DEA-C01 practice questions 41–50

1. Question 41 · 313 in bank

   A data engineer is using an AWS Glue crawler to catalog data that is in an Amazon S3 bucket. The S3 bucket contains both .csv and json files. The data engineer configured the crawler to exclude the .json files from the catalog. When the data engineer runs queries in Amazon Athena, the queries also process the excluded .json files. The data engineer wants to resolve this issue. The data engineer needs a solution that will not affect access requirements for the .csv files in the source S3 bucket. Which solution will meet this requirement with the SHORTEST query times?

   • AAdjust the AWS Glue crawler settings to ensure that the AWS Glue crawler also excludes .json files.
   • BUse the Athena console to ensure the Athena queries also exclude the .json files.
   • CRelocate the .json files to a different path within the S3 bucket.
   • DUse S3 bucket policies to block access to the .json files.

   Show answer

   Answer: C

   Explanation

   Athena does not recognize exclude patterns that you specify an AWS Glue crawler. For example, if you have an Amazon S3 bucket that contains both .csv and .json files and you exclude the .json files from the crawler, Athena queries both groups of files. To avoid this, place the files that you want to exclude in a different location. https://docs.aws.amazon.com/athena/latest/ug/troubleshooting-athena.html

   Source: Adapted from community discussion — teo2157

   References

   • AWS documentation

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2. Question 42 · 313 in bank

   A data engineer set up an AWS Lambda function to read an object that is stored in an Amazon S3 bucket. The object is encrypted by an AWS KMS key. The data engineer configured the Lambda function’s execution role to access the S3 bucket. However, the Lambda function encountered an error and failed to retrieve the content of the object. What is the likely cause of the error?

   • AThe data engineer misconfigured the permissions of the S3 bucket. The Lambda function could not access the object.
   • BThe Lambda function is using an outdated SDK version, which caused the read failure.
   • CThe S3 bucket is located in a different AWS Region than the Region where the data engineer works. Latency issues caused the Lambda function to encounter an error.
   • DThe Lambda function’s execution role does not have the necessary permissions to access the KMS key that can decrypt the S3 object.

   Show answer

   Answer: D

   Explanation

   The correct answer is D. Here is why: The Lambda function is configured to access the S3 bucket: The data engineer has already set up the Lambda function's execution role to access the S3 bucket. This means that basic S3 access permissions are likely in place. The object is encrypted with a KMS key: This is a crucial detail. When an object in S3 is encrypted with a KMS key, any entity trying to read that object needs two sets of permissions: a. Permission to access the S3 bucket and object b. Permission to use the specific KMS key for decryption The error occurs when trying to retrieve the content: This suggests that the Lambda function can likely see the object (as it has S3 access) but fails when trying to read its contents. To resolve this issue, the data engineer should grant the Lambda function's execution role the required KMS permissions. Specifically, add the 'kms:Decrypt' permission for the KMS key used to encrypt the S3 object.

   Source: Adapted from community discussion — AgboolaKun

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3. Question 43 · 313 in bank

   A data engineer has implemented data quality rules in 1,000 AWS Glue Data Catalog tables. Because of a recent change in business requirements, the data engineer must edit the data quality rules. How should the data engineer meet this requirement with the LEAST operational overhead?

   • ACreate a pipeline in AWS Glue ETL to edit the rules for each of the 1,000 Data Catalog tables. Use an AWS Lambda function to call the corresponding AWS Glue job for each Data Catalog table.
   • BCreate an AWS Lambda function that makes an API call to AWS Glue Data Quality to make the edits.
   • CCreate an Amazon EMR cluster. Run a pipeline on Amazon EMR that edits the rules for each Data Catalog table. Use an AWS Lambda function to run the EMR pipeline.
   • DUse the AWS Management Console to edit the rules within the Data Catalog.

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   Answer: B

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4. Question 44 · 313 in bank

   Two developers are working on separate application releases. The developers have created feature branches named Branch A and Branch B by using a GitHub repository’s master branch as the source. The developer for Branch A deployed code to the production system. The code for Branch B will merge into a master branch in the following week’s scheduled application release. Which command should the developer for Branch B run before the developer raises a pull request to the master branch?

