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PROFESSIONAL-DATA-ENGINEER · Question #145
Your company receives both batch- and stream-based event data. You want to process the data using Google Cloud Dataflow over a predictable time period. However, you realize that in some instances data
The correct answer is C. Use watermarks and timestamps to capture the lagged data.. Explanation/Reference: A watermark is a threshold that indicates when Dataflow expects all of the data in a window to have arrived. If new data arrives with a timestamp that's in the window but older than the watermark, the data is considered late data.
Submitted by jaden.t· Mar 30, 2026Designing data processing systems
Question
Your company receives both batch- and stream-based event data. You want to process the data using Google Cloud Dataflow over a predictable time period. However, you realize that in some instances data can arrive late or out of order. How should you design your Cloud Dataflow pipeline to handle data that is late or out of order?
Options
- ASet a single global window to capture all the data.
- BSet sliding windows to capture all the lagged data.
- CUse watermarks and timestamps to capture the lagged data.
- DEnsure every datasource type (stream or batch) has a timestamp, and use the timestamps to define the logic for lagged data.
How the community answered
(43 responses)- A7% (3)
- B14% (6)
- C74% (32)
- D5% (2)
Explanation
Explanation/Reference: A watermark is a threshold that indicates when Dataflow expects all of the data in a window to have arrived. If new data arrives with a timestamp that's in the window but older than the watermark, the data is considered late data.
Topics
#Cloud Dataflow#watermarks#timestamps#late data handling
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