MLS-C01 Data Engineering Practice Test 7 — 15 Questions

Question 1

A company uses Amazon Kinesis Data Analytics for real-time anomaly detection on a stream of IoT sensor data. The application is experiencing high latency. The data volume has doubled. Which action would MOST effectively reduce latency?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Increase the Parallelism setting of the Kinesis Data Analytics application. Increasing the Parallelism setting of the Kinesis Data Analytics application directly allocates more processing resources (e.g., more Kinesis Processing Units or KPUs) to handle the doubled data volume. This allows the application to process records concurrently, reducing the per-record processing time and overall latency. Parallelism is the primary scaling mechanism for Kinesis Data Analytics to match throughput increases.

Answer

Change the record format from JSON to Avro

Answer

Decrease the retention period of the source stream

Answer

Increase the number of shards in the source Kinesis stream

Question 2

A data engineer needs to transfer 50 TB of historical data from an on-premises HDFS cluster to Amazon S3. The company has a 1 Gbps internet connection. Which service would complete the transfer in the shortest time?

Accepted Answer

AWS Snowball. AWS Snowball is the correct choice because transferring 50 TB over a 1 Gbps internet connection would take approximately 5.5 days (50 TB × 1024 GB/TB × 8 bits/byte ÷ 1 Gbps ÷ 86400 seconds/day), assuming full utilization, which is unrealistic due to overhead and contention. Snowball provides a physical appliance that can be loaded with data locally and shipped to AWS, completing the transfer in a few days including shipping time, making it faster than any network-based method for this volume.

Answer

Amazon S3 Transfer Acceleration

Answer

AWS Direct Connect

Answer

AWS DataSync

Question 3

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. Combining S3 default encryption with a bucket policy that denies PutObject requests lacking encryption headers ensures that every object stored in the bucket is encrypted at rest, even if the PutObject call does not include encryption parameters. Default encryption alone can be overridden by a client that explicitly sets encryption headers, but the bucket policy enforces encryption for all uploads, closing that loophole. This dual approach guarantees compliance with encryption-at-rest requirements for a versioned bucket.

Answer

Use AWS KMS with automatic key rotation

Answer

Enable S3 default encryption only

Answer

Enable S3 Block Public Access

Question 4

A company uses Amazon EMR with Spark to process data daily. The job reads from S3 and writes to S3. Recently, the job started failing with 'S3AccessDenied' errors. The IAM role used by EMR has not changed. What is the MOST likely cause?

Accepted Answer

The S3 bucket policy was updated to deny access to the EMR role. The IAM role used by EMR has not changed, but the S3 bucket policy can be updated independently to deny access to that specific role. An explicit deny in a bucket policy overrides any allow in the IAM policy, causing the 'S3AccessDenied' error even though the role itself remains unchanged. This is the most likely cause because the job was previously working and only the bucket policy could have been modified without touching the EMR configuration.

Answer

The EMR cluster's security group blocks outbound traffic

Answer

The S3 bucket was deleted and recreated

Answer

The EMR service role was rotated

Question 5

A company is designing a data pipeline to ingest data from multiple sources into an Amazon S3 data lake. The data must be encrypted at rest and in transit. Which TWO actions should be taken to meet these requirements?

Accepted Answer

Enable Server-Side Encryption on the S3 bucket. Enabling Server-Side Encryption (SSE-S3 or SSE-KMS) on the S3 bucket automatically encrypts data at rest when written to disk, using AES-256 encryption. This meets the requirement for encryption at rest without any client-side changes.

Answer

Enable S3 Transfer Acceleration

Answer

Use client-side encryption before uploading

Answer

Use S3 VPC Endpoint

Question 6

A data engineering team uses AWS Glue to run ETL jobs. They notice that jobs are taking longer to complete as data volume grows. They want to optimize performance without increasing cost significantly. Which THREE strategies should they consider?

Accepted Answer

Partition the input data in S3. Partitioning input data in S3 (B) allows AWS Glue to use partition pruning, reading only the relevant subsets of data instead of scanning the entire dataset. This reduces I/O and processing time, directly addressing the performance degradation caused by growing data volumes.

Answer

Remove partitioning from the output

Answer

Use Amazon EMR instead of Glue

Question 7

A company wants to analyze streaming data from IoT devices in near-real-time. They need to store raw data in Amazon S3 and also run SQL queries on the streaming data. Which TWO services should they use?

Accepted Answer

Amazon Kinesis Data Analytics. Amazon Kinesis Data Analytics is correct because it enables running SQL queries on streaming data in near-real-time, allowing the company to analyze IoT data as it arrives without needing to store it first. It integrates directly with Kinesis Data Streams or Firehose to process data streams using standard SQL, making it ideal for real-time analytics on streaming data.

Answer

AWS Glue

Answer

Amazon Kinesis Data Streams

Answer

AWS Lambda

Question 8

An IAM policy is attached to a group. A user in the group tries to read the object s3://data-lake-bucket/sensitive/file.txt from an IP address 192.168.1.1. What will happen?

