MLS-C01 Practice Test 39 — 15 Questions

Question 1

A company is using AWS Glue ETL jobs to process data stored in Amazon S3. The jobs currently run sequentially and take too long. The data engineer wants to reduce job duration without rewriting the code. Which action is most effective?

Accepted Answer

Increase the number of DPUs (Data Processing Units) for the job. Increasing the number of DPUs (Data Processing Units) allocated to the Glue job can parallelize the processing and reduce runtime without code changes. Option A (changing to a larger instance type) is not applicable because Glue uses DPUs, not EC2 instances. Option B (using a different data format) may help but is not a direct solution for parallelization. Option D (enabling job bookmarks) helps with incremental processing but does not speed up the existing job.

Answer

Change the underlying EC2 instance type to a compute-optimized instance

Answer

Convert the data from CSV to Parquet format

Answer

Enable job bookmarks to skip already processed data

Question 2

A company uses Amazon Redshift for data warehousing. The data engineering team notices that query performance has degraded over time. Which THREE actions should the team take to improve performance? (Choose THREE.)

Accepted Answer

Define appropriate sort keys on large tables. Sort keys help the query optimizer scan less data. Distribution keys reduce data shuffling. ANALYZE commands update statistics for the optimizer. Option B (increasing node count) is costly and not always necessary. Option D (deleting old data) may help but is not a direct performance tuning technique.

Answer

Increase the number of nodes in the Redshift cluster

Answer

Delete old data that is no longer needed

Question 3

Which TWO AWS services can be used to move data from an on-premises database to Amazon S3 on a recurring schedule without writing custom code? (Choose 2.)

Accepted Answer

AWS Glue. AWS Database Migration Service (DMS) can perform continuous replication from on-premises databases to S3. AWS Glue can run scheduled ETL jobs to pull data from on-premises sources via JDBC and write to S3. Option A is wrong because Snowball is a one-time physical transfer. Option D is wrong because Kinesis Data Firehose is for streaming, not scheduled batch. Option E is wrong because Athena is a query service, not a data movement tool.

Answer

AWS Snowball Edge

Answer

Amazon Athena

Answer

Amazon Kinesis Data Firehose

Question 4

A data scientist needs to run a one-time SQL query on a large dataset in Amazon S3. The dataset is stored in Parquet format and is about 500 GB. The query requires complex aggregations and joins. Which AWS service should be used to minimize cost and setup time?

Accepted Answer

Amazon Athena. Amazon Athena is serverless and charges per query, ideal for one-time queries on S3 data. Option B (Amazon EMR) requires cluster setup and management. Option C (Amazon Redshift) requires provisioning a cluster. Option D (Amazon RDS) is not designed for direct S3 querying.

Answer

Amazon Redshift

Answer

Amazon RDS for MySQL

Answer

Amazon EMR with Spark SQL

Question 5

A data engineer needs to process streaming data from an IoT fleet and store the results in Amazon S3 for analysis. The solution must be serverless and handle data that arrives at irregular intervals. Which AWS service should be used to ingest the data?

Accepted Answer

AWS IoT Core. Option B is correct because AWS IoT Core is designed to ingest data from IoT devices securely and at scale, and it integrates with other AWS services for processing. Option A is wrong because Kinesis Data Streams is for real-time streaming but not specifically for IoT device connectivity. Option C is wrong because SQS is a message queue, not optimized for IoT ingestion. Option D is wrong because S3 is storage, not ingestion.

Answer

Amazon S3

Answer

Amazon Simple Queue Service (SQS)

Answer

Amazon Kinesis Data Streams

Question 6

A data engineer created a CloudFormation template for a Glue ETL job as shown. The job processes 500 GB of data and takes 90 minutes to complete. However, the job fails after 60 minutes. What is the MOST likely cause?

Accepted Answer

The Timeout property is set to 60 minutes, but the job requires more time.. Option C is correct because the Timeout is set to 60 minutes, but the job takes 90 minutes, so it is killed. Option A is wrong because the script location is correct. Option B is wrong because the role appears correctly configured. Option D is wrong because MaxRetries is 0, but the job fails due to timeout, not due to retry policy.

Answer

The IAM role does not have sufficient permissions.

Answer

The ScriptLocation S3 bucket is in a different region.

Answer

The MaxRetries property is set to 0, so the job does not retry on failure.

Question 7

A company is designing a data pipeline that ingests streaming data from social media feeds. The data must be processed in real-time to detect trending topics, and results must be stored in Amazon DynamoDB for low-latency access. Which services should the company use? (Choose TWO.)

Accepted Answer

Amazon Kinesis Data Analytics. Option A (Kinesis Data Streams) is required for ingestion, and Option D (Kinesis Data Analytics) is required for real-time trending detection. Option B (SQS) is not for streaming. Option C (Lambda) can process but is not the best for real-time analytics on streams. Option E (Firehose) is near-real-time, not real-time.

Answer

Amazon Kinesis Data Firehose

Answer

AWS Lambda

Answer

Amazon Simple Queue Service (SQS)

Question 8

A company is building a data lake on Amazon S3. They need to enforce encryption at rest for all objects. Which combination of actions will achieve this? (Assume the bucket is versioned.)

Accepted Answer

Enable S3 default encryption and set a bucket policy to deny PutObject without encryption headers. Enabling default encryption on the bucket ensures all new objects are encrypted. Adding a bucket policy that denies PutObject without encryption headers prevents unencrypted uploads. The other options do not enforce encryption for all objects.

