Free Databricks-Certified-Professional-Data-Engineer Exam Braindumps
Certified Data Engineer Professional Questions 169–176 (page: 23)

Updated On: 16-Apr-2026

A data engineer, User A, has promoted a new pipeline to production by using the REST API to programmatically create several jobs. A DevOps engineer, User B, has configured an external orchestration tool to trigger job runs through the REST API. Both users authorized the REST API calls using their personal access tokens.

Which statement describes the contents of the workspace audit logs concerning these events?

  1. Because the REST API was used for job creation and triggering runs, a Service Principal will be automatically used to identify these events.
  2. Because User A created the jobs, their identity will be associated with both the job creation events and the job run events.
  3. Because these events are managed separately, User A will have their identity associated with the job creation events and User B will have their identity associated with the job run events.
  4. Because the REST API was used for job creation and triggering runs, user identity will not be captured in the audit logs.

Answer(s): C


Reference:



A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.

In which location can one review the timeline for cluster resizing events?

  1. Workspace audit logs
  2. Driver's log file
  3. Ganglia
  4. Cluster Event Log

Answer(s): D


Reference:



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

  1. The five Minute Load Average remains consistent/flat
  2. CPU Utilization is around 75%
  3. Network I/O never spikes
  4. Total Disk Space remains constant

Answer(s): B


Reference:



The data engineer is using Spark's MEMORY_ONLY storage level.

Which indicators should the data engineer look for in the Spark UI's Storage tab to signal that a cached table is not performing optimally?

  1. On Heap Memory Usage is within 75% of Off Heap Memory Usage
  2. The RDD Block Name includes the "*" annotation signaling a failure to cache
  3. Size on Disk is > 0
  4. The number of Cached Partitions > the number of Spark Partitions

Answer(s): C



Review the following error traceback:



Which statement describes the error being raised?

  1. There is a syntax error because the heartrate column is not correctly identified as a column.
  2. There is no column in the table named heartrateheartrateheartrate
  3. There is a type error because a column object cannot be multiplied.
  4. There is a type error because a DataFrame object cannot be multiplied.

Answer(s): B



What is a method of installing a Python package scoped at the notebook level to all nodes in the currently active cluster?

  1. Run source env/bin/activate in a notebook setup script
  2. Install libraries from PyPI using the cluster UI
  3. Use %pip install in a notebook cell
  4. Use %sh pip install in a notebook cell

Answer(s): C


Reference:



What is the first line of a Databricks Python notebook when viewed in a text editor?

  1. %python
  2. // Databricks notebook source
  3. # Databricks notebook source
  4. -- Databricks notebook source

Answer(s): C


Reference:



Incorporating unit tests into a PySpark application requires upfront attention to the design of your jobs, or a potentially significant refactoring of existing code.

Which benefit offsets this additional effort?

  1. Improves the quality of your data
  2. Validates a complete use case of your application
  3. Troubleshooting is easier since all steps are isolated and tested individually
  4. Ensures that all steps interact correctly to achieve the desired end result

Answer(s): C



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