Accepted Answer

The request is denied because of the Deny statement. The Deny statement explicitly denies any S3 action on the sensitive prefix when the source IP is not from 10.0.0.0/8. Since the IP 192.168.1.1 is not in that range, the Deny applies. Deny statements override Allow statements. So the user is denied access.

Answer

The request is allowed because the Allow statement grants s3:GetObject

Answer

The request is allowed because the Deny condition does not match

Answer

The request is denied because the policy has no explicit Allow for the sensitive prefix

Question 9

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. When an object is uploaded to S3 by a different AWS account, the object is owned by the uploading account, not the bucket owner. By default, the bucket owner does not have access to objects uploaded by other accounts, even if the bucket owner has a policy granting s3:GetObject to their IAM users. The engineer's IAM user has permission on the bucket, but the object itself is not owned by the bucket owner, so the bucket owner cannot delegate access to it unless the object owner explicitly grants read access via an object ACL or a bucket policy that the object owner accepts.

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

Question 10

An S3 event notification is configured to trigger a Lambda function when new objects are created. The Lambda function processes the event JSON shown. Which field should the function use to read the new object from S3?

Accepted Answer

s3.bucket.arn and s3.object.key. The Lambda function needs the bucket name and object key to retrieve the new object from S3. The `s3.bucket.arn` provides the bucket identifier, and `s3.object.key` provides the object path. Together, they allow the function to call `GetObject` on the S3 API.

Answer

s3.s3SchemaVersion

Answer

awsRegion

Answer

eventName

Question 11

A data engineer needs to ingest streaming data from an on-premises Kafka cluster into Amazon S3 with minimal operational overhead. Which AWS service should be used to stream the data into S3 without managing servers?

Accepted Answer

Amazon Kinesis Data Firehose. Amazon Kinesis Data Firehose is the correct choice because it is a fully managed service that can directly ingest streaming data from an on-premises Kafka cluster (via a Kinesis Data Firehose HTTP endpoint or a custom producer) and deliver it to Amazon S3 without requiring any server management. It handles scaling, buffering, and compression automatically, minimizing operational overhead.

Answer

Amazon Kinesis Data Streams

Answer

AWS Glue

Answer

Amazon Managed Streaming for Apache Kafka (Amazon MSK)

Question 12

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) for the AWS Glue ETL job directly allocates more distributed computing resources, enabling parallel execution of the job's stages. This reduces the overall runtime without requiring any code changes, as Glue automatically distributes the workload across the additional DPUs.

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 13

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. Amazon FSx for Lustre provides a high-performance, POSIX-compliant file system that can be directly linked to an S3 bucket, allowing training instances to access data with sub-millisecond latency instead of S3 GET request latency. This integration enables data to be read from the Lustre file system at up to hundreds of gigabytes per second of throughput, which is significantly faster than reading directly from S3, and it is cost-effective because you only pay for the storage and throughput you provision during training.

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 14

A company runs a daily ETL job that reads data from Amazon RDS, transforms it using AWS Glue, and writes the results to Amazon S3. The job started failing yesterday with the error: 'Rate exceeded'. What is the most likely cause and solution?

Accepted Answer

The RDS database is overwhelmed by the number of connections; reduce the Glue job's parallelism or increase RDS instance size. The 'Rate exceeded' error in an AWS Glue job reading from Amazon RDS typically indicates that the database is being overwhelmed by too many concurrent connections or queries. AWS Glue jobs can spawn multiple executors, each opening connections to RDS, and if the database's max_connections or IOPS limit is exceeded, RDS throttles requests. Reducing the Glue job's parallelism (e.g., setting the number of executors or DPUs lower) or scaling up the RDS instance (e.g., increasing instance size or provisioned IOPS) resolves the issue.

Answer

The Glue job is using too many DPUs; reduce the number of DPUs

Answer

The S3 bucket has reached its request rate limit; request a limit increase

Answer

Enable job bookmarks in the Glue job to process only new data

Question 15

A company wants to analyze historical data stored in Amazon S3 using Amazon Athena. The data is in CSV format and is partitioned by date. Which action will provide the best query performance and cost optimization?

Accepted Answer

Convert the data to Parquet format and use the existing partition structure. Converting data to Parquet and partitioning provides the best performance and cost savings because Athena can use predicate pushdown and column pruning, scanning less data. Option A (using Glue to gzip compress) still uses CSV which requires full scan. Option B (S3 event notification to warm up Athena) is not relevant because Athena caches results but doesn't need warming. Option C (only partitioning) helps but CSV is still row-based and less efficient than Parquet.

Answer

Use AWS Glue to compress the CSV files with gzip

Answer

Create an S3 event notification to trigger a Lambda function that warms up Athena

Answer

Keep CSV format but ensure partitions are in the format year=YYYY/month=MM/day=DD