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Question 172

You are analyzing the price of a company's stock. Every 5 seconds, you need to compute a moving average of the past 30 seconds' worth of data. You are reading data from Pub/Sub and using DataFlow to conduct the analysis. How should you set up your windowed pipeline?

  • A. Use a fixed window with a duration of 5 seconds. Emit results by setting the following trigger: AfterProcessingTime.pastFirstElementInPane().plusDelayOf (Duration.standardSeconds(30))
  • B. Use a fixed window with a duration of 30 seconds. Emit results by setting the following trigger: AfterWatermark.pastEndOfWindow().plusDelayOf (Duration.standardSeconds(5))
  • C. Use a sliding window with a duration of 5 seconds. Emit results by setting the following trigger: AfterProcessingTime.pastFirstElementInPane().plusDelayOf (Duration.standardSeconds(30))
  • D. Use a sliding window with a duration of 30 seconds and a period of 5 seconds. Emit results by setting the following trigger: AfterWatermark.pastEndOfWindow ()

Sliding Window: Since you need to compute a moving average of the past 30 seconds' worth of data every 5 seconds, a sliding window is appropriate. A sliding window allows overlapping intervals and is well-suited for computing rolling aggregates.

Window Duration: The window duration should be set to 30 seconds to cover the required 30 seconds' worth of data for the moving average calculation. Window Period: The window period or sliding interval should be set to 5 seconds to move the window every 5 seconds and recalculate the moving average with the latest data.

Trigger: The trigger should be set to AfterWatermark.pastEndOfWindow() to emit the computed moving average results when the watermark advances past the end of the window. This ensures that all data within the window is considered before emitting the result.

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