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The Databricks Certified Professional Data Engineer exam is designed to test the skills and knowledge of individuals who work with big data and cloud computing technologies. This exam is primarily focused on assessing candidates’ abilities to design, build, and maintain big data solutions using the Apache Spark platform. This certification is highly valued in the industry and can help individuals demonstrate their proficiency in managing big data projects.

Passing the Databricks Certified Professional Data Engineer exam can be a significant achievement for individuals pursuing a career in big data and cloud computing. This certification demonstrates that the candidate has a deep understanding of Apache Spark and can apply that knowledge to design and implement scalable big data solutions. Additionally, this certification is recognized by many companies in the industry and can improve the candidate's chances of obtaining a high-paying job.

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Databricks Certified Professional Data Engineer Exam Sample Questions (Q119-Q124):

NEW QUESTION # 119
Once a cluster is deleted, below additional actions need to performed by the administrator

A. Remove logs
B. Remove virtual machines but storage and networking are automatically dropped
C. No action needs to be performed. All resources are automatically removed.
D. Remove networking but Virtual machines and storage disks are automatically dropped
E. Drop storage disks but Virtual machines and networking are automatically dropped

Answer: C

Explanation:
Explanation
What is Delta?
Delta lake is
* Open source
* Builds up on standard data format
* Optimized for cloud object storage
* Built for scalable metadata handling
Delta lake is not
* Proprietary technology
* Storage format
* Storage medium
* Database service or data warehouse

NEW QUESTION # 120
A junior data engineer has ingested a JSON file into a table raw_table with the following schema:
1. cart_id STRING,
2. items ARRAY<item_id:STRING>
The junior data engineer would like to unnest the items column in raw_table to result in a new table with the
following schema:
1.cart_id STRING,
2.item_id STRING
Which of the following commands should the junior data engineer run to complete this task?

A. 1. SELECT cart_id, explode(items) AS item_id
2. FROM raw_table;
B. 1. SELECT cart_id, flatten(items) AS item_id
2. FROM raw_table;
C. 1. SELECT cart_id, filter(items) AS item_id
2. FROM raw_table;
D. 1. SELECT cart_id, slice(items) AS item_id
2. FROM raw_table;
E. 1. SELECT cart_id, reduce(items) AS item_id
2. FROM raw_table;

Answer: A

NEW QUESTION # 121
A data engineer is overwriting data in a table by deleting the table and recreating the table. Another data
engineer suggests that this is inefficient and the table should simply be overwritten instead.
Which of the following reasons to overwrite the table instead of deleting and recreating the table is incorrect?

A. Overwriting a table results in a clean table history for logging and audit purposes
B. Overwriting a table maintains the old version of the table for Time Travel
C. Overwriting a table allows for concurrent queries to be completed while in progress
D. Overwriting a table is efficient because no files need to be deleted
E. Overwriting a table is an atomic operation and will not leave the table in an unfinished state

Answer: A

NEW QUESTION # 122
Which of the following is correct for the global temporary view?

A. global temporary views can be accessed across many clusters
B. global temporary views can be still accessed even if the notebook is detached and at-tached
C. global temporary views are created in a database called temp database
D. global temporary views cannot be accessed once the notebook is detached and attached
E. global temporary views can be still accessed even if the cluster is restarted

Answer: B

Explanation:
Explanation
The answer is global temporary views can be still accessed even if the notebook is detached and attached There are two types of temporary views that can be created Local and Global
* A local temporary view is only available with a spark session, so another notebook in the same cluster can not access it. if a notebook is detached and reattached local temporary view is lost.
* A global temporary view is available to all the notebooks in the cluster, even if the notebook is detached and reattached it can still be accessible but if a cluster is restarted the global temporary view is lost.

NEW QUESTION # 123
What is the type of table created when you issue SQL DDL command CREATE TABLE sales (id int, units int)

A. External Table
B. Query fails due to missing format
C. Managed Parquet table
D. Query fails due to missing location
E. Managed Delta table

Answer: E

Explanation:
Explanation
Answer is Managed Delta table
Anytime a table is created without the Location keyword it is considered a managed table, by de-fault all managed tables DELTA tables Syntax CREATE TABLE table_name ( column column_data_type...)

NEW QUESTION # 124
......

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