A topic is a named stream, split into partitions. Offsets mark positions in a partition. Brokers are the servers, and replicas are copies of each partition.
A topic is a named stream of records, such as orders. Kafka splits it into partitions. Each partition is an ordered, append-only log stored on disk. New records are only added at the end.
Every record in a partition gets a number in sequence, called its offset. Consumers use offsets to track their position.
A broker is a Kafka server. Kafka spreads partitions across brokers, so the whole cluster shares a topic's load and storage.
Each partition has a replication factor: the number of copies it has. Each copy is a replica:
- One replica is the leader. It handles writes and normally reads too.
- The other replicas are followers. They copy the leader.
- Followers that are fully caught up form the ISR (in-sync replica set).
- If the leader's broker fails, a replica from the ISR becomes the new leader.
Partitions are the unit of parallelism and of ordering. Kafka guarantees order only inside one partition.
- A topic is split into partitions, and each partition is an append-only log.
- An offset is a record's position inside its partition.
- Brokers host partitions, so the load spreads across the cluster.
- Each partition has a leader and follower replicas, and a replica from the ISR takes over if the leader fails.
- A partition is the unit of ordering and parallelism.
- Kafka introduction (https://kafka.apache.org/intro)kafka.apache.org
- Kafka partitions (https://developer.confluent.io/courses/apache-kafka/partitions/)developer.confluent.io