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Exam Certified Data Engineer Professional topic 1 question 19 discussion

Actual exam question from Databricks's Certified Data Engineer Professional
Question #: 19
Topic #: 1
[All Certified Data Engineer Professional Questions]

A junior data engineer has been asked to develop a streaming data pipeline with a grouped aggregation using DataFrame df. The pipeline needs to calculate the average humidity and average temperature for each non-overlapping five-minute interval. Events are recorded once per minute per device.
Streaming DataFrame df has the following schema:
"device_id INT, event_time TIMESTAMP, temp FLOAT, humidity FLOAT"
Code block:

Choose the response that correctly fills in the blank within the code block to complete this task.

  • A. to_interval("event_time", "5 minutes").alias("time")
  • B. window("event_time", "5 minutes").alias("time")
  • C. "event_time"
  • D. window("event_time", "10 minutes").alias("time")
  • E. lag("event_time", "10 minutes").alias("time")
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️


Chosen Answer:
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2 weeks, 2 days ago
B. window("event_time", "5 minutes").alias("time") In Structured Streaming, expressing such windows on event-time is simply performing a special grouping using the window() function. For example, counts over 5 minute tumbling (non-overlapping) windows on the eventTime column in the event is as following.
upvoted 1 times
5 months ago
Selected Answer: B
correct B
upvoted 1 times
5 months, 1 week ago
Selected Answer: B
B is correct
upvoted 1 times
7 months, 2 weeks ago
Selected Answer: B
Window of 5 mins
upvoted 2 times
8 months, 1 week ago
Selected Answer: B
B is correct: https://www.databricks.com/blog/2017/05/08/event-time-aggregation-watermarking-apache-sparks-structured-streaming.html
upvoted 1 times
8 months, 4 weeks ago
answer is B
upvoted 2 times
9 months, 2 weeks ago
Selected Answer: B
Correct, B.
upvoted 4 times
Community vote distribution
A (35%)
C (25%)
B (20%)
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