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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Productionizing Data Pipelines | 18% | - Deployment and CI/CD
|
| Topic 2: Data Governance & Quality | 11% | - Unity Catalog implementation
|
| Topic 3: Databricks Intelligence Platform | 10% | - Platform architecture and core concepts
|
| Topic 4: Data Processing & Transformations | 31% | - Query optimization and performance
|
| Topic 5: Development and Ingestion | 30% | - Data ingestion patterns and methods
|
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NEW QUESTION # 30
Which of the following describes a benefit of creating an external table from Parquet rather than CSV when using a CREATE TABLE AS SELECT statement?
Answer: A
Explanation:
Option C is the correct answer because Parquet files have a well-defined schema that is embedded within the data itself. This means that the data types and column names of the Parquet files are automatically detected and preserved when creating an external table from them. This also enables the use of SQL and other structured query languages to access and analyze the data. CSV files, on the other hand, do not have a schema embedded in them, and require specifying the schema explicitly or inferring it from the data when creating an external table from them. This can lead to errors or inconsistencies in the data types and column names, and also increase the processing time and complexity.
CREATE TABLE AS SELECT, Parquet Files, CSV Files, Parquet vs. CSV
NEW QUESTION # 31
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: C
Explanation:
A temporary view is a relational object that is defined in the metastore and points to an existing DataFrame. It does not copy or store any physical data, but only saves the query that defines the view. The lifetime of a temporary view is tied to the SparkSession that was used to create it, so it does not persist across different sessions or applications. A temporary view is useful for accessing the same data multiple times within the same notebook or session, without incurring additional storage costs. The other options are either materialized (A, E), persistent (B, C), or not relational objects ©. References: Databricks Documentation - Temporary View, Databricks Community - How do temp views actually work?, Databricks Community - What's the difference between a Global view and a Temp view?, Big Data Programmers - Temporary View in Databricks.
NEW QUESTION # 32
A company uses Delta Sharing to collaborate with partners across different cloud providers and geographic regions. What will result in additional costs due to cross-region or egress fees?
Answer: C
Explanation:
Databricks documents that Delta Sharing does not require data replication, but cloud providers can still charge data egress fees when data is shared across clouds or across geographic regions. Databricks specifically states that sharing within the same region incurs no egress cost, while cross-cloud or cross-region transfers can create additional charges from the underlying cloud provider. That means option A is correct. Options B and C describe same-cloud or same-region use cases that do not trigger the cross-region/cross-cloud egress pattern Databricks calls out. Option D is unrelated to the main documented billing driver for Delta Sharing costs. The important principle is that Delta Sharing itself is designed to avoid replication overhead, but the physical movement of data between cloud boundaries or regions can still result in vendor networking charges. Therefore, when sharing data with external partners in other regions or clouds, engineers should plan for possible egress costs and monitor them accordingly.
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NEW QUESTION # 33
Which of the following queries is performing a streaming hop from raw data to a Bronze table?
Answer: B
NEW QUESTION # 34
A data engineer needs to use a Delta table as part of a data pipeline, but they do not know if they have the appropriate permissions.
In which of the following locations can the data engineer review their permissions on the table?
Answer: D
Explanation:
Data Explorer is a graphical interface that allows you to browse, create, and manage data objects such as databases, tables, and views in your workspace. You can also review and modify the permissions on these data objects using Data Explorer. To access Data Explorer, you can click on the Data icon in the sidebar, or use the
%sql magic command in a notebook. You can then select a database and a table, and click on the Permissions tab to view and edit the access control lists (ACLs) for the table. You can also use SQL commands such as SHOW GRANT and GRANT to query and modify the permissions on a Delta table. References:
* Data Explorer
* Access control for Delta tables
* SHOW GRANT
* [GRANT]
NEW QUESTION # 35
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