[Aug 25, 2023] Databricks-Certified-Data-Engineer-Associate Dumps PDF and Test Engine Exam Questions – TestKingIT [Q27-Q41]

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[Aug 25, 2023] Databricks-Certified-Data-Engineer-Associate Dumps PDF and Test Engine Exam Questions – TestKingIT

Verified Databricks-Certified-Data-Engineer-Associate exam dumps Q&As with Correct 47 Questions and Answers

The Databricks Certified Data Engineer Associate Exam covers a range of topics related to data engineering, including data ingestion, ETL (extract, transform, load) processes, data modeling, and data warehousing. Databricks-Certified-Data-Engineer-Associate exam also covers Databricks-specific tools and technologies, such as Databricks Delta Lake and Databricks Runtime. Passing the exam requires a deep understanding of these topics and the ability to apply that knowledge in real-world scenarios. Successful candidates will have demonstrated their ability to design and implement reliable, scalable, and efficient data pipelines using Databricks.

Q27. Which of the following describes the storage organization of a Delta table?

Delta tables are stored in a single file that contains data, history, metadata, and other attributes.

Delta tables store their data in a single file and all metadata in a collection of files in a separate location.

Delta tables are stored in a collection of files that contain data, history, metadata, and other attributes.

Delta tables are stored in a collection of files that contain only the data stored within the table.

Delta tables are stored in a single file that contains only the data stored within the table.

Q28. A data analyst has a series of queries in a SQL program. The data analyst wants this program to run every day.
They only want the final query in the program to run on Sundays. They ask for help from the data engineering team to complete this task.
Which of the following approaches could be used by the data engineering team to complete this task?

They could submit a feature request with Databricks to add this functionality.

They could wrap the queries using PySpark and use Python’s control flow system to determine when to run the final query.

They could only run the entire program on Sundays.

They could automatically restrict access to the source table in the final query so that it is only accessible on Sundays.

They could redesign the data model to separate the data used in the final query into a new table.

Q29. A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start.
Which of the following actions can the data engineer perform to improve the start up time for the clusters used for the Job?

They can use endpoints available in Databricks SQL

They can use jobs clusters instead of all-purpose clusters

They can configure the clusters to be single-node

They can use clusters that are from a cluster pool

They can configure the clusters to autoscale for larger data sizes

Q30. A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Q31. Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?

Q32. A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?

SELECT * FROM sales

There is no way to share data between PySpark and SQL.

spark.sql(“sales”)

spark.delta.table(“sales”)

spark.table(“sales”)

Q33. Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?

The ability to manipulate the same data using a variety of languages

The ability to collaborate in real time on a single notebook

The ability to set up alerts for query failures

The ability to support batch and streaming workloads

The ability to distribute complex data operations

Q34. A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.
Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INNER JOIN SELECT * FROM april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
UNION SELECT * FROM april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
OUTER JOIN SELECT * FROM april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INTERSECT SELECT * from april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
MERGE SELECT * FROM april_transactions;

Q35. A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

They can ensure the dashboard’s SQL endpoint matches each of the queries’ SQL endpoints.

They can set up the dashboard’s SQL endpoint to be serverless.

They can turn on the Auto Stop feature for the SQL endpoint.

They can reduce the cluster size of the SQL endpoint.

They can ensure the dashboard’s SQL endpoint is not one of the included query’s SQL endpoint.

Q36. A data engineer has left the organization. The data team needs to transfer ownership of the data engineer’s Delta tables to a new data engineer. The new data engineer is the lead engineer on the data team.
Assuming the original data engineer no longer has access, which of the following individuals must be the one to transfer ownership of the Delta tables in Data Explorer?

Databricks account representative

This transfer is not possible

Workspace administrator

New lead data engineer

Original data engineer

Q37. An engineering manager wants to monitor the performance of a recent project using a Databricks SQL query.
For the first week following the project’s release, the managerwants the query results to be updated every minute. However, the manager is concerned that the compute resources used for the query will be left running and cost the organization a lot of money beyond the first week of the project’s release.
Which of the following approaches can the engineering team use to ensure the query does not cost the organization any money beyond the first week of the project’s release?

They can set a limit to the number of DBUs that are consumed by the SQL Endpoint.

They can set the query’s refresh schedule to end after a certain number of refreshes.

They cannot ensure the query does not cost the organization money beyond the first week of the project’s release.

They can set a limit to the number of individuals that are able to manage the query’s refresh schedule.

They can set the query’s refresh schedule to end on a certain date in the query scheduler.

Q38. A data engineer has realized that they made a mistake when making a daily update to a table. They need to use Delta time travel to restore the table to a version that is 3 days old. However, when the data engineer attempts to time travel to the older version, they are unable to restore the data because the data files have been deleted.
Which of the following explains why the data files are no longer present?

The VACUUM command was run on the table

The TIME TRAVEL command was run on the table

The DELETE HISTORY command was run on the table

The OPTIMIZE command was nun on the table

The HISTORY command was run on the table

Q39. A data engineer is maintaining a data pipeline. Upon data ingestion, the data engineer notices that the source data is starting to have a lower level of quality. The data engineer would like to automate the process of monitoring the quality level.
Which of the following tools can the data engineer use to solve this problem?

Unity Catalog

Data Explorer

Delta Lake

Delta Live Tables

Auto Loader

Q40. A data engineer wants to create a data entity from a couple of tables. The data entity must be used by other data engineers in other sessions. It also must be saved to a physical location.
Which of the following data entities should the data engineer create?

Database

Function

View

Temporary view

Table

Q41. A data engineer needs to determine whether to use the built-in Databricks Notebooks versioning or version their project using Databricks Repos.
Which of the following is an advantage of using Databricks Repos over the Databricks Notebooks versioning?

Databricks Repos automatically saves development progress

Databricks Repos supports the use of multiple branches

Databricks Repos allows users to revert to previous versions of a notebook

Databricks Repos provides the ability to comment on specific changes

Databricks Repos is wholly housed within the Databricks Lakehouse Platform

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To prepare for the certification exam, candidates can take advantage of various study resources, including online courses, study guides, and practice exams. The GAQM website also provides a detailed exam blueprint that outlines the topics and subtopics covered in the exam. Candidates can use this blueprint to create a study plan and focus their preparation efforts on the areas where they need the most improvement.

GAQM Databricks-Certified-Data-Engineer-Associate Test Engine PDF – All Free Dumps: https://www.testkingit.com/GAQM/latest-Databricks-Certified-Data-Engineer-Associate-exam-dumps.html