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Free CERTIFIED-DATA-ENGINEER-PROFESSIONAL – Databricks CERTIFIED-DATA-ENGINEER-PROFESSIONAL Practice Test Question

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Showing 16–18 of 26 questions

Question 16 (Topic 1)

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: Which line of code correctly fills in the blank within the code block to complete this task?

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  • ○ to_interval("event_time", "5 minutes").alias("time")
  • ○ window("event_time", "5 minutes").alias("time")
  • ○ "event_time"
  • ○ lag("event_time", "10 minutes").alias("time")
Question 17 (Topic 1)

Which statement describes Delta Lake optimized writes?

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  • ○ Before a Jobs cluster terminates, OPTIMIZE is executed on all tables modified during the most recent job.
  • ○ An asynchronous job runs after the write completes to detect if files could be further compacted; if yes, an OPTIMIZE job is executed toward a default of 1 GB.
  • ○ A shuffle occurs prior to writing to try to group similar data together resulting in fewer files instead of each executor writing multiple files based on directory partitions.
  • ○ Optimized writes use logical partitions instead of directory partitions; because partition boundaries are only represented in metadata, fewer small files are written.
Question 18 (Topic 1)

When evaluating the Ganglia Metrics for a given cluster with 3 executor nodes, which indicator would signal proper utilization of the VM's resources?

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  • ○ The five Minute Load Average remains consistent/flat
  • ○ CPU Utilization is around 75%
  • ○ Network I/O never spikes
  • ○ Total Disk Space remains constant