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H13-711_V3.5 · Question #344

In Flink, the checkpoint mechanism can ensure that when the application fails during operation, it recovers from a certain checkpoint. During this process, stream snapshots are created sequentially…

The correct answer is A. True. Option A is correct because Flink's checkpoint mechanism uses checkpoint barriers - special markers injected into the data stream that flow downstream in the exact same order as the incoming data records. When a checkpoint is triggered, these barriers travel through the stream…

Big Data Processing Technologies (MapReduce, Spark, Hive)

Question

In Flink, the checkpoint mechanism can ensure that when the application fails during operation, it recovers from a certain checkpoint. During this process, stream snapshots are created sequentially according to the order of data inflow.

Options

  • ATrue
  • BFalse

How the community answered

(33 responses)
  • A
    76% (25)
  • B
    24% (8)

Explanation

Option A is correct because Flink's checkpoint mechanism uses checkpoint barriers - special markers injected into the data stream that flow downstream in the exact same order as the incoming data records. When a checkpoint is triggered, these barriers travel through the stream sequentially, causing each operator to snapshot its state only after processing all records that arrived before the barrier, preserving strict data-order consistency.

Since the barriers respect the inflow order of data, the resulting snapshots capture a globally consistent state aligned with that order - meaning recovery replays data from a well-defined, ordered point, not an arbitrary one. Option B (False) is incorrect because it would imply snapshots could be taken in arbitrary or out-of-order fashion, which would break consistency guarantees and make recovery unreliable.

Memory tip: Think of a checkpoint barrier like a "timestamp flag" racing through a conveyor belt of data - it never overtakes the items ahead of it, so every snapshot is always taken in line with the data flow order.

Topics

#Flink Checkpoint#Stream Processing Fault Tolerance#Barrier Ordering#Data Consistency

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