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最新的 AWS Certified Data Engineer Data-Engineer-Associate 免費考試真題:

1. A company is migrating its database servers from Amazon EC2 instances that run Microsoft SQL Server to Amazon RDS for Microsoft SQL Server DB instances. The company's analytics team must export large data elements every day until the migration is complete. The data elements are the result of SQL joins across multiple tables. The data must be in Apache Parquet format. The analytics team must store the data in Amazon S3.
Which solution will meet these requirements in the MOST operationally efficient way?

A) Use a SQL query to create a view in the EC2 instance-based SQL Server databases that contains the required data elements. Create and run an AWS Glue crawler to read the view. Create an AWS Glue job that retrieves the data and transfers the data in Parquet format to an S3 bucket. Schedule the AWS Glue job to run every day.
B) Schedule SQL Server Agent to run a daily SQL query that selects the desired data elements from the EC2 instance-based SQL Server databases. Configure the query to direct the output .csv objects to an S3 bucket. Create an S3 event that invokes an AWS Lambda function to transform the output format from .csv to Parquet.
C) Create a view in the EC2 instance-based SQL Server databases that contains the required data elements.
Create an AWS Glue job that selects the data directly from the view and transfers the data in Parquet format to an S3 bucket. Schedule the AWS Glue job to run every day.
D) Create an AWS Lambda function that queries the EC2 instance-based databases by using Java Database Connectivity (JDBC). Configure the Lambda function to retrieve the required data, transform the data into Parquet format, and transfer the data into an S3 bucket. Use Amazon EventBridge to schedule the Lambda function to run every day.

2. A company uses Amazon Redshift for its data warehouse. The company must automate refresh schedules for Amazon Redshift materialized views.
Which solution will meet this requirement with the LEAST effort?

A) Use an AWS Glue workflow to refresh the materialized views.
B) Use the query editor v2 in Amazon Redshift to refresh the materialized views.
C) Use an AWS Lambda user-defined function (UDF) within Amazon Redshift to refresh the materialized views.
D) Use Apache Airflow to refresh the materialized views.

3. A company has an Amazon Redshift data warehouse that users access by using a variety of IAM roles. More than 100 users access the data warehouse every day.
The company wants to control user access to the objects based on each user's job role, permissions, and how sensitive the data is.
Which solution will meet these requirements?

A) Use dynamic data masking policies in Amazon Redshift.
B) Use the row-level security (RLS) feature of Amazon Redshift.
C) Use the column-level security (CLS) feature of Amazon Redshift.
D) Use the role-based access control (RBAC) feature of Amazon Redshift.

4. A company wants to migrate an application and an on-premises Apache Kafka server to AWS. The application processes incremental updates that an on-premises Oracle database sends to the Kafka server. The company wants to use the replatform migration strategy instead of the refactor strategy.
Which solution will meet these requirements with the LEAST management overhead?

A) Amazon Data Firehose
B) Amazon Managed Streaming for Apache Kafka (Amazon MSK) Serverless
C) Amazon Managed Streaming for Apache Kafka (Amazon MSK) provisioned cluster
D) Amazon Kinesis Data Streams

5. A company's data engineer needs to optimize the performance of table SQL queries. The company stores data in an Amazon Redshift cluster. The data engineer cannot increase the size of the cluster because of budget constraints.
The company stores the data in multiple tables and loads the data by using the EVEN distribution style. Some tables are hundreds of gigabytes in size. Other tables are less than 10 MB in size.
Which solution will meet these requirements?

A) Use the ALL distribution style for large tables. Specify primary and foreign keys for all tables.
B) Use the ALL distribution style for rarely updated small tables. Specify primary and foreign keys for all tables.
C) Specify a combination of distribution, sort, and partition keys for all tables.
D) Keep using the EVEN distribution style for all tables. Specify primary and foreign keys for all tables.

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