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| Section | Objectives |
|---|---|
| Databricks Lakehouse Platform Fundamentals | - Clusters, notebooks, and basic Databricks environment usage - Workspace, architecture, and core platform concepts |
| Data Governance and Quality | - Data quality concepts and management - Data access control and governance - Unity Catalog basics |
| Productionizing Data Pipelines | - Databricks Workflows / Jobs orchestration - Scheduling and monitoring jobs - Pipeline deployment and operationalization |
| Data Processing and Transformations | - User-defined functions (UDFs) - Apache Spark SQL operations (joins, aggregations, filtering) - Delta Lake fundamentals (tables, transactions, optimization) - PySpark DataFrame transformations |
| Data Ingestion and ELT Development | - Handling structured and semi-structured data - Data ingestion using Spark SQL and PySpark - ETL patterns and transformations |
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NEW QUESTION # 240
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?
Answer: B
NEW QUESTION # 241
A data engineer is reviewing the documentation on audit logs in Databricks for compliance purposes and needs to understand the format in which audit logs output events.
How are events formatted in Databricks audit logs?
Answer: A
NEW QUESTION # 242
Which of the following queries is performing a streaming hop from raw data to a Bronze table?
Answer: E
NEW QUESTION # 243
A data engineer has a Python variable table_name that they would like to use in a SQL query. They want to construct a Python code block that will run the query using table_name.
They have the following incomplete code block:
____(f"SELECT customer_id, spend FROM {table_name}")
Which of the following can be used to fill in the blank to successfully complete the task?
Answer: C
Explanation:
The spark.sql method can be used to execute SQL queries programmatically and return the result as a DataFrame. The spark.sql method accepts a string argument that contains a valid SQL statement. The data engineer can use a formatted string literal (f-string) to insert the Python variable table_name into the SQL query. The other methods are either invalid or not suitable for running SQL queries. Reference: Running SQL Queries Programmatically, Formatted string literals, spark.sql
NEW QUESTION # 244
Which of the following is stored in the Databricks customer's cloud account?
Answer: E
Explanation:
The only option that is stored in the Databricks customer's cloud account is data. Data is stored in the customer's cloud storage service, such as AWS S3 or Azure Data Lake Storage. The customer has full control and ownership of their data and can access it directly from their cloud account.
Option A is not correct, as the Databricks web application is hosted and managed by Databricks on their own cloud infrastructure. The customer does not need to install or maintain the web application, but only needs to access it through a web browser.
Option B is not correct, as the cluster management metadata is stored and managed by Databricks on their own cloud infrastructure. The cluster management metadata includes information such as cluster configuration, status, logs, and metrics. The customer can view and manage their clusters through the Databricks web application, but does not have direct access to the cluster management metadata.
Option C is not correct, as the repos are stored and managed by Databricks on their own cloud infrastructure. Repos are version-controlled repositories that store code and data files for Databricks projects. The customer can create and manage their repos through the Databricks web application, but does not have direct access to the repos.
Option E is not correct, as the notebooks are stored and managed by Databricks on their own cloud infrastructure. Notebooks are interactive documents that contain code, text, and visualizations for Databricks workflows. The customer can create and manage their notebooks through the Databricks web application, but does not have direct access to the notebooks.
Reference:
Databricks Architecture
Databricks Data Sources
Databricks Repos
[Databricks Notebooks]
[Databricks Data Engineer Professional Exam Guide]
NEW QUESTION # 245
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