Databricks Certified Data Engineer - Associate
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In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?
Real Exam
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KKeng
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A
Checkpointing and Write-ahead Logs
B
Structured Streaming cannot record the offset range of the data being processed in each trigger.
C
Replayable Sources and Idempotent Sinks
D
Write-ahead Logs and Idempotent Sinks
E
Checkpointing and Idempotent Sinks
Explanation:
Explanation
Correct Answer: A (Checkpointing and Write-ahead Logs)
Structured Streaming uses two key mechanisms to reliably track processing progress and handle failures:
1. Checkpointing
- Purpose: Periodically saves the state of the streaming computation to durable storage
- Function: If the streaming computation fails, it can be restarted from the last checkpoint and resume processing from where it left off
- What it stores: Metadata about the streaming query, including the progress of processing (offsets)
2. Write-ahead Logs (WAL)
- Purpose: Records all changes made to a dataset before they are applied
- Function: Allows Structured Streaming to recover from failures by replaying the write-ahead logs from the last checkpoint
- How it works: Ensures that no data is lost even if the system crashes between checkpoints
Why Other Options Are Incorrect:
B: Incorrect - Structured Streaming can and does record offset ranges through checkpointing and WAL.
C: While replayable sources and idempotent sinks are important concepts in streaming systems, they are not the primary mechanisms Spark uses to record offset ranges for failure recovery.
D: Write-ahead logs are correct, but idempotent sinks alone don't track offset ranges for recovery.
E: Checkpointing is correct, but idempotent sinks handle duplicate data processing rather than tracking offset ranges.
Key Insight:
The combination of checkpointing (for periodic state saving) and write-ahead logs (for continuous change recording) provides the reliability guarantees needed for Structured Streaming to handle failures while maintaining exactly-once processing semantics.
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