Answer

Use AWS KMS with automatic key rotation

Answer

Enable S3 default encryption only

Answer

Enable S3 Block Public Access

Question 9

A data science team uses Amazon SageMaker to train models on a dataset stored in Amazon S3. The dataset is 2 TB and is accessed by multiple training jobs. The team notices that training jobs are slow due to high S3 GET request latency. Which solution would provide the fastest and most cost-effective data access?

Accepted Answer

Mount an Amazon FSx for Lustre file system integrated with the S3 bucket. Using Amazon FSx for Lustre as a managed Lustre file system with S3 integration provides high-throughput, low-latency access for training jobs. Option A (Cluster Placement Group) reduces network latency but does not improve S3 access. Option B (Elastic Fabric Adapter) improves inter-node communication, not data access from S3. Option D (S3 Transfer Acceleration) improves upload speed, not GET latency for large datasets.

Answer

Place all training instances in a Cluster Placement Group

Answer

Enable S3 Transfer Acceleration on the bucket

Answer

Use Elastic Fabric Adapter (EFA) for training instances

Question 10

A data engineer is building a data pipeline that ingests streaming data from IoT devices. The data must be processed in near real-time and stored in Amazon S3 for further analysis. Which AWS service should be used to capture and process the streaming data before storing it in S3?

Accepted Answer

Use Amazon Kinesis Data Streams to capture the data and Amazon Kinesis Data Firehose to deliver it to S3.. Amazon Kinesis Data Streams is designed for real-time data ingestion and can be integrated with Lambda for processing. Kinesis Data Firehose can then load the data into S3. Option A is wrong because S3 is a storage service, not a streaming ingestion service. Option B is wrong because AWS Glue is for ETL and cataloging, not real-time streaming. Option D is wrong because SQS is a message queue, not optimized for streaming analytics.

Answer

Use Amazon S3 with S3 Event Notifications to trigger AWS Lambda for processing.

Answer

Use AWS Glue to perform ETL on the streaming data.

Answer

Use Amazon Simple Queue Service (SQS) to buffer the data and then process it with AWS Lambda.

Question 11

Which THREE factors should be considered when choosing between Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose for a real-time data ingestion pipeline? (Choose 3.)

Accepted Answer

Need for custom data processing using AWS Lambda. Kinesis Data Streams provides custom processing with shard-level throughput and retention up to 365 days. Firehose automatically delivers to destinations like S3, Redshift, and Elasticsearch with near-real-time latency. Option A is wrong because both support encryption. Option D is wrong because both support compression before delivery. Option E is wrong because both can handle streaming data, but Firehose is simpler for delivery to S3.

Answer

Ability to compress data before delivery

Answer

Ability to encrypt data at rest

Question 12

A data engineering team is building a pipeline to process terabytes of log data daily using Amazon EMR with Spark. The data arrives in hourly batches and must be processed within 4 hours. The team needs to minimize cost. Which cluster configuration is MOST cost-effective?

Accepted Answer

Use a transient cluster with a mix of on-demand and spot instances, terminated after the job completes.. Option B is correct because spot instances offer significant cost savings and are suitable for fault-tolerant Spark jobs. Option A is wrong because on-demand is more expensive. Option C is wrong because a single large instance reduces parallelism. Option D is wrong because EMR Serverless may be more expensive for predictable, large workloads.

Answer

Use a single large instance with multiple cores to avoid data shuffling.

Answer

Use a long-running cluster of on-demand instances to avoid startup time.

Answer

Use Amazon EMR Serverless to automatically scale.

Question 13

A team is building a data lake on Amazon S3 and using AWS Glue to catalog data. They notice that Glue crawlers are taking too long to update the catalog for a large dataset with millions of small files. Which approach will MOST improve crawler performance?

Accepted Answer

Consolidate the small files into larger files (e.g., 100 MB each).. Option D is correct because consolidating small files into larger files reduces the number of objects the crawler must scan. Option A is wrong because increasing crawler frequency doesn't reduce scan time. Option B is wrong because using a custom classifier doesn't reduce scan time. Option C is wrong because partitioning helps but still many files per partition.

Answer

Increase the frequency of the crawler runs.

Answer

Partition the data by date in S3.

Answer

Use a custom classifier to parse the data.

Question 14

A data scientist needs to query a dataset stored as Parquet files in Amazon S3 using standard SQL without managing any infrastructure. Which service should they use?

Accepted Answer

Amazon Athena. Amazon Athena is serverless and allows SQL queries directly on S3 data. Redshift requires a cluster. Glue is for ETL. QuickSight is for visualization.

Answer

Amazon QuickSight

Answer

AWS Glue

Answer

Amazon Redshift

Question 15

A data engineer runs the CLI command to download an object from S3. The bucket owner is 123456789012, and the engineer's IAM user has s3:GetObject permission on the bucket. The object was uploaded by a different AWS account. What is the MOST likely reason for the AccessDenied error?

Accepted Answer

The object is owned by a different AWS account, and the bucket owner has not been granted access. By default, objects uploaded by another account are owned by the uploading account, and the bucket owner does not have access unless explicitly granted via bucket policy or ACL. The --expected-bucket-owner parameter only checks the bucket owner, not the object. The engineer's permissions are on the bucket, but the object is owned by another account, so the bucket owner needs additional permissions.

Answer

The --expected-bucket-owner parameter is incorrect

Answer

The bucket policy denies access to the engineer's IAM user

Answer

The IAM policy does not allow s3:GetObject for that specific key