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The GAQM Databricks-Certified-Data-Engineer-Associate certification is an essential credential for individuals and organizations working with big data using Databricks. It validates the candidate's skills and knowledge of data engineering concepts and their ability to design and implement data pipelines using Databricks. Databricks Certified Data Engineer Associate Exam certification is globally recognized and highly respected in the industry, making it a valuable asset for anyone looking to advance their career in the field of data engineering.
The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is a challenging and highly respected certification for data professionals. It is designed to test individuals' knowledge and skills in data engineering, with a focus on the Databricks platform. Individuals who pass the exam will have a valuable certification that can help them advance their careers and increase their earning potential.
The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) certification exam is a highly esteemed certification for data professionals. Databricks-Certified-Data-Engineer-Associate exam measures an individual's competence in designing, building, and maintaining data pipelines using Databricks. Databricks Certified Data Engineer Associate Exam certification covers a wide range of topics, including data engineering fundamentals, Databricks architecture, data modeling, and data processing.
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Databricks Certified Data Engineer Associate Exam Sample Questions (Q33-Q38):
NEW QUESTION # 33
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 did not have a location
- B. The table was managed
- C. The table's data was smaller than 10 GB
- D. The table's data was larger than 10 GB
- E. The table was external
Answer: E
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 # 34
Which of the following is hosted completely in the control plane of the classic Databricks architecture?
- A. Driver node
- B. Databricks Filesystem
- C. JDBC data source
- D. Databricks web application
- E. Worker node
Answer: D
Explanation:
1: The Databricks web application is the user interface that allows you to create and manage workspaces, clusters, notebooks, jobs, and other resources. It is hosted completely in the control plane of the classic Databricks architecture, which includes the backend services that Databricks manages in your Databricks account. The other options are part of the compute plane, which is where your data is processed by compute resources such as clusters. The compute plane is in your own cloud account and network. Reference: Databricks architecture overview, Security and Trust Center
NEW QUESTION # 35
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?
- A. Workspace administrator
- B. Databricks account representative
- C. Original data engineer
- D. This transfer is not possible
- E. New lead data engineer
Answer: A
Explanation:
The workspace administrator is the only individual who can transfer ownership of the Delta tables in Data Explorer, assuming the original data engineer no longer has access. The workspace administrator has the highest level of permissions in the workspace and can manage all resources, users, and groups. The other options are either not possible or not sufficient to perform the ownership transfer. The Databricks account representative is not involved in the workspace management. The transfer is possible and not dependent on the original data engineer. The new lead data engineer may not have the necessary permissions to access or modify the Delta tables, unless granted by the workspace administrator or the original data engineer before leaving. Reference: Workspace access control, Manage Unity Catalog object ownership.
NEW QUESTION # 36
A data engineer only wants to execute the final block of a Python program if the Python variable day_of_week is equal to 1 and the Python variable review_period is True.
Which of the following control flow statements should the data engineer use to begin this conditionally executed code block?
- A. if day_of_week = 1 and review_period = "True":
- B. if day_of_week = 1 & review_period: = "True":
- C. if day_of_week == 1 and review_period:
- D. if day_of_week == 1 and review_period == "True":
- E. if day_of_week = 1 and review_period:
Answer: C
Explanation:
Explanation
This statement will check if the variable day_of_week is equal to 1 and if the variable review_period evaluates to a truthy value. The use of the double equal sign (==) in the comparison of day_of_week is important, as a single equal sign (=) would be used to assign a value to the variable instead of checking its value. The use of a single ampersand (&) instead of the keyword and is not valid syntax in Python. The use of quotes around True in options B and C will result in a string comparison, which will not evaluate to True even if the value of review_period is True.
NEW QUESTION # 37
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?
- A. The OPTIMIZE command was nun on the table
- B. The TIME TRAVEL command was run on the table
- C. The HISTORY command was run on the table
- D. The DELETE HISTORY command was run on the table
- E. The VACUUM command was run on the table
Answer: E
Explanation:
The VACUUM command is used to remove files that are no longer referenced by a Delta table and are older than the retention threshold1. The default retention period is 7 days2, but it can be changed by setting the delta.logRetentionDuration and delta.deletedFileRetentionDuration configurations3. If the VACUUM command was run on the table with a retention period shorter than 3 days, then the data files that were needed to restore the table to a 3-day-old version would have been deleted. The other commands do not delete data files from the table. The TIME TRAVEL command is used to query a historical version of the table4. The DELETE HISTORY command is not a valid command in Delta Lake. The OPTIMIZE command is used to improve the performance of the table by compacting small files into larger ones5. The HISTORY command is used to retrieve information about the operations performed on the table. References: 1: VACUUM | Databricks on AWS 2: Work with Delta Lake table history | Databricks on AWS 3: [Delta Lake configuration | Databricks on AWS] 4: Work with Delta Lake table history - Azure Databricks 5: [OPTIMIZE | Databricks on AWS] : [HISTORY | Databricks on AWS]
NEW QUESTION # 38
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