the first replica in alive assign replicas will be elected as the leader for each partition.
As for the master/worker things, as I know, many open sources have already replaced the old terminology with leader/replica or primary/replica, so basically, they are the same.
Related
I am reading one of the article related to Kafka basics. If one of the Kafka brokerX dies in a cluster then, that brokerX data copies will move to other live brokers, which are in the cluster.
If that is the case, Is zookeeper/Kafka Controller will copy the brokerX data folder and move to live brokers like copy paste from one machine hard-disc to another (physical copy)?
Or, live brokers will share a common location ? so that will zookeeper/controller will link/point to the brokerX locations(logical copy) ?
I am little hard in understanding here. Could someone help me on this?
If a broker dies, it's dead. There's no background process that will copy data off of it
The replication of topics only happens while the broker is running
Plus, that image is wrong. The partitions = 2 means exactly that. A third partition doesn't just appear when a broker dies
This all depends if the topic has a replication factor > 1. In this case, brokers holding follower replica are constantly sending fetch requests to the leader replica (a specific broker), with a goal of being head to head with the leader (both the follower replica and leader replica having the same records stored on disk).
So when a broker goes down, all it takes is for the controller to select and promote an in-sync replica (by default, but could select non insync replicas) to take over as the leader of the partition. No copy/paste required, all brokers holding a partition(s) (as a follower replica or leader replica) of that topic are storing the same information prior to shutting down.
If a broker dies the behaviour depends on the dead broker. If it was not the leader for its partition it's non problem. when the broker returns on-line it will have to copy all missing data from the leader replica. If the dead broker was the leader for the partition a new leader will be elected according to some rules. If the new elected leader was in sync before the old leader died, there will be no message loss and the follower brokers will sync their replica from the new leader, as the broken leader will do when up again. If the new elected leader was not in sync you might have some message loss. Anyway you can drive the behaviour of your kafka cluster setting various parameters to balance speed, data integrity and reliability.
I'm new to Kafka and I want to ask a question.
If there are 3 Kafka brokers(kafka1, kafka2, kafka3)(they are in same Kafka Cluster)
and topic=test(replication=2)
kafka1 has leader partition and kafka2 has follower partition.
If producer sends data to kafka3, then how do data stored in kafka1 and Kafka2?
I heard that, if producer sends data to kafka3, then the zookeeper finds the broker who has the leader partition and returns the broker's dns or IP address.
And then, producer will resend to the broker with metadata.
Is it right? or if it's wrong, plz tell me how it works.
Thanks a lot!
Every kafka topic partition has its own leader. So if you have 2 partitions , kafka would assign leader for each partition. They might end up being same kafka nodes or they might be different.
When producer connects to kafka cluster, it gets to know about the the partition leaders. All writes must go through corresponding partition leader, which is responsible to keep track of in-sync replicas.
All consumers only talk to corresponding partition leaders to get data.
If partition leader goes down , one of the replicas become leader and all producers and consumers are notified about this change
Please differentiate Kafka Leader(Broker) and Partition leader. Partition leader can be present in follower as well. When we send the message to Kafka broker, it will directly send the message to leader and follower based on partition?
From https://kafka.apache.org/documentation/#intro_distribution
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.
[edit]
From https://kafka.apache.org/documentation/#design_replicamanagment
It is also important to optimize the leadership election process as that is the critical window of unavailability. A naive implementation of leader election would end up running an election per partition for all partitions a node hosted when that node failed. Instead, we elect one of the brokers as the "controller". This controller detects failures at the broker level and is responsible for changing the leader of all affected partitions in a failed broker. The result is that we are able to batch together many of the required leadership change notifications which makes the election process far cheaper and faster for a large number of partitions. If the controller fails, one of the surviving brokers will become the new controller.
The broker writes messages to only partition leader of topic those messages replicated to follower partitions.
If leader partition fail follower partition will replace the leader partition.
What is kafka controller?
A. The Kafka controller is brain of the Kafka cluster:
Broker leader is called kafka controller.
one of the brokers serves as the active controller there can be only one controller at a time. if u find 2 controllers that is a glitch.
controller monitors the liveliness of the brokers and acts on broker failures i.e. if a broker dies, then controller divides up leadership of its topic partitions to the remaining brokers in the cluster.
also responsible for electing topic partition leaders.
zookeeper elect one of the broker as controller.
broker controller will elect one of the partition as leader.
When the Zookeeper doesn't receive heartbeat messages from the Controller, Zookeeper elects one of the available brokers as new controller.
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.
Does Kafka broker store metadata which producer API uses (e.g. which partitions are leader for a topic etc.)? As per my understanding this metadata is stored in Zookeeper , is it correct? If it is true then how Brokers are updated by Zookeeper with latest information?
All Kafka brokers can answer a metadata request that describes the current state of the cluster: what topics there are, which partitions those topics have, which broker is the leader for those partitions etc.
ZooKeeper is responsible for:
Electing a controller broker - and making sure there is only one
Cluster membership - allowing brokers to join a cluster
Topic configuration - which topics exist, how many partitions each has, where are the replicas, who is the preferred leader, what configuration overrides are set for each topic
Quotas - how much data is each client allowed to read and write
ACLs - who is allowed to read and write to which topic
There is regular communication between Kafka and ZooKeeper such that ZooKeeper knows a Kafka broker is still alive (ZooKeeper heartbeat mechanism) and also in response to events such as a topic being created or a replica falling out of sync for a topic-partition.
Kafka is a distributed system and is built to use Zookeeper which is responsible for controller election, topic configuration, clustering etc.
More precisely, Zookeeper initiates controller election. The controller broker is a single broker in the Kafka cluster which takes care of leader broker and followers for every partition. When a particular broker is taken down, the controller lets other replicas know (in order to handle partition leaders etc). Moreover, when the controller fails then Zookeeper initiates new elections in order to elect the new broker which will act as the controller.
Furthermore, Zookeeper knows which brokers are part of the Kafka cluster and which are still alive. Similarly, it is also aware of topic-specific information such as which topics exist, how many partitions each has, where are the replicas and so on.
Zookeeper also stores information regarding quotas and ACLs, i.e. what volume of data each client is allowed to consume/produce and also, who is allowed to consume or produce from a particular topic.