Consider a Kafka topic with one partition. A producer sends messages with keys 1, 2, 3 in that order. The consumer reads from this partition. What order will the consumer receive the messages?
Producer sends messages: [1, 2, 3] Consumer reads messages from partition 0
Think about how Kafka guarantees ordering within a partition.
Kafka guarantees that messages within a single partition are delivered in the order they were produced. So the consumer will receive messages 1, 2, 3 in that exact order.
A Kafka topic has 3 partitions. A producer sends messages with keys 1 to 6, distributed across partitions. The consumer reads from all partitions. What can be said about the order of messages received?
Producer sends messages with keys 1 to 6 across 3 partitions Consumer reads from all partitions
Recall Kafka's ordering guarantees across partitions.
Kafka guarantees ordering only within each partition. Across partitions, messages can be interleaved in any order.
Kafka guarantees message order within a partition but not across partitions. Why is this design chosen?
Think about how Kafka achieves high throughput and fault tolerance.
Kafka partitions allow parallel processing and scalability. Guaranteeing order only within partitions enables this parallelism without complex global coordination.
A consumer manually tries to read offset 10 before offset 9 in a Kafka partition. What happens?
Consumer seeks to offset 10 before reading offset 9
Consider how Kafka consumers control offsets.
Kafka consumers can seek to any offset. If they seek to offset 10, they start reading from there, skipping earlier offsets. Kafka does not enforce sequential offset reading.
Kafka guarantees ordering only within partitions. How can a producer ensure strict global ordering of messages sent to a topic?
Think about how partitioning affects ordering guarantees.
Using a single partition ensures all messages are in one sequence, preserving strict global order. Multiple partitions break global ordering.