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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is a prestigious certification exam that is designed for professionals who have experience in designing and implementing big data solutions using Databricks platform. Databricks Certified Data Engineer Associate Exam certification exam is ideal for data engineers, architects, developers, and data scientists who want to demonstrate their skills and knowledge in working with Databricks for big data processing and analytics.

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q57-Q62):

NEW QUESTION # 57
A new data engineering team team has been assigned to an ELT project. The new data engineering team will need full privileges on the table sales to fully manage the project.
Which command can be used to grant full permissions on the database to the new data engineering team?

A. GRANT SELECT CREATE MODIFY ON TABLE sales TO team;
B. GRANT SELECT ON TABLE sales TO team;
C. grant all privileges on table sales TO team;
D. GRANT ALL PRIVILEGES ON TABLE team TO sales;

Answer: C

Explanation:
To grant full privileges on a table such as 'sales' to a group like 'team', the correct SQL command in Databricks is:
GRANT ALL PRIVILEGES ON TABLE sales TO team;
This command assigns all available privileges, including SELECT, INSERT, UPDATE, DELETE, and any other data manipulation or definition actions, to the specified team. This is typically necessary when a team needs full control over a table to manage and manipulate it as part of a project or ongoing maintenance.
Reference:
Databricks documentation on SQL permissions: SQL Permissions in Databricks

NEW QUESTION # 58
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The code block used by the data engineer is below:

If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?

A. trigger(availableNow=True)
B. trigger(parallelBatch=True)
C. trigger(continuous="once")
D. processingTime(1)
E. trigger(processingTime="once")

Answer: A

Explanation:
Explanation
https://stackoverflow.com/questions/71061809/trigger-availablenow-for-delta-source-streaming-queries-in-pyspa

NEW QUESTION # 59
A data engineer wants to create a new table containing the names of customers that live in France.
They have written the following command:

A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (PII).
Which of the following lines of code fills in the above blank to successfully complete the task?

A. There is no way to indicate whether a table contains PII.
B. "COMMENT PII"
C. PII
D. TBLPROPERTIES PII
E. COMMENT "Contains PII"

Answer: D

NEW QUESTION # 60
A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE. Three datasets are defined against Delta Lake table sources using LIVE TABLE.
The table is configured to run in Production mode using the Continuous Pipeline Mode.
Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?

A. All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated.
B. All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing.
C. All datasets will be updated once and the pipeline will persist without any processing. The compute resources will persist but go unused.
D. All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will be deployed for the update and terminated when the pipeline is stopped.
E. All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing.

Answer: B

Explanation:
Explanation
In a Delta Live Table pipeline running in Continuous Pipeline Mode, when you click Start to update the pipeline, the following outcome is expected: All datasets defined using STREAMING LIVE TABLE and LIVE TABLE against Delta Lake table sources will be updated at set intervals. The compute resources will be deployed for the update process and will be active during the execution of the pipeline. The compute resources will be terminated when the pipeline is stopped or shut down. This mode allows for continuous and periodic updates to the datasets as new data arrives or changes in the underlying Delta Lake tables occur. The compute resources are provisioned and utilized during the update intervals to process the data and perform the necessary operations.

NEW QUESTION # 61
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?

A. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
OUTER JOIN SELECT * FROM april_transactions;
B. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
MERGE SELECT * FROM april_transactions;
C. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INTERSECT SELECT * from april_transactions;
D. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INNER JOIN SELECT * FROM april_transactions;
E. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
UNION SELECT * FROM april_transactions;

Answer: E

Explanation:
Explanation
To create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records, you should use the UNION operator, as shown in option B. This operator combines the result sets of the two tables while automatically removing duplicate records.

NEW QUESTION # 62
......

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q57-Q62):

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