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To achieve maximum parallelism for a Kafka topic with 5 partitions, which consumer group configuration is optimal?

hard📝 Application Q8 of 15
Kafka - Consumer Groups
To achieve maximum parallelism for a Kafka topic with 5 partitions, which consumer group configuration is optimal?
A3 consumers sharing 5 partitions with overlapping reads
B1 consumer processing all 5 partitions sequentially
C5 consumers in the group, each assigned one partition
DMore consumers than partitions to ensure redundancy
Step-by-Step Solution
Solution:

  1. Step 1: Understand partition assignment rules

    Each partition is assigned to only one consumer in the group.

  2. Step 2: Maximize parallelism

    Having 5 consumers for 5 partitions allows each consumer to process one partition concurrently.

  3. Final Answer:

    5 consumers in the group, each assigned one partition -> Option C

  4. Quick Check:

    Consumers equal to partitions maximize parallelism [OK]
Quick Trick: Match consumers to partitions for max parallelism [OK]
Common Mistakes:
  • Using fewer consumers reduces parallelism
  • Assuming overlapping reads increase throughput
  • Believing more consumers than partitions improves processing

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