   • Agit diff branchB master git commit -m
   • Bgit pull master
   • Cgit rebase master
   • Dgit fetch -b master

   Show answer

   Answer: C

   Explanation

   The correct answer is C. Here is why: Rebasing Branch B onto the updated master branch ensures that Branch B incorporates all the recent changes from the master branch (including the changes from Branch A that were deployed to production). It helps maintain a linear, clean history by placing Branch B's commits on top of the latest master branch commits. This approach reduces the likelihood of merge conflicts when the pull request is eventually merged into master. It makes the code review process easier as all the changes in the pull request will be relevant and up-to-date. By using git rebase master, the developer ensures that Branch B is up-to-date with all changes in the master branch, including those from Branch A, before creating the pull request. This approach helps maintain a clean, linear history and reduces the likelihood of conflicts during the merge process.

   Source: Adapted from community discussion — AgboolaKun

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5. Question 45 · 313 in bank

   Select 2

   A company stores employee data in Amazon Resdshift. A table names Employee uses columns named Region ID, Department ID, and Role ID as a compound sort key. Which queries will MOST increase the speed of query by using a compound sort key of the table? (Choose two.)

   • ASelect *from Employee where Region ID=’North America’;
   • BSelect *from Employee where Region ID=’North America’ and Department ID=20;
   • CSelect *from Employee where Department ID=20 and Region ID=’North America’;
   • DSelect *from Employee where Role ID=50;
   • ESelect *from Employee where Region ID=’North America’ and Role ID=50;

   Show answer

   Answer: BE

   Explanation

   To maximize the speed of queries by using the compound sort key (Region ID, Department ID, and Role ID) in the Employee table in Amazon Redshift, the queries should align with the order of the columns in the sort key.

   Source: Adapted from community discussion — antun3ra

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6. Question 46 · 313 in bank

   A company loads transaction data for each day into Amazon Redshift tables at the end of each day. The company wants to have the ability to track which tables have been loaded and which tables still need to be loaded. A data engineer wants to store the load statuses of Redshift tables in an Amazon DynamoDB table. The data engineer creates an AWS Lambda function to publish the details of the load statuses to DynamoDB. How should the data engineer invoke the Lambda function to write load statuses to the DynamoDB table?

   • AUse a second Lambda function to invoke the first Lambda function based on Amazon CloudWatch events.
   • BUse the Amazon Redshift Data API to publish an event to Amazon EventBridge. Configure an EventBridge rule to invoke the Lambda function.
   • CUse the Amazon Redshift Data API to publish a message to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke the Lambda function.
   • DUse a second Lambda function to invoke the first Lambda function based on AWS CloudTrail events.

   Show answer

   Answer: B

   Explanation

   The most appropriate way for the data engineer to invoke the Lambda function to write load statuses to the DynamoDB table is: B. Use the Amazon Redshift Data API to publish an event to Amazon EventBridge. Configure an EventBridge rule to invoke the Lambda function. Explanation: Option B leverages the Amazon Redshift Data API to publish events to Amazon EventBridge, which provides a serverless event bus service for handling events across AWS services. By configuring an EventBridge rule to invoke the Lambda function in response to events published by the Redshift Data API, the data engineer can ensure that the Lambda function is triggered whenever there is a new transaction data load in Amazon Redshift. This approach offers a straightforward and scalable solution for tracking table load statuses without relying on additional Lambda functions or services.

   Source: Adapted from community discussion — TonyStark0122

   References

   • AWS documentation
   • AWS documentation
   • AWS documentation

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7. Question 47 · 313 in bank

   A company receives test results from testing facilities that are located around the world. The company stores the test results in millions of 1 KB JSON files in an Amazon S3 bucket. A data engineer needs to process the files, convert them into Apache Parquet format, and load them into Amazon Redshift tables. The data engineer uses AWS Glue to process the files, AWS Step Functions to orchestrate the processes, and Amazon EventBridge to schedule jobs. The company recently added more testing facilities. The time required to process files is increasing. The data engineer must reduce the data processing time. Which solution will MOST reduce the data processing time?

