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

1. A company needs to partition the Amazon S3 storage that the company uses for a data lake. The partitioning will use a path of the S3 object keys in the following format: s3://bucket/prefix/year=2023/month=01/day=01.
A data engineer must ensure that the AWS Glue Data Catalog synchronizes with the S3 storage when the company adds new partitions to the bucket.
Which solution will meet these requirements with the LEAST latency?

A) Schedule an AWS Glue crawler to run every morning.
B) Use code that writes data to Amazon S3 to invoke the Boto3 AWS Glue create partition API call.
C) Manually run the AWS Glue CreatePartition API twice each day.
D) Run the MSCK REPAIR TABLE command from the AWS Glue console.

2. A company stores data in a data lake that is in Amazon S3. Some data that the company stores in the data lake contains personally identifiable information (PII). Multiple user groups need to access the raw data. The company must ensure that user groups can access only the PII that they require.
Which solution will meet these requirements with the LEAST effort?

A) Build a custom query builder UI that will run Athena queries in the background to access the data.
Create user groups in Amazon Cognito. Assign access levels to the user groups based on the PII access requirements of the users.
B) Use Amazon Athena to query the data. Set up AWS Lake Formation and create data filters to establish levels of access for the company's IAM roles. Assign each user to the IAM role that matches the user's PII access requirements.
C) Create IAM roles that have different levels of granular access. Assign the IAM roles to IAM user groups. Use an identity-based policy to assign access levels to user groups at the column level.
D) Use Amazon QuickSight to access the data. Use column-level security features in QuickSight to limit the PII that users can retrieve from Amazon S3 by using Amazon Athena. Define QuickSight access levels based on the PII access requirements of the users.

3. A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations.
Which combination of AWS services will implement a data mesh? (Choose two.)

A) Use AWS Lake Formation for centralized data governance and access control.
B) Use Amazon Aurora for data storage. Use an Amazon Redshift provisioned cluster for data analysis.
C) Use AWS Glue DataBrewfor centralized data governance and access control.
D) Use Amazon RDS for data storage. Use Amazon EMR for data analysis.
E) Use Amazon S3 for data storage. Use Amazon Athena for data analysis.

4. A company uses Amazon S3 to store semi-structured data in a transactional data lake. Some of the data files are small, but other data files are tens of terabytes.
A data engineer must perform a change data capture (CDC) operation to identify changed data from the data source. The data source sends a full snapshot as a JSON file every day and ingests the changed data into the data lake.
Which solution will capture the changed data MOST cost-effectively?

A) Ingest the data into Amazon RDS for MySQL. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.
B) Use an open source data lake format to merge the data source with the S3 data lake to insert the new data and update the existing data.
C) Create an AWS Lambda function to identify the changes between the previous data and the current data.
Configure the Lambda function to ingest the changes into the data lake.
D) Ingest the data into an Amazon Aurora MySQL DB instance that runs Aurora Serverless. Use AWS Database Migration Service (AWS DMS) to write the changed data to the data lake.

5. A company uses an Amazon Redshift provisioned cluster as its database. The Redshift cluster has five reserved ra3.4xlarge nodes and uses key distribution.
A data engineer notices that one of the nodes frequently has a CPU load over 90%. SQL Queries that run on the node are queued. The other four nodes usually have a CPU load under 15% during daily operations.
The data engineer wants to maintain the current number of compute nodes. The data engineer also wants to balance the load more evenly across all five compute nodes.
Which solution will meet these requirements?

A) Upgrade the reserved node from ra3.4xlarqe to ra3.16xlarqe.
B) Change the distribution key to the table column that has the largest dimension.
C) Change the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
D) Change the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.

問題與答案：

問題 #1 答案： B

問題 #2 答案： B

問題 #3 答案： A,E

問題 #4 答案： B

問題 #5 答案： B