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Databricks Certified Data Engineer Associate Exam covers a wide range of topics, including data ingestion, data transformation, data storage, data processing, and data analysis. It is designed to test the candidate's ability to work with a variety of data sources and formats, including structured, semi-structured, and unstructured data. It also tests the candidate's knowledge of data engineering best practices, such as data quality, data governance, and data security.

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q42-Q47):

NEW QUESTION # 42
A Python file is ready to go into production and the client wants to use the cheapest but most efficient type of cluster possible. The workload is quite small, only processing 10GBs of data with only simple joins and no complex aggregations or wide transformations. Which cluster meets the requirement?

Answer: C

Explanation:
A job cluster with spot instances enabled is the cheapest and efficient option for small, production workloads. Spot instances reduce costs, and a job cluster ensures the cluster only runs during the workload execution.


NEW QUESTION # 43
A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.
Which of the following relational objects should the data engineer create?

Answer: A

Explanation:
Explanation
Temp view : session based Create temp view view_name as query All these are termed as session ended:
Opening a new notebook Detaching and reattaching a cluster Installing a python package Restarting a cluster


NEW QUESTION # 44
Which of the following is hosted completely in the control plane of the classic Databricks architecture?

Answer: D

Explanation:
Explanation
In the classic Databricks architecture, the control plane includes components like the Databricks web application, the Databricks REST API, and the Databricks Workspace. These components are responsible for managing and controlling the Databricks environment, including cluster provisioning, notebook management, access control, and job scheduling. The other options, such as worker nodes, JDBC data sources, Databricks Filesystem (DBFS), and driver nodes, are typically part of the data plane or the execution environment, which is separate from the control plane. Worker nodes are responsible for executing tasks and computations, JDBC data sources are used to connect to external databases, DBFS is a distributed file system for data storage, and driver nodes are responsible for coordinating the execution of Spark jobs.


NEW QUESTION # 45
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

Answer: D


NEW QUESTION # 46
A data engineer needs to migrate the Unity Catalog external Delta table catalog.schema.sales while meeting the following requirements:
Databricks must manage file cleanup after the table is dropped.
The migration must minimize downtime while retaining the same table name, permissions, and history.
Access must be enforced through the registered Unity Catalog table name.
Which action should the engineer take?

Answer: D


NEW QUESTION # 47
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