Databricks-Certified-Data-Engineer-Associate試験解説問題 & Databricks-Certified-Data-Engineer-Associate合格体験談

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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:

Section	Objectives
Databricks Lakehouse Platform Fundamentals	- Workspace, architecture, and core platform concepts - Clusters, notebooks, and basic Databricks environment usage
Data Governance and Quality	- Unity Catalog basics - Data quality concepts and management - Data access control and governance
Data Processing and Transformations	- User-defined functions (UDFs) - Delta Lake fundamentals (tables, transactions, optimization) - PySpark DataFrame transformations - Apache Spark SQL operations (joins, aggregations, filtering)
Productionizing Data Pipelines	- Databricks Workflows / Jobs orchestration - Pipeline deployment and operationalization - Scheduling and monitoring jobs
Data Ingestion and ELT Development	- ETL patterns and transformations - Data ingestion using Spark SQL and PySpark - Handling structured and semi-structured data

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Databricks Certified Data Engineer Associate Exam 認定 Databricks-Certified-Data-Engineer-Associate 試験問題 (Q109-Q114):

質問 # 109
Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?

正解：E

質問 # 110
A data engineer needs to create a table in Databricks using data from a CSV file at location /path/to/csv.
They run the following command:

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

A. FROM "path/to/csv"
B. None of these lines of code are needed to successfully complete the task
C. USING DELTA
D. FROM CSV
E. USING CSV

正解：E

質問 # 111
Which compute option should be chosen in a scenario where small-scale ad-hoc Python scripts need to be run at high frequency and should wind down quickly after these queries have finished running?

A. All-purpose Cluster
B. SQL Warehouse
C. Serverless Compute
D. Job Cluster

正解：C

解説：
Serverless Compute is ideal for small-scale, frequent, ad-hoc Python scripts because it provisions automatically, scales quickly, and terminates when queries finish, minimizing operational overhead and costs.

質問 # 112
A data engineer at a company that uses Databricks with Unity Catalog needs to share a collection of tables with an external partner who also uses a Databricks workspace enabled for Unity Catalog. The data engineer decides to use Delta Sharing to accomplish this.
What is the first piece of information the data engineer should request from the external partner to set up Delta Sharing?

A. The name of their Databricks cluster
B. Their Databricks account password
C. The IP address of their Databricks workspace
D. The sharing identifier of their Unity Catalog metastore

正解：D

質問 # 113
An organization plans to share a large dataset stored in a Databricks workspace on AWS with a partner organization whose Databricks workspace is hosted on Azure. The data engineer wants to minimize data transfer costs while ensuring secure and efficient data sharing.
Which strategy will reduce data egress costs associated with cross-cloud data sharing?

A. Migrating the dataset to Cloudflare R2 object storage before sharing
B. Configure VPN connection between AWS and Azure for faster data sharing
C. Using Delta Sharing without any additional configurations
D. Sharing data via pre-signed URLs without monitoring egress costs

正解：C

質問 # 114
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