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| Section | Objectives |
|---|---|
| Topic 1: Data Processing and Transformations | - Delta Lake fundamentals (tables, transactions, optimization) - User-defined functions (UDFs) - Apache Spark SQL operations (joins, aggregations, filtering) - PySpark DataFrame transformations |
| Topic 2: Data Ingestion and ELT Development | - Handling structured and semi-structured data - ETL patterns and transformations - Data ingestion using Spark SQL and PySpark |
| Topic 3: Databricks Lakehouse Platform Fundamentals | - Workspace, architecture, and core platform concepts - Clusters, notebooks, and basic Databricks environment usage |
| Topic 4: Productionizing Data Pipelines | - Pipeline deployment and operationalization - Scheduling and monitoring jobs - Databricks Workflows / Jobs orchestration |
| Topic 5: Data Governance and Quality | - Data access control and governance - Data quality concepts and management - Unity Catalog basics |
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NEW QUESTION # 131
A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when it is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?
Answer: A
Explanation:
The Auto Stop feature allows the SQL endpoint to automatically stop after a specified period of inactivity.
This can help reduce the cost and resource consumption of the SQL endpoint, as it will only run when it is needed to refresh the dashboard or execute queries. The data engineer can configure the Auto Stop setting for the SQL endpoint from the SQL Endpoints UI, by selecting the desired idle time from the Auto Stop dropdown menu. The default idle time is 120 minutes, but it can be set to as low as 15 minutes or as high as
240 minutes. Alternatively, the data engineer can also use the SQL Endpoints REST API to set the Auto Stop setting programmatically. References: SQL Endpoints UI, SQL Endpoints REST API, Refreshing SQL Dashboard
NEW QUESTION # 132
Which of the following must be specified when creating a new Delta Live Tables pipeline?
Answer: B
NEW QUESTION # 133
A departing platform owner currently holds ownership of multiple catalogs and controls storage credentials and external locations. A data engineer has been asked to ensure continuity: transfer catalog ownership to the platform team group, delegate ongoing privilege management, and retain the ability to receive and share data via Delta Sharing.
Which role must be in place to perform these actions across the metastore?
Answer: A
Explanation:
Metastore Admins have the highest administrative privileges within a Unity Catalog metastore. They can transfer ownership of any Unity Catalog object, including catalogs, schemas, tables, storage credentials, and external locations. Metastore Admins are also required to manage Delta Sharing configurations such as creating or transferring shares and recipients.
Account Admins, by contrast, only create metastores and cannot change ownership or manage Delta Sharing objects. Workspace Admins have privileges limited to workspace-level management, not cross-metastore access.
Reference Source: Databricks Unity Catalog Administration Guide - "Metastore admin privileges and ownership transfer."
NEW QUESTION # 134
Differentiate between all-purpose clusters and jobs clusters.
A data engineering team has created a python notebook to load data from cloud storage, this job has been tested and now needs to be scheduled in production.
Which would be the best cluster to be used in this case?
Answer: A
NEW QUESTION # 135
Which of the following is stored in the Databricks customer's cloud account?
Answer: C
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.
Databricks Architecture
Databricks Data Sources
Databricks Repos
[Databricks Notebooks]
[Databricks Data Engineer Professional Exam Guide]
NEW QUESTION # 136
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