Import from S3 in DynamoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

What is the result of this import command?

You run the following AWS CLI command to import data from an S3 bucket into a DynamoDB table. What will be the status of the import job immediately after running this command?

DynamoDB

aws dynamodb import-table --input-format DYNAMODB_JSON --s3-bucket-source S3Bucket=mybucket,S3KeyPrefix=data.json --table-name MyTable

A The import job status will be 'FAILED'.

B The import job status will be 'COMPLETED'.

C The import job status will be 'IN_PROGRESS'.

D The import job status will be 'NOT_STARTED'.

💡 Hint

Think about what happens right after starting a data import job.

When you start an import job, it begins processing asynchronously. So immediately after running the command, the status is 'IN_PROGRESS'. It will only be 'COMPLETED' after the import finishes.

🧠 Conceptual

intermediate

Which data format is supported for DynamoDB import from S3?

You want to import data from an S3 bucket into DynamoDB. Which of the following data formats can you use for the import?

A DynamoDB JSON format

B CSV format with headers

C XML format

D Plain text with comma-separated values

💡 Hint

DynamoDB expects a specific JSON format for import.

DynamoDB import supports the DynamoDB JSON format, which represents data types explicitly. CSV, XML, or plain text are not supported for direct import.

🔧 Debug

advanced

Why does this import command fail with AccessDeniedException?

You run this command to import data from S3 to DynamoDB but get an AccessDeniedException error: aws dynamodb import-table --input-format DYNAMODB_JSON --s3-bucket-source S3Bucket=mybucket,S3KeyPrefix=data.json --table-name MyTable What is the most likely cause?

A The AWS CLI version is outdated.

B The DynamoDB table name is invalid.

C The input file is not in DynamoDB JSON format.

D The IAM role used does not have permission to read the S3 bucket.

💡 Hint

AccessDeniedException usually relates to permissions.

The error indicates the AWS identity running the command lacks permission to access the S3 bucket. You must ensure the IAM role or user has s3:GetObject permission for the bucket.

📝 Syntax

advanced

Which command correctly imports data from S3 to DynamoDB with a specified IAM role?

You want to import data from S3 to DynamoDB and specify an IAM role ARN for the import job. Which command is correct?

A aws dynamodb import-table --input-format DYNAMODB_JSON --s3-bucket-source S3Bucket=bucket,S3KeyPrefix=data.json --table-name MyTable --role-arn arn:aws:iam::123456789012:role/MyImportRole

B aws dynamodb import-table --input-format DYNAMODB_JSON --s3-bucket-source S3Bucket=bucket,S3KeyPrefix=data.json --table-name MyTable --import-role arn:aws:iam::123456789012:role/MyImportRole

C aws dynamodb import-table --input-format DYNAMODB_JSON --s3-bucket-source S3Bucket=bucket,S3KeyPrefix=data.json --table-name MyTable --role arn:aws:iam::123456789012:role/MyImportRole

D aws dynamodb import-table --input-format DYNAMODB_JSON --s3-bucket-source S3Bucket=bucket,S3KeyPrefix=data.json --table-name MyTable --iam-role arn:aws:iam::123456789012:role/MyImportRole

💡 Hint

Check the exact parameter name for specifying the IAM role ARN in the import command.

The correct parameter to specify the IAM role ARN for the import job is '--role-arn'. Other options are invalid and cause syntax errors.

❓ optimization

expert

How to optimize import speed from S3 to DynamoDB for large datasets?

You have a large dataset in S3 to import into DynamoDB. Which approach will best optimize the import speed?

A Compress the data file with gzip and import directly.

B Split the data into multiple files in S3 and run multiple import jobs in parallel.

C Import the data using the AWS console instead of CLI.

D Use a single large file and run one import job to avoid overhead.

💡 Hint

Think about parallel processing and how DynamoDB import jobs work.

Splitting data into multiple files and running parallel import jobs can speed up the overall import by using more resources concurrently. Single large files or compression do not improve import speed directly. The AWS console does not affect import speed.