Amazon Data-Engineer-Associate Practice Exam Questions

Amazon Data-Engineer-Associate Sample Question Answers

Question # 1

A company has a data warehouse that contains a table that is named Sales. The company stores the table in Amazon Redshift The table includes a column that is named city_name. The company wants to query the table to find all rows that have a city_name that starts with "San" or "El."Which SQL query will meet this requirement?

A. Select * from Sales where city_name - '$(San|EI)";
B. Select * from Sales where city_name -, ^(San|EI) *';
C. Select * from Sales where city_name - '$(San&EI)";
D. Select * from Sales where city_name -, ^(San&EI)";

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Question # 2

A company is uploading log files from on-premises servers to an Amazon S3 bucket. The company needs to validate that the logs from the on-premises servers are the same as the logs that are stored in the S3 bucket.Which solution will meet this requirement?

A. Use the AWS SDK to automatically compute CRC32 checksums during the upload. Store the checksums in S3 object metadata.
B. Create an AWS Lambda function to calculate SHA-256 checksums. Store the results in a separate metadata table. Validate the logs after the upload.
C. Enable S3 Object Lock in compliance mode on the S3 bucket. Upload the objects to the bucket.
D. After uploading the objects to the S3 bucket, enable S3 Object Lock in governance mode on the S3 objects.

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Question # 3

A company is building a data stream processing application. The application runs in an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The application stores processed data in an Amazon DynamoDB table.The company needs the application containers in the EKS cluster to have secure access to the DynamoDB table. The company does not want to embed AWS credentials in the containers.Which solution will meet these requirements?

A. Store the AWS credentials in an Amazon S3 bucket. Grant the EKS containers access to the S3 bucket to retrieve the credentials.
B. Attach an IAM role to the EKS worker nodes. Grant the IAM role access to DynamoDB. Use the IAM role to set up IAM roles service accounts (IRSA) functionality.
C. Create an IAM user that has an access key to access the DynamoDB table. Use environment variables in the EKS containers to store the IAM user access key data.
D. Create an IAM user that has an access key to access the DynamoDB table. Use Kubernetes secrets that are mounted in a volume of the EKS cluster nodes to store the user access key data.

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Question # 4

A company has a data processing pipeline that runs multiple SQL queries in sequence against an Amazon Redshift cluster. The company merges with a second company. The original company modifies a query that aggregates sales revenue data to join sales tables from both companies.The sales table for the first company is named Table S1 and contains 10 billion records. The sales table for the second company is named Table S2 and contains 900 million records. The query becomes slow after the modification.A data engineer must improve the query performance.Which solutions will meet these requirements? (Select TWO)

A. Use the KEY distribution style for both sales tables. Select a low-cardinality column to use for the join.
B. Use the KEY distribution style for both sales tables. Select a high-cardinality column to use for the join.
C. Use the EVEN distribution style for Table S1. Use the ALL distribution style for Table S2.
D. Use the Amazon Redshift query optimizer to review and select optimizations to i l t implement.
E. Use Amazon Redshift Advisor to review and select optimizations to implement.

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Question # 5

A data engineer is optimizing query performance in Amazon Athena notebooks that use Apache Spark to analyze large datasets that are stored in Amazon S3. The data is partitioned. An AWS Glue crawler updates the partitions.The data engineer wants to minimize the amount of data that is scanned to improve efficiency of Athena queries.Which solution will meet these requirements?

A. Apply partition filters in the queries.
B. Increase the frequency of AWS Glue crawler invocations to update the data catalog more often.
C. Organize the data that is in Amazon S3 by using a nested directory structure.
D. Configure Spark to use in-memory caching for frequently accessed data.

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Question # 6

A company stores time-series data that is collected from streaming services in an Amazon S3 bucket. The company must ensure that only workloads that are deployed within the company's VPC can access the data.Which solution will meet this requirement?

A. Create an S3 bucket policy that uses a condition to allow access only to traffic that originates from the company's VPC.
B. Apply a security group to the S3 bucket that allows connections only from the company's VPC CIDR block.
C. Define an IAM policy that denies access to all users unless the request originates from within the company's VPC.
D. Use a network ACL on the VPC subnets to allow only specific resources to access the S3 bucket.

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Question # 7

A company uses AWS Glue Apache Spark jobs to handle extract, transform, and load (ETL) workloads. The company has enabled logging and monitoring for all AWS Glue jobs. One of the AWS Glue jobs begins to fail. A data engineer investigates the error and wants to examine metrics for all individual stages within the job. How can the data engineer access the stage metrics?

A. Examine the AWS Glue job and stage details in the Spark UI.
B. Examine the AWS Glue job and stage metrics in Amazon CloudWatch.
C. Examine the AWS Glue job and stage logs in AWS CloudTrail logs.
D. Examine the AWS Glue job and stage details by using the run insights feature on the job.

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Question # 8

A data engineer needs Amazon Athena queries to finish faster. The data engineer notices that all the files the Athena queries use are currently stored in uncompressed .csv format. The data engineer also notices that users perform most queries by selecting a specific column.Which solution will MOST speed up the Athena query performance?

A. Change the data format from .csvto JSON format. Apply Snappy compression.
B. Compress the .csv files by using Snappy compression.
C. Change the data format from .csvto Apache Parquet. Apply Snappy compression.
D. Compress the .csv files by using gzjg compression.

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Question # 9

A company uses Amazon S3 as a data lake. The company sets up a data warehouse by using a multi-node Amazon Redshift cluster. The company organizes the data files in the data lake based on the data source of each data file.The company loads all the data files into one table in the Redshift cluster by using a separate COPY command for each data file location. This approach takes a long time to load all the data files into the table. The company must increase the speed of the data ingestion. The company does not want to increase the cost of the process. Which solution will meet these requirements?

A. Use a provisioned Amazon EMR cluster to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.
B. Load all the data files in parallel into Amazon Aurora. Run an AWS Glue job to load the data into Amazon Redshift.
C. Use an AWS Glue job to copy all the data files into one folder. Use a COPY command to load the data into Amazon Redshift.
D. Create a manifest file that contains the data file locations. Use a COPY command to load the data into Amazon Redshift.

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Question # 10

A data engineer uses AWS Lake Formation to manage access to data that is stored in an Amazon S3 bucket. The data engineer configures an AWS Glue crawler to discover data at a specific file location in the bucket, s3://examplepath. The crawler execution fails with the following error:"The S3 location: s3://examplepath is not registered."The data engineer needs to resolve the error.

A. Attach an appropriate IAM policy to the IAM role of the AWS Glue crawler to grant the crawler permission to read the S3 location.
B. Register the S3 location in Lake Formation to allow the crawler to access the data.
C. Create a new AWS Glue database. Assign the correct permissions to the database for the crawler.
D. Configure the S3 bucket policy to allow cross-account access.

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