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Kafka partitioning 🪓

Efficiently distributing data for scalable and fault-tolerant stream processing.

· kafka,java

Partitioning in Apache Kafka facilitates scalability by breaking down a single topic log into multiple segments,

each capable of residing on a separate node within the Kafka cluster.

This decentralized approach optimizes the storage, writing, and processing of messages across multiple nodes,

ensuring efficient management of topics and enabling Kafka to handle large volumes of data and numerous reads and write

without being constrained to a single machine.

🤔 How Partitioning Works

Partitioning in Kafka distributes messages among topic partitions based on either a round-robin approach or a hash of the message key.

Using a key ensures that messages with the same key consistently land in the same partition, preserving their order, which is particularly useful for maintaining sequential data, such as events associated with specific entities like customers.

#kafka #partitioning #roadToKafka