DEA-C01 Data Ingestion and Transformation Practice Test 31 — 15 Questions

Question 1

A company needs to transfer 20 TB of historical data from an on-premises Hadoop cluster to Amazon S3. The network bandwidth is limited and the transfer must complete within one week. Which service should the company use?

Accepted Answer

AWS Snowball Edge. Option C is correct because AWS Snowball is designed for large-scale data transfers with limited bandwidth. Option A is wrong because DataSync over the internet may not meet the deadline. Option B is wrong because the bandwidth is insufficient. Option D is wrong because S3 Transfer Acceleration speeds up uploads but still uses the internet.

Answer

Amazon S3 Transfer Acceleration

Answer

AWS Direct Connect with DataSync

Answer

AWS DataSync over a VPN connection

Question 2

Which TWO AWS services can be used to ingest streaming data into Amazon S3 with minimal code? (Choose two.)

Accepted Answer

Amazon Kinesis Data Firehose. Option A (Kinesis Data Firehose) and Option D (Amazon MSK with S3 connector) are correct. Option B (Lambda) requires code. Option C (DMS) is for databases. Option E (DataSync) is for batch file transfers.

Answer

AWS Lambda

Answer

AWS Database Migration Service (DMS)

Answer

AWS DataSync

Question 3

Which THREE factors should a data engineer consider when choosing between AWS Glue and Amazon EMR for a data transformation job? (Choose three.)

Accepted Answer

The level of control over the execution environment and dependencies. Options A, B, and C are correct. Option D is not a direct factor because both can output to S3. Option E is incorrect because EMR also uses clusters.

Answer

The ability to output results to Amazon S3

Answer

The support for Apache Spark

Question 4

Which TWO actions can improve the performance of an AWS Glue ETL job that processes large datasets in Amazon S3? (Choose two.)

Accepted Answer

Increase the number of DPUs allocated to the job.. Option A (increase DPUs) and Option D (use columnar format) are correct. Option B (use a single file) may reduce parallelism. Option C (increase crawler frequency) does not affect ETL performance. Option E (single availability zone) does not improve performance.

Answer

Increase the frequency of the Glue crawler.

Answer

Use a single Availability Zone for the S3 bucket.

Answer

Use a single large file instead of many small files.

Question 5

Refer to the exhibit. An IAM policy is attached to a role used by an AWS Glue job. The job fails with an 'AccessDenied' error when trying to write to 's3://my-bucket/output/'. What is the most likely cause?

Accepted Answer

The policy does not grant s3:ListBucket permission.. Option B is correct because the policy only allows s3:PutObject on objects inside the bucