MLS-C01 Data Engineering Practice Test 20 — 15 Questions

Question 1

A data scientist needs to process a large volume of streaming data from IoT devices and store the results in Amazon S3 for further analysis. Which AWS service is most suitable for ingesting and processing this data in near real-time?

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

Accepted Answer

Amazon Kinesis Data Analytics. Amazon Kinesis Data Analytics is the most suitable service because it can process streaming data from IoT devices in near real-time using SQL or Apache Flink, and directly output the results to Amazon S3. It is designed for continuous, low-latency ingestion and analysis of data streams, making it ideal for this use case.

Answer

Amazon Redshift

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AWS Glue

Answer

Amazon EMR

Question 2

A company is using AWS Glue to run ETL jobs that transform data from Amazon S3 to Amazon Redshift. The jobs are failing intermittently with timeouts. What is the most likely cause?

Accepted Answer

The AWS Glue job does not have enough DPUs (Data Processing Units) allocated.. Intermittent timeouts in AWS Glue ETL jobs typically indicate insufficient resource allocation. DPUs (Data Processing Units) define the compute capacity for the job; if too few are allocated, the job may run slowly and exceed the default timeout (e.g., 2880 minutes) or internal service limits, especially when processing large datasets from S3 to Redshift. Increasing the DPU count or using the G.1X/G.2X worker types can resolve this.

Answer

The S3 bucket policy is too restrictive.

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The Amazon Redshift cluster is in maintenance mode.

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The source data is not compressed.

Question 3

A company uses Amazon Kinesis Data Streams to collect clickstream data. The data is consumed by a Lambda function that writes to DynamoDB. Occasionally, the Lambda function fails due to throttling from DynamoDB. How can the company resolve this issue without losing data?

Accepted Answer

Decrease the batch size in the Lambda event source mapping.. Decreasing the batch size in the Lambda event source mapping reduces the number of records sent to each Lambda invocation. This lowers the write throughput demand on DynamoDB per invocation, mitigating throttling while still allowing Lambda to retry failed records individually. The Kinesis stream retains data for up to 365 days, so no data is lost as long as the Lambda function eventually processes all records.

Answer

Ignore the throttling errors and let Lambda retry.

Answer

Increase the number of shards in the Kinesis stream.

Answer

Use an Amazon SQS queue as a buffer between Kinesis and Lambda.

Question 4

A company needs to perform complex transformations on large datasets stored in Amazon S3 using Apache Spark. They want to minimize operational overhead. Which AWS service should they use?

Accepted Answer

Amazon EMR. Amazon EMR is the correct choice because it is a managed big data platform that natively runs Apache Spark, allowing you to perform complex transformations on large datasets stored in Amazon S3 without provisioning or managing underlying infrastructure. EMR automatically handles cluster lifecycle, scaling, and tuning, minimizing operational overhead while providing full Spark compatibility.

Answer

Amazon EC2 with manually configured Spark

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Amazon Athena

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AWS Glue

Question 5

A company is migrating its on-premises Hadoop cluster to AWS. They have a large amount of historical data stored in HDFS. Which approach is the most efficient for transferring this data to Amazon S3?

Accepted Answer

Use AWS Snowball Edge devices.. AWS Snowball Edge is ideal for large data transfers when network bandwidth is limited. AWS DataSync is for network transfers, but slower for huge datasets. S3 Transfer Acceleration improves speed but still network. Direct Connect is network-based.

Answer

Use AWS Direct Connect.

Answer

Use AWS DataSync over the internet.

Answer

Use S3 Transfer Acceleration.

Question 6

A data engineer needs to automate the transformation of CSV files to Parquet format as soon as they are uploaded to an S3 bucket. The transformed files should be stored in another S3 bucket. Which solution is the most cost-effective and requires the least maintenance?

Accepted Answer

Configure an S3 event notification to invoke a Lambda function.. AWS Lambda, triggered by S3 event notifications, provides a serverless, event-driven architecture that automatically converts CSV to Parquet upon file upload. This approach is cost-effective because you pay only for compute time during execution, and it requires minimal maintenance as AWS manages the infrastructure, scaling, and fault tolerance.

Answer

Configure an S3 event notification to invoke an AWS Glue job.

Answer

Run an Amazon EMR cluster continuously to watch for new files.

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Set up an EC2 instance with a cron job to poll the S3 bucket.

Question 7

A company uses Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. They notice that the data is delivered in 5-minute intervals even though they set the buffer interval to 60 seconds. What could be the cause?

Accepted Answer

The buffer size is set to a value larger than the incoming data rate.. B is correct because Kinesis Data Firehose delivers data based on whichever condition is met first: the buffer interval (60 seconds) or the buffer size (e.g., 5 MB). If the incoming data rate is very low, the buffer size threshold may never be reached within 60 seconds, causing Firehose to wait longer—up to the maximum buffer interval of 900 seconds—before delivering. In this case, the data rate is so low that it takes 5 minutes to fill the buffer, overriding the 60-second interval setting.

Answer

The source Kinesis stream has insufficient shards.

Answer

The S3 bucket is in a different region.

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The IAM role does not have permission to write to S3.

Question 8

A company needs to process sensitive data from multiple sources. They want to use AWS Glue to catalog and transform the data. Which feature should they use to ensure that sensitive columns are masked before the data is available for querying?

Accepted Answer

AWS Glue DataBrew. Glue DataBrew provides data masking and cleansing capabilities. Glue Studio is for building ETL jobs, but masking requires custom code. Lake Formation is for fine-grained access control, not masking. Macie is for discovering sensitive data, not masking.

Answer

AWS Glue Studio

Answer

AWS Lake Formation

Answer

Amazon Macie

Question 9

A company runs a critical ETL job using AWS Glue that writes to an Amazon Redshift cluster. The job occasionally fails due to insufficient disk space on the Redshift cluster. How can the company automate the process to prevent this failure?

Accepted Answer

Use a CloudWatch alarm to trigger a Lambda function that resizes the cluster.. Using Amazon CloudWatch to monitor disk space and automatically resize the cluster is the best automated solution. Reserving nodes does not address space. Using RA3 nodes with managed storage is a good proactive step but does not automate resizing. The correct answer is to monitor and auto-resize.

Answer

Use RA3 node types with managed storage.

Answer

Increase the number of slices in the Redshift cluster.

Answer

Reserve additional nodes for the Redshift cluster.

Question 10

Which TWO AWS services are suitable for real-time stream processing?

Accepted Answer

Amazon Kinesis Data Analytics. Amazon Kinesis Data Analytics and AWS Lambda can process streams in real-time. AWS Glue is batch-oriented, Amazon EMR can process streams but is more batch, and Amazon Athena is for ad-hoc SQL queries on S3.

Answer

Amazon Athena

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AWS Glue

Answer

Amazon EMR

Question 11

Which TWO data formats are columnar and optimized for analytics queries in Amazon S3?

Accepted Answer

ORC. ORC (Optimized Row Columnar) is a columnar storage format that stores data in a column-oriented manner, enabling efficient compression and predicate pushdown for analytics queries on Amazon S3. It is designed for high-performance read operations in big data frameworks like Apache Hive and Spark, making it ideal for aggregation and filtering workloads.

Answer

CSV

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JSON

Answer

Avro

Question 12

Which THREE considerations are important when designing a data lake on Amazon S3?

Accepted Answer

Setting up S3 Lifecycle policies to transition data to colder storage. S3 Lifecycle policies allow you to automatically transition objects to colder storage classes (e.g., S3 Standard-IA, S3 Glacier) based on age or other rules, reducing storage costs for infrequently accessed data in a data lake. This is a key design consideration for managing data lifecycle and cost efficiency at scale.

Answer

Using Provisioned IOPS for S3

Answer

Using a single Availability Zone for data storage

Question 13

An IAM policy attached to an AWS Glue job allows reading and writing to an S3 bucket and accessing Glue Data Catalog. The job fails with an access denied error when trying to create a table in the Data Catalog. What is the likely issue?

Accepted Answer

The policy does not include the glue:CreateTable action.. The policy allows GetTable and GetDatabase actions, but not CreateTable. The job needs glue:CreateTable permission. The S3 actions are sufficient. The error is specifically about creating a table.

Answer

The Glue Data Catalog is not enabled for the account.

Answer

The job does not have permission to write to the S3 bucket.

Answer

The S3 bucket is encrypted with a KMS key that the job cannot access.

Question 14

A data engineer runs the AWS CLI command shown and notices a zero-byte file in the results. What is the most likely cause of this zero-byte file?

Accepted Answer

The file was created by a failed Spark task that wrote no data.. Zero-byte files often occur when an ETL job fails partway through writing, or when a task starts but writes no data. A completed write would have non-zero size. The other options are less likely: prefix typo wouldn't produce a file; correct permissions wouldn't cause zero bytes; compression would produce some output.

Answer

The S3 bucket has a lifecycle policy that deleted the content.

Answer

The file was written with the wrong prefix.

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The file was compressed, reducing size to zero.

Question 15

A company uses AWS Glue jobs with job bookmarks enabled to process incremental data. They notice that the job processes all data each time instead of only new data. What is the most likely reason?

Accepted Answer

The MaxConcurrentRuns is set to 3, which can cause bookmark conflicts.. Setting MaxConcurrentRuns to a value greater than 1 can cause job bookmark conflicts. When multiple concurrent runs of the same AWS Glue job attempt to update the bookmark state simultaneously, they can overwrite each other's progress, leading to inconsistent bookmark tracking. This results in the job reprocessing all data instead of only incremental data, as the bookmark fails to correctly record the last processed position.

Answer

The TempDir is not configured correctly.

Answer

The job bookmark option is set to 'job-bookmark-enable' but should be 'job-bookmark-disable'.

Answer

The source data does not have a column that can be used as a bookmark key.