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H13-711_V3.5 · Question #332

Synchronize data between partition replication in Kafka. Copying data from the leader of the partition to the follower requires a thread (replicationFetcherThread), and the follower (a follower is…

The correct answer is A. True. A is correct because Kafka's replication mechanism works exactly as described: each follower broker runs a ReplicaFetcherThread that actively pulls (fetches) messages from the partition leader in batches, mirroring how a consumer reads data. This pull-based model is intentional…

Big Data Processing Technologies (MapReduce, Spark, Hive)

Question

Synchronize data between partition replication in Kafka. Copying data from the leader of the partition to the follower requires a thread (replicationFetcherThread), and the follower (a follower is equivalent to a consumer) actively pulls messages from the leader in batches, which greatly improves the throughput.

Options

  • ATrue
  • BFalse

How the community answered

(56 responses)
  • A
    73% (41)
  • B
    27% (15)

Explanation

A is correct because Kafka's replication mechanism works exactly as described: each follower broker runs a ReplicaFetcherThread that actively pulls (fetches) messages from the partition leader in batches, mirroring how a consumer reads data. This pull-based model is intentional - followers control their own fetch rate, preventing the leader from overwhelming slow followers.

B is wrong because there is no push-based model where the leader sends data to followers; the fetch is always initiated by the follower, making the statement fully accurate and leaving no grounds for "False."

Memory tip: Think of followers as "internal consumers" - just like a Kafka consumer polls the broker for messages in batches, a follower replica polls its leader using the same fetch mechanism, just with a dedicated replication thread rather than a consumer client.

Topics

#Kafka replication#leader-follower architecture#batch pull mechanism#throughput optimization

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