   • AUse AWS Lambda to group the raw input files into larger files. Write the larger files back to Amazon S3. Use AWS Glue to process the files. Load the files into the Amazon Redshift tables.
   • BUse the AWS Glue dynamic frame file-grouping option to ingest the raw input files. Process the files. Load the files into the Amazon Redshift tables.
   • CUse the Amazon Redshift COPY command to move the raw input files from Amazon S3 directly into the Amazon Redshift tables. Process the files in Amazon Redshift.
   • DUse Amazon EMR instead of AWS Glue to group the raw input files. Process the files in Amazon EMR. Load the files into the Amazon Redshift tables.

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   Answer: B

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8. Question 48 · 313 in bank

   A data engineer uses Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to run data pipelines in an AWS account. A workflow recently failed to run. The data engineer needs to use Apache Airflow logs to diagnose the failure of the workflow. Which log type should the data engineer use to diagnose the cause of the failure?

   • AYourEnvironmentName-WebServer
   • BYourEnvironmentName-Scheduler
   • CYourEnvironmentName-DAGProcessing
   • DYourEnvironmentName-Task

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   Answer: D

   Explanation

   https://pupuweb.com/amazon-dea-c01-which-apache-airflow-log-type-should-you-use-to-diagnose-workflow-failures-in-amazon-mwaa/ When a workflow fails to run in Amazon MWAA, the task logs (YourEnvironmentName-Task) are the most relevant for diagnosing the issue. Task logs contain detailed information about the execution of individual tasks within the workflow, including any error messages or stack traces that can help pinpoint the cause of the failure.

   Source: Adapted from community discussion — 150b64e

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9. Question 49 · 313 in bank

   Select 2

   A finance company uses Amazon Redshift as a data warehouse. The company stores the data in a shared Amazon S3 bucket. The company uses Amazon Redshift Spectrum to access the data that is stored in the S3 bucket. The data comes from certified third-party data providers. Each third-party data provider has unique connection details. To comply with regulations, the company must ensure that none of the data is accessible from outside the company's AWS environment. Which combination of steps should the company take to meet these requirements? (Choose two.)

   • AReplace the existing Redshift cluster with a new Redshift cluster that is in a private subnet. Use an interface VPC endpoint to connect to the Redshift cluster. Use a NAT gateway to give Redshift access to the S3 bucket.
   • BCreate an AWS CloudHSM hardware security module (HSM) for each data provider. Encrypt each data provider's data by using the corresponding HSM for each data provider.
   • CTurn on enhanced VPC routing for the Amazon Redshift cluster. Set up an AWS Direct Connect connection and configure a connection between each data provider and the finance company’s VPC.
   • DDefine table constraints for the primary keys and the foreign keys.
   • EUse federated queries to access the data from each data provider. Do not upload the data to the S3 bucket. Perform the federated queries through a gateway VPC endpoint.

   Show answer

   Answer: AC

   Explanation

   A. Replace the existing Redshift cluster with a new Redshift cluster that is in a private subnet. Use an interface VPC endpoint to connect to the Redshift cluster. Use a NAT gateway to give Redshift access to the S3 bucket. C. Turn on enhanced VPC routing for the Amazon Redshift cluster. Set up an AWS Direct Connect connection and configure a connection between each data provider and the finance company’s VPC.

   Source: Adapted from community discussion — EJGisME

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10. Question 50 · 313 in bank

    Files from multiple data sources arrive in an Amazon S3 bucket on a regular basis. A data engineer wants to ingest new files into Amazon Redshift in near real time when the new files arrive in the S3 bucket. Which solution will meet these requirements?

    • AUse the query editor v2 to schedule a COPY command to load new files into Amazon Redshift.
    • BUse the zero-ETL integration between Amazon Aurora and Amazon Redshift to load new files into Amazon Redshift.
    • CUse AWS Glue job bookmarks to extract, transform, and load (ETL) load new files into Amazon Redshift.
    • DUse S3 Event Notifications to invoke an AWS Lambda function that loads new files into Amazon Redshift.

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    Answer: D

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DEA-C01 practice, question 41. 313 questions available.