Answer: trigger(once=True)

## Explanation In Apache Spark Structured Streaming, when you want to execute a streaming query that processes all available data in a **single micro-batch** and then stops, you should use the `trigger(once=True)` option. ### Why Option A is correct: - `trigger(once=True)` is specifically designed for this use case - It processes all available data in one batch and then terminates the streaming query - This is commonly used for batch-like processing using the streaming framework ### Why other options are incorrect: - **B. trigger(continuous="once")**: This syntax is incorrect. Continuous processing mode doesn't use "once" as a parameter - **C. processingTime("once")**: This is invalid syntax. `processingTime` expects a time interval string like "1 second" or "5 minutes" - **D. trigger(processingTime="once")**: Invalid syntax - `processingTime` trigger expects a time interval, not the string "once" - **E. processingTime(1)**: This would trigger the query every 1 millisecond, creating continuous micro-batches, not a single batch ### Key Points: - `trigger(once=True)` is the proper way to execute a one-time batch processing using Structured Streaming - This is useful for scenarios where you want to process all available data at once and then stop - The query will process all data that has accumulated since the last trigger and then terminate

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