Free Access Snowflake.DEA-C01.v2026-09-04.q215 Practice Test (Page 10)

Question 41

A company has a frontend ReactJS website that uses Amazon API Gateway to invoke REST APIs. The APIs perform the functionality of the website. A data engineer needs to write a Python script that can be occasionally invoked through API Gateway. The code must return results to API Gateway.
Which solution will meet these requirements with the LEAST operational overhead?

A.Deploy a custom Python script on an Amazon Elastic Container Service (Amazon ECS) cluster.

B.Create an AWS Lambda Python function with provisioned concurrency.

C.Deploy a custom Python script that can integrate with API Gateway on Amazon Elastic Kubernetes Service (Amazon EKS).

D.Create an AWS Lambda function. Ensure that the function is warm by scheduling an Amazon EventBridge rule to invoke the Lambda function every 5 minutes by using mock events.

Question 42

A data engineer is configuring an AWS Glue Apache Spark extract, transform, and load (ETL) job. The job contains a sort-merge join of two large and equally sized DataFrames.
The job is failing with the following error: No space left on device.
Which solution will resolve the error?

A.Use the AWS Glue Spark shuffle manager.

B.Deploy are Amazon Elastic Block Store (Amazon EBS) volume for the job to use.

C.Convert the sort-merge join in the job to be a broadcast join.

D.Convert the DataFrames to DynamicFrames, and perform a DynamicFrame join in the job.

Question 43

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. The sales table for the second company is named Table S2. Table S1 contains 10 billion records. Table S2 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? (Choose 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 implement.

E.Use Amazon Redshift Advisor to review and select optimizations to implement.

Question 44

A company needs to set up a data catalog and metadata management for data sources that run in the AWS Cloud. The company will use the data catalog to maintain the metadata of all the objects that are in a set of data stores. The data stores include structured sources such as Amazon RDS and Amazon Redshift. The data stores also include semistructured sources such as JSON files and .xml files that are stored in Amazon S3.
The company needs a solution that will update the data catalog on a regular basis. The solution also must detect changes to the source metadata.
Which solution will meet these requirements with the LEAST operational overhead?

A.Use Amazon Aurora as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the Aurora data catalog. Schedule the Lambda functions to run periodically.

B.Use the AWS Glue Data Catalog as the central metadata repository. Use AWS Glue crawlers to connect to multiple data stores and to update the Data Catalog with metadata changes. Schedule the crawlers to run periodically to update the metadata catalog.

C.Use Amazon DynamoDB as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the DynamoDB data catalog. Schedule the Lambda functions to run periodically.

D.Use the AWS Glue Data Catalog as the central metadata repository. Extract the schema for Amazon RDS and Amazon Redshift sources, and build the Data Catalog. Use AWS Glue crawlers for data that is in Amazon S3 to infer the schema and to automatically update the Data Catalog.

Question 45

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?

A.The 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.

B.The data engineer misconfigured the permissions of the S3 bucket. The Lambda function could not access the object.

C.The Lambda function is using an outdated SDK version, which caused the read failure.

D.The Lambda function's execution role does not have the necessary permissions to access the KMS key that can decrypt the S3 object.

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