Answer: Stream-static join

## Explanation **Stream-static join** is the correct answer because: - **Stateless tables** in streaming contexts don't maintain state information across processing windows - **Stream-static join** involves joining a streaming dataset with a static (non-streaming) reference table - This operation doesn't require maintaining state about the streaming data since the static table is fixed and doesn't change during processing - The state dimension remains limited because only the static table data needs to be loaded, not historical streaming data **Why other options are incorrect:** - **A. Stream-stream join**: Requires maintaining state for both streaming sources to handle late-arriving data and ensure correct joins - **C. Stateful aggregation**: By definition maintains state (counts, sums, etc.) across processing windows - **D. Drop duplicates**: Requires maintaining state to track which records have already been seen to identify duplicates Stream-static joins are commonly used for enrichment operations where streaming data is joined with reference/lookup tables, making them suitable for stateless processing scenarios where state maintenance needs to be minimized.

Author: LeetQuiz .