Kafka Topic Partitions
Explore how Kafka topic partitions work to support scalable data streaming. Understand the role of partitions in distributing messages, handling keys, and enabling parallel consumer processing. This lesson clarifies how partitioning impacts throughput, message order, and load balancing in Kafka applications.
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A topic can be broken down into multiple partitions. Each partition is a log on its own and has its own set of offsets. When messages are produced to a topic, each message can be routed to a different partition. Let’s take a look at a topic with three partitions:
There are two main reasons to have multiple partitions in a topic. We learned about the first reason in the previous section—partitioning the topic enables horizontal scaling for the topic’s size. Kafka can keep each partition on a different machine with its own disk, allowing topics to grow beyond the space capabilities of a single disk.
The second reason to have multiple partitions in a topic is consumer throughput and ...