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最新的 AWS Certified Data Engineer Data-Engineer-Associate 免費考試真題 (Q14-Q19):

問題 #14
A company has used an Amazon Redshift table that is named Orders for 6 months. The company performs weekly updates and deletes on the table. The table has an interleaved sort key on a column that contains AWS Regions.
The company wants to reclaim disk space so that the company will not run out of storage space. The company also wants to analyze the sort key column.
Which Amazon Redshift command will meet these requirements?

A. VACUUM FULL Orders
B. VACUUM DELETE ONLY Orders
C. VACUUM REINDEX Orders
D. VACUUM SORT ONLY Orders

答案：C

解題說明：
Amazon Redshift is a fully managed, petabyte-scale data warehouse service that enables fast and cost-effective analysis of large volumes of data. Amazon Redshift uses columnar storage, compression, and zone maps to optimize the storage and performance of data. However, over time, as data is inserted, updated, or deleted, the physical storage of data can become fragmented, resulting in wasted disk space and degraded query performance. To address this issue, Amazon Redshift provides the VACUUM command, which reclaims disk space and resorts rows in either a specified table or all tables in the current schema1.
The VACUUM command has four options: FULL, DELETE ONLY, SORT ONLY, and REINDEX. The option that best meets the requirements of the question is VACUUM REINDEX, which re-sorts the rows in a table that has an interleaved sort key and rewrites the table to a new location on disk. An interleaved sort key is a type of sort key that gives equal weight to each column in the sort key, and stores the rows in a way that optimizes the performance of queries that filter by multiple columns in the sort key. However, as data is added or changed, the interleaved sort order can become skewed, resulting in suboptimal query performance. The VACUUM REINDEX option restores the optimal interleaved sort order and reclaims disk space by removing deleted rows. This option also analyzes the sort key column and updates the table statistics, which are used by the query optimizer to generate the most efficient query execution plan23.
The other options are not optimal for the following reasons:
A . VACUUM FULL Orders. This option reclaims disk space by removing deleted rows and resorts the entire table. However, this option is not suitable for tables that have an interleaved sort key, as it does not restore the optimal interleaved sort order. Moreover, this option is the most resource-intensive and time-consuming, as it rewrites the entire table to a new location on disk.
B . VACUUM DELETE ONLY Orders. This option reclaims disk space by removing deleted rows, but does not resort the table. This option is not suitable for tables that have any sort key, as it does not improve the query performance by restoring the sort order. Moreover, this option does not analyze the sort key column and update the table statistics.
D . VACUUM SORT ONLY Orders. This option resorts the entire table, but does not reclaim disk space by removing deleted rows. This option is not suitable for tables that have an interleaved sort key, as it does not restore the optimal interleaved sort order. Moreover, this option does not analyze the sort key column and update the table statistics.
Reference:
1: Amazon Redshift VACUUM
2: Amazon Redshift Interleaved Sorting
3: Amazon Redshift ANALYZE

問題 #15
A company runs multiple applications on AWS. The company configured each application to output logs. The company wants to query and visualize the application logs in near real time.
Which solution will meet these requirements?

A. Update the application code to send the log data to Amazon QuickSight by using Super-fast, Parallel, In- memory Calculation Engine (SPICE). Create the required analyses and dashboards in QuickSight.
B. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Use CloudWatch log anomaly detection to query and visualize the log data.
C. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an Amazon S3 bucket. Create an AWS Lambda function that runs on a schedule to export the required log groups to the S3 bucket. Use Amazon Athena to query the log data in the S3 bucket.
D. Create an Amazon OpenSearch Service domain. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an OpenSearch Service subscription filter for each log group to stream the data to OpenSearch. Create the required queries and dashboards in OpenSearch Service to analyze and visualize the data.

答案：D

解題說明：
The optimal solution for near-real-time querying and visualization of logs is to integrateAmazon CloudWatch LogswithAmazon OpenSearch Serviceusingsubscription filters, which stream the logs directly into OpenSearch for querying and dashboarding:
"Use OpenSearch Service with CloudWatch Logs and create a subscription filter to stream log data in near real time into OpenSearch. Then use OpenSearch dashboards for visualization."
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf This approach offers low latency and avoids batch exports, unlike the scheduled Athena + S3 pattern.

問題 #16
A company is developing an application that runs on Amazon EC2 instances. Currently, the data that the application generates is temporary. However, the company needs to persist the data, even if the EC2 instances are terminated.
A data engineer must launch new EC2 instances from an Amazon Machine Image (AMI) and configure the instances to preserve the data.
Which solution will meet this requirement?

A. Launch new EC2 instances by using an AMI that is backed by a root Amazon Elastic Block Store (Amazon EBS) volume that contains the application data. Apply the default settings to the EC2 instances.
B. Launch new EC2 instances by using an AMI that is backed by an Amazon Elastic Block Store (Amazon EBS) volume. Attach an additional EC2 instance store volume to contain the application data. Apply the default settings to the EC2 instances.
C. Launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume. Attach an Amazon Elastic Block Store (Amazon EBS) volume to contain the application data. Apply the default settings to the EC2 instances.
D. Launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data. Apply the default settings to the EC2 instances.

答案：C

解題說明：
Amazon EC2 instances can use two types of storage volumes: instance store volumes and Amazon EBS volumes. Instance store volumes are ephemeral, meaning they are only attached to the instance for the duration of its life cycle. If the instance is stopped, terminated, or fails, the data on the instance store volume is lost. Amazon EBS volumes are persistent, meaning they can be detached from the instance and attached to another instance, and the data on the volume is preserved. To meet the requirement of persisting the data even if the EC2 instances are terminated, the data engineer must use Amazon EBS volumes to store the application data. The solution is to launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume, which is the default option for most AMIs. Then, the data engineer must attach an Amazon EBS volume to each instance and configure the application to write the data to the EBS volume. This way, the data will be saved on the EBS volume and can be accessed by another instance if needed. The data engineer can apply the default settings to the EC2 instances, as there is no need to modify the instance type, security group, or IAM role for this solution. The other options are either not feasible or not optimal. Launching new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data (option A) or by using an AMI that is backed by a root Amazon EBS volume that contains the application data (option B) would not work, as the data on the AMI would be outdated and overwritten by the new instances. Attaching an additional EC2 instance store volume to contain the application data (option D) would not work, as the data on the instance store volume would be lost if the instance is terminated. References:
* Amazon EC2 Instance Store
* Amazon EBS Volumes
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 2: Data Store Management, Section 2.1: Amazon EC2

問題 #17
A company is using an AWS Transfer Family server to migrate data from an on-premises environment to AWS. Company policy mandates the use of TLS 1.2 or above to encrypt the data in transit.
Which solution will meet these requirements?

A. Generate new SSH keys for the Transfer Family server. Make the old keys and the new keys available for use.
B. Update the security group rules for the on-premises network to allow only connections that use TLS 1.2 or above.
C. Install an SSL certificate on the Transfer Family server to encrypt data transfers by using TLS 1.2.
D. Update the security policy of the Transfer Family server to specify a minimum protocol version of TLS
1.2.

答案：D

解題說明：
The AWS Transfer Family server's security policy can be updated to enforce TLS 1.2 or higher, ensuring compliance with company policy for encrypted data transfers.
* AWS Transfer Family Security Policy:
* AWS Transfer Family supports setting a minimum TLS version through its security policy configuration. This ensures that only connections using TLS 1.2 or above are allowed.

問題 #18
A company maintains an Amazon Redshift provisioned cluster that the company uses for extract, transform, and load (ETL) operations to support critical analysis tasks. A sales team within the company maintains a Redshift cluster that the sales team uses for business intelligence (BI) tasks.
The sales team recently requested access to the data that is in the ETL Redshift cluster so the team can perform weekly summary analysis tasks. The sales team needs to join data from the ETL cluster with data that is in the sales team's BI cluster.
The company needs a solution that will share the ETL cluster data with the sales team without interrupting the critical analysis tasks. The solution must minimize usage of the computing resources of the ETL cluster.
Which solution will meet these requirements?

A. Create materialized views based on the sales team's requirements. Grant the sales team direct access to the ETL cluster.
B. Set up the sales team Bl cluster as a consumer of the ETL cluster by using Redshift data sharing.
C. Create database views based on the sales team's requirements. Grant the sales team direct access to the ETL cluster.
D. Unload a copy of the data from the ETL cluster to an Amazon S3 bucket every week. Create an Amazon Redshift Spectrum table based on the content of the ETL cluster.

答案：B

解題說明：
Redshift data sharing is a feature that enables you to share live data across different Redshift clusters without the need to copy or move data. Data sharing provides secure and governed access to data, while preserving the performance and concurrency benefits of Redshift. By setting up the sales team BI cluster as a consumer of the ETL cluster, the company can share the ETL cluster data with the sales team without interrupting the critical analysis tasks. The solution also minimizes the usage of the computing resources of the ETL cluster, as the data sharing does not consume any storage space or compute resources from the producer cluster. The other options are either not feasible or not efficient. Creating materialized views or database views would require the sales team to have direct access to the ETL cluster, which could interfere with the critical analysis tasks. Unloading a copy of the data from the ETL cluster to an Amazon S3 bucket every week would introduce additional latency and cost, as well as create data inconsistency issues. References:
* Sharing data across Amazon Redshift clusters
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 2: Data Store Management, Section 2.2: Amazon Redshift

問題 #19
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