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CCDAK · Question #214

You have a topic with four partitions. The application reading this topic is using a consumer group and two consumers. The throughput is smoothly distributed among partitions but the application lag…

The correct answer is A. Add more consumers to increase the level of parallelism of the processing. Since CPU is the bottleneck and lag is increasing, adding more consumers to the consumer group will increase the parallelism of message processing. Each consumer can be assigned one or more partitions, allowing the workload to be distributed more efficiently across multiple CPU

Developing Kafka Consumers

Question

You have a topic with four partitions. The application reading this topic is using a consumer group and two consumers. The throughput is smoothly distributed among partitions but the application lag is increasing. Application monitoring shows that message processing is taking all the CPU. Which action should you take to resolve this issue?

Options

  • AAdd more consumers to increase the level of parallelism of the processing.
  • BAdd more partitions to the topic to increase the level of parallelism of the processing.
  • CIncrease the 'max.poll.records' property of consumers.
  • DDecrease the 'max.poll.records' property of consumers.

How the community answered

(22 responses)
  • A
    64% (14)
  • B
    5% (1)
  • C
    9% (2)
  • D
    23% (5)

Explanation

Since CPU is the bottleneck and lag is increasing, adding more consumers to the consumer group will increase the parallelism of message processing. Each consumer can be assigned one or more partitions, allowing the workload to be distributed more efficiently across multiple CPU

Topics

#consumer parallelism#consumer lag#CPU bottleneck#consumer group scaling

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