Databricks-Spark-Assoc Structured Streaming Practice Question
A developer is writing a Structured Streaming query that reads from a JSON file source and writes to the console for debugging. The query uses `outputMode("append")`. Which statement describes the output behavior?
⚠ Common exam trap
The trap here is mixing up append mode with complete or update mode, especially when aggregations are not involved.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Only new rows added since the last micro-batch are written to the console.
Append mode in Structured Streaming outputs only new rows that are added to the result table since the last micro-batch. For a simple file source without aggregations, each incoming record is emitted once. This is ideal for debugging because you see data as it arrives. Complete mode rewrites the whole table, and update mode emits only updated rows, neither of which matches the described behavior.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
No output is produced until the query is stopped.
Why it's wrong here
Append mode does not buffer all output until the query stops. It writes new rows at each micro-batch. The console sink will display rows as they are processed. Waiting until the query stops would defeat the purpose of streaming and debugging. This option incorrectly describes the streaming behavior.
- ✓
Only new rows added since the last micro-batch are written to the console.
Why this is correct
In append mode, only new rows that have been added to the result table since the last trigger are output. For a non-aggregated streaming query, this means each new record is emitted once. This matches the typical debugging use case where you want to see incoming data as it arrives. Therefore this statement correctly describes append mode behavior.
- ✗
Only rows that have been updated since the last micro-batch are written to the console.
Why it's wrong here
Update mode outputs only rows that were updated in the result table since the last trigger. This is different from append mode, which outputs only newly appended rows. For a non-aggregated query, append and update may behave similarly, but update mode is specifically for aggregations. The scenario does not specify updates, so this option is not accurate.
- ✗
The entire result table is rewritten to the console after every micro-batch.
Why it's wrong here
Rewriting the entire result table is the behavior of complete mode, not append mode. Complete mode is used for aggregations and outputs all rows every time. Append mode only outputs new rows. Using complete mode with a console sink would produce increasingly large output, which is not the case here. This option misidentifies the output mode.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
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