Amazon Web Services Data-Engineer-Associate Exam With Confidence Using Practice Dumps

For high-performance analytics in Athena and EMR Spark, the columnar storage formats Parquet and ORC deliver the shortest query times. These formats minimize I/O, enable predicate pushdown, and support efficient compression and parallel reads.

When integrated with the AWS Glue Data Catalog, schema evolution is automatically tracked and managed across queries.

This combination (Parquet/ORC + Glue Catalog) is explicitly recommended by AWS for analytical workloads on S3 data lakes.

“For analytical workloads using Amazon EMR and Athena, store data in columnar formats such as Parquet or ORC. These formats provide optimized compression and query performance.”

– Ace the AWS Certified Data Engineer – Associate Certification – version 2 – apple.pdf

“Use the AWS Glue Data Catalog to manage table schemas and schema evolution for columnar data formats such as Parquet and ORC.”

– Ace the AWS Certified Data Engineer – Associate Certification – version 2 – apple.pdf

Therefore, using ORC or Parquet along with the Glue Data Catalog achieves the shortest Athena query times and seamless schema management.

The company needs to ingest tables from an on-premises Oracle database into a data lake on Amazon S3 in Apache Parquet format. The most efficient solution, requiring the least manual effort, would be to use AWS Database Migration Service (DMS) for continuous data replication.

Option C: Create an AWS Database Migration Service (AWS DMS) task for ongoing replication. Set the Oracle database as the source. Set Amazon S3 as the target. Configure the task to write the data in Parquet format.AWS DMS can continuously replicate data from the Oracle database into Amazon S3, transforming it into Parquet format as it ingests the data. DMS simplifies the process by providing ongoing replication with minimal setup, and it automatically handles the conversion to Parquet format without requiring manual transformations or separate jobs. This option is the least effort solution since it automates both the ingestion and transformation processes.

Other options:

Option A (Apache Sqoop on EMR) involves more manual configuration and management, including setting up EMR clusters and writing Sqoop jobs.

Option B (AWS Glue bookmark job) involves configuring Glue jobs, which adds complexity. While Glue supports data transformations, DMS offers a more seamless solution for database replication.

Option D (RDS and Lambda triggers) introduces unnecessary complexity by involving RDS and Lambda for a task that DMS can handle more efficiently.

Problem Analysis:

The company needs cross-account access to allow QuickSight in BI-Account to interact with an S3 bucket in Hub-Account.

The bucket is encrypted with an AWS KMS key.

Appropriate permissions must be set for both S3 access and KMS decryption.

Key Considerations:

QuickSight requires IAM permissions to access S3 data and decrypt files using the KMS key.

Both S3 and KMS permissions need to be properly configured across accounts.

Solution Analysis:

Option A: Use Existing KMS Key for Encryption

While the existing KMS key is used for encryption, it must also grant decryption permissions to QuickSight.

Option B: Add S3 Bucket to QuickSight Role

Granting S3 bucket access to the QuickSight service role is necessary for cross-account access.

Option C: AWS RAM for Bucket Sharing

AWS RAM is not required; bucket policies and IAM roles suffice for granting cross-account access.

Option D: IAM Policy for KMS Access

QuickSight’s service role in BI-Account needs explicit permissions to use the KMS key for decryption.

Option E: Add KMS Key as Resource for Role

The KMS key must explicitly list the QuickSight role as an entity that can access it.

Implementation Steps:

S3 Bucket Policy in Hub-Account:Add a policy to the S3 bucket granting the QuickSight service role access:

json

{

"Version": "2012-10-17",

"Statement": [

{

"Effect": "Allow",

"Principal": { "AWS": "arn:aws:iam:::role/service-role/QuickSightRole" },

"Action": "s3:GetObject",

"Resource": "arn:aws:s3:::/*"

}

]

}

KMS Key Policy in Hub-Account:Add permissions for the QuickSight role:

{

"Version": "2012-10-17",

"Statement": [

{

"Effect": "Allow",

"Principal": { "AWS": "arn:aws:iam:::role/service-role/QuickSightRole" },

"Action": [

"kms:Decrypt",

"kms:DescribeKey"

],

"Resource": "*"

}

]

}

IAM Policy for QuickSight Role in BI-Account:Attach the following policy to the QuickSight service role:

{

"Version": "2012-10-17",

"Statement": [

{

"Effect": "Allow",

"Action": [

"s3:GetObject",

"kms:Decrypt"

],

"Resource": [

"arn:aws:s3:::/*",

"arn:aws:kms:::key/"

]

}

]

}

Setting Up Cross-Account S3 Access

AWS KMS Key Policy Examples

Amazon QuickSight Cross-Account Access