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Answer: Apply a last-write-wins policy, using event timestamps to resolve conflicts during ingestion.
Applying a last-write-wins policy using event timestamps to resolve conflicts during ingestion is the most efficient technique for ensuring data accuracy and consistency in real-time data ingestion scenarios. This approach prioritizes the most recent data based on event timestamps, ensuring the latest information is captured while minimizing data inconsistencies. Other methods, such as implementing a two-phase commit protocol or utilizing streaming stateful operations, may introduce unnecessary complexity or performance issues. Staging data in a raw format for periodic batch reconciliation can lead to delays, making it unsuitable for real-time requirements.
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In the context of real-time data ingestion into a lakehouse from multiple sources where conflicts are likely, which technique ensures data accuracy and consistency without significantly degrading performance?
A
Stage incoming data in a raw format, employing periodic batch reconciliation jobs to resolve conflicts and merge data.
B
Utilize streaming stateful operations to detect and resolve conflicts based on predefined business rules.
C
Apply a last-write-wins policy, using event timestamps to resolve conflicts during ingestion.
D
Implement a two-phase commit protocol across the ingestion pipeline to ensure atomicity and consistency of writes.
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