Databricks-Spark-Assoc Structured Streaming Practice Question
A developer wants to start a Structured Streaming query that reads from a Kafka topic and writes to the console for debugging. The developer uses `writeStream.format("console").start()`. What is the default trigger for this query?
⚠ Common exam trap
Candidates often confuse the default trigger with a processing time trigger of 0 seconds or a once trigger, when the default is actually an unspecified trigger that runs micro-batches back-to-back.
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
✓
Default trigger, which processes data in micro-batches as soon as the previous batch completes, without a fixed interval.
The default trigger in Structured Streaming processes data in micro-batches as soon as the previous batch completes, without a fixed interval. This is the behavior when no trigger is explicitly set. It provides continuous processing with low latency, making it suitable for most streaming use cases. Developers can override this by specifying a processing time, once, or continuous trigger.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Default trigger, which processes data in micro-batches as soon as the previous batch completes, without a fixed interval.
Why this is correct
When no trigger is specified, Structured Streaming uses the default trigger, which processes each micro-batch as soon as the previous one finishes. This provides the lowest latency without a fixed interval. It is the standard behavior for streaming queries that need continuous processing. The developer does not need to set a trigger for this default behavior.
- ✗
Continuous trigger with a 1-second checkpoint interval, which provides low-latency processing.
Why it's wrong here
Continuous trigger is an experimental feature that provides millisecond latency but is not the default. It must be explicitly enabled with `trigger(continuous='1 second')` and has limitations, such as not supporting all operations. The default trigger is micro-batch based, not continuous. Using continuous trigger requires specific configuration and is not automatically applied.
- ✗
Once trigger, which processes all available data in a single batch and then stops.
Why it's wrong here
A once trigger is specified using `trigger(once=True)` and is used for batch-like processing of available data. It is not the default. The default trigger runs continuously, processing new data as it arrives, rather than stopping after one batch. The developer would need to explicitly set the once trigger to achieve that behavior.
- ✗
ProcessingTime trigger with an interval of 0 seconds, which processes data as fast as possible.
Why it's wrong here
The default trigger is not a processing time trigger with 0 seconds. A processing time trigger with 0 seconds would be specified explicitly as `trigger(processingTime='0 seconds')`, which is not the default. The default trigger processes data in micro-batches as soon as the previous batch completes, but it is not defined as a processing time trigger with 0 seconds; it is simply the absence of a trigger specification.
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JA
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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