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
Structured Streaming uses two key mechanisms to reliably track processing progress and handle failures:
1. Checkpointing - Stores the current state of the streaming query, including:
- Progress information (which offsets have been processed)
- Aggregation state (for stateful operations)
- Metadata about the query
2. Write-ahead Logs (WAL) - Records the offset ranges being processed in each trigger before the actual processing begins. This ensures:
- Exactly-once processing semantics
- If a failure occurs during processing, the system can replay from the last recorded offset
- No data loss or duplication
Why other options are incorrect:
- Option B: Incorrect - Structured Streaming can and does record offset ranges
- Option C: Replayable sources and idempotent sinks are important concepts but not the specific mechanisms for recording offset ranges
- Option D: Write-ahead logs are correct, but idempotent sinks alone don't track offset ranges
- Option E: Checkpointing is correct, but idempotent sinks don't track offset ranges
The combination of checkpointing and write-ahead logs provides the fault tolerance and exactly-once semantics that Structured Streaming is known for.
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