Google Cloud Certified – Professional Data Engineer – Practice Exam (Question 50)
Question 1
What are two of the characteristics of using online prediction rather than batch prediction?
- A. It is optimized to handle a high volume of data instances in a job and to run more complex models.
- B. Predictions are returned in the response message.
- C. Predictions are written to output files in a Google Cloud Storage location that you specify.
- D. It is optimized to minimize the latency of serving predictions.
Correct Answer: B, D
Online prediction:
– .Optimized to minimize the latency of serving predictions.
– .Predictions returned in the response message.
Batch prediction:
-.Optimized to handle a high volume of instances in a job and to run more complex models.
– .Predictions written to output files in a Google Cloud Storage location that you specify.
Reference contents:
– Prediction overview > Online prediction versus batch prediction
Question 2
What Google Cloud Dataflow concept determines when a Window’s contents should be output based on certain criteria being met?
- A. Sessions
- B. OutputCriteria
- C. Windows
- D. Triggers
Correct Answer: D
Triggers control when the elements for a specific key and window are output. As elements arrive, they are put into one or more windows by a Window transform and its associated WindowFn, and then passed to the associated Trigger to determine if the Windows contents should be output.
Reference contents:
– Trigger (Google Cloud Dataflow SDK 1.9.1 API)
Question 3
What is the general recommendation when designing your row keys for a Google Cloud Bigtable schema?
- A. Include multiple time series values within the row key.
- B. Keep the row kept as an 8 bit integer.
- C. Keep your row key reasonably short.
- D. Keep your row key as long as the field permits.
