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Databricks-Certified-Data-Engineer-Associate Exam Braindumps & Databricks-Certified-Data-Engineer-Associate Origination Questions & Databricks-Certified-Data-Engineer-Associate Study Guide

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The Databricks Databricks-Certified-Data-Engineer-Associate exam is conducted online and consists of 80 multiple-choice questions. The duration of the exam is 2 hours, and candidates must achieve a minimum score of 60% to pass. Databricks-Certified-Data-Engineer-Associate exam fee is $300, and candidates can schedule their exam at any time through the GAQM website. Databricks Certified Data Engineer Associate Exam certification is valid for three years and can be renewed by passing the latest version of the exam.

Databricks-Certified-Data-Engineer-Associate exam is an essential certification for data engineers who work with Databricks. Databricks-Certified-Data-Engineer-Associate Exam measures the candidate's knowledge, skills, and abilities in Databricks architecture, data ingestion, data processing, data engineering, data storage, and data management. Databricks Certified Data Engineer Associate Exam certification is recognized globally and is a valuable asset for data engineers who want to advance their careers and demonstrate their proficiency in Databricks.

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q71-Q76):

NEW QUESTION # 71
A data engineer is attempting to drop a Spark SQL table my_table and runs the following command:
DROP TABLE IF EXISTS my_table;
After running this command, the engineer notices that the data files and metadata files have been deleted from the file system.
Which of the following describes why all of these files were deleted?

A. The table's data was larger than 10 GB
B. The table's data was smaller than 10 GB
C. The table did not have a location
D. The table was managed
E. The table was external

Answer: D

Explanation:
Explanation
managed tables files and metadata are managed by metastore and will be deleted when the table is dropped .
while external tables the metadata is stored in a external location. hence when a external table is dropped you clear off only the metadata and the files (data) remain.

NEW QUESTION # 72
Which query is performing a streaming hop from raw data to a Bronze table?

Answer: C

Explanation:
The query performing a streaming hop from raw data to a Bronze table is identified by using the Spark streaming read capability and then writing to a Bronze table. Let's analyze the options:
Option A: Utilizes .writeStream but performs a complete aggregation which is more characteristic of a roll-up into a summarized table rather than a hop into a Bronze table.
Option B: Also uses .writeStream but calculates an average, which again does not typically represent the raw to Bronze transformation, which usually involves minimal transformations.
Option C: This uses a basic .write with .mode("append") which is not a streaming operation, and hence not suitable for real-time streaming data transformation to a Bronze table.
Option D: It employs spark.readStream.load() to ingest raw data as a stream and then writes it out with .writeStream, which is a typical pattern for streaming data into a Bronze table where raw data is captured in real-time and minimal transformation is applied. This approach aligns with the concept of a Bronze table in a modern data architecture, where raw data is ingested continuously and stored in a more accessible format.
Reference:
Databricks documentation on Structured Streaming: Structured Streaming in Databricks

NEW QUESTION # 73
A data engineer is working with two tables. Each of these tables is displayed below in its entirety.

The data engineer runs the following query to join these tables together:

Which of the following will be returned by the above query?

A. Option E
B. Option B
C. Option C
D. Option A
E. Option D

Answer: C

NEW QUESTION # 74
Which of the following Git operations must be performed outside of Databricks Repos?

A. Merge
B. Clone
C. Pull
D. Push
E. Commit

Answer: A

Explanation:
Explanation
For following tasks, work in your Git provider:
Create a pull request.
Resolve merge conflicts.
Merge or delete branches.
Rebase a branch.
https://docs.databricks.com/repos/index.html

NEW QUESTION # 75
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
UNION 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
INTERSECT SELECT * from april_transactions;

Answer: C

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 # 76
......

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