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PROFESSIONAL-DATA-ENGINEER · Question #362
You are running a streaming pipeline with Dataflow and are using hopping windows to group the data as the data arrives. You noticed that some data is arriving late but is not being marked as late…
The correct answer is A. Use watermarks to define the expected data arrival window. Allow late data as it arrives. You've hit your limit · resets 5am (America/New_York)
Submitted by viktor_hu· Mar 30, 2026Building and operationalizing data processing systems
Question
You are running a streaming pipeline with Dataflow and are using hopping windows to group the data as the data arrives. You noticed that some data is arriving late but is not being marked as late data, which is resulting in inaccurate aggregations downstream. You need to find a solution that allows you to capture the late data in the appropriate window. What should you do?
Options
- AUse watermarks to define the expected data arrival window. Allow late data as it arrives.
- BChange your windowing function to tumbling windows to avoid overlapping window periods.
- CChange your windowing function to session windows to define your windows based on certain activity.
- DExpand your hopping window so that the late data has more time to arrive within the grouping.
How the community answered
(20 responses)- A65% (13)
- B5% (1)
- C20% (4)
- D10% (2)
Explanation
You've hit your limit · resets 5am (America/New_York)
Topics
#Dataflow watermarks#late data handling#hopping windows#streaming aggregations
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