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Databricks-Certified-Professional-Data-Engineer Exam Dumps : Databricks Certified Data Engineer Professional Exam

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Databricks Certified Data Engineer Professional Exam Questions and Answers

Question 1

A developer has successfully configured credential for Databricks Repos and cloned a remote Git repository. Hey don not have privileges to make changes to the main branch, which is the only branch currently visible in their workspace.

Use Response to pull changes from the remote Git repository commit and push changes to a branch that appeared as a changes were pulled.

Options:

A.

Use Repos to merge all differences and make a pull request back to the remote repository.

B.

Use repos to merge all difference and make a pull request back to the remote repository.

C.

Use Repos to create a new branch commit all changes and push changes to the remote Git repertory.

D.

Use repos to create a fork of the remote repository commit all changes and make a pull request on the source repository

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Question 2

An upstream system has been configured to pass the date for a given batch of data to the Databricks Jobs API as a parameter. The notebook to be scheduled will use this parameter to load data with the following code:

df = spark.read.format("parquet").load(f"/mnt/source/(date)")

Which code block should be used to create the date Python variable used in the above code block?

Options:

A.

date = spark.conf.get("date")

B.

input_dict = input()

date= input_dict["date"]

C.

import sys

date = sys.argv[1]

D.

date = dbutils.notebooks.getParam("date")

E.

dbutils.widgets.text("date", "null")

date = dbutils.widgets.get("date")

Question 3

The marketing team is looking to share data in an aggregate table with the sales organization, but the field names used by the teams do not match, and a number of marketing specific fields have not been approval for the sales org.

Which of the following solutions addresses the situation while emphasizing simplicity?

Options:

A.

Create a view on the marketing table selecting only these fields approved for the sales team alias the names of any fields that should be standardized to the sales naming conventions.

B.

Use a CTAS statement to create a derivative table from the marketing table configure a production jon to propagation changes.

C.

Add a parallel table write to the current production pipeline, updating a new sales table that varies as required from marketing table.

D.

Create a new table with the required schema and use Delta Lake's DEEP CLONE functionality to sync up changes committed to one table to the corresponding table.