What is the Kafka Topic underlying DataStructure?

 In Apache Kafka, the underlying data structure for topics and their partitions is not a linked list. Instead, Kafka uses a data structure that involves segmented, immutable log files.

Kafka relies on a storage abstraction referred to as a "log." Each partition within a topic is associated with its own log. This log is a structured sequence of records (messages) that are appended in an immutable and ordered manner.

The structure of Kafka logs is more akin to an append-only file, where messages are written sequentially. Each message is stored with an associated offset, representing its unique identifier within the partition. These logs are segmented for easier management and handling.

This log structure provides several benefits:

Sequential Writes: Messages are appended to the end of the log, allowing for efficient sequential writes.

Immutability: Once a message is written, it cannot be changed. This immutability ensures data integrity.

Segmentation: Logs are segmented into smaller files for easier management and storage. Segments are periodically closed and archived, which aids in data retention and cleanup.

Offset-based Retrieval: Consumers can read messages based on their offsets, enabling efficient retrieval and replaying of messages.

This design of using segmented, immutable logs allows Kafka to efficiently handle large volumes of data, provide fault tolerance through replication, enable high throughput, and support reliable message delivery while maintaining strong ordering guarantees within partitions.