Topics, Partitions, and Offsets

The video introduces Kafka topics, comparing them to database tables, and explains how they are structured with partitions and offsets. It provides a practical example using truck GPS data to illustrate how Kafka topics work. The video also covers data management aspects like order, retention, and immutability, concluding with a call to practice the concepts discussed.

What is a Kafka topic most similar to in a database?

• A database schema

• A database query

• A database table

• A database index

How are Kafka partitions numbered?

• Starting from one

• Starting from zero

• Starting from a random number

• Starting from ten

In the trucking company example, what does each message contain?

• Truck ID and GPS coordinates

• Truck ID and fuel level

• Truck ID and driver name

• Truck ID and speed

What is the default data retention period in Kafka?

• One year

• One week

• One month

• One day

What is guaranteed within a Kafka partition?

• Data immutability

• Data duplication

• Data order

• Data deletion

What happens to offsets when data is deleted in Kafka?

• Offsets continue incrementing

• Offsets are archived

• Offsets reset to zero

• Offsets are deleted

What is the significance of offsets in Kafka?

• They indicate the data retention period

• They determine the partition

• They identify the topic

• They provide a unique ID for messages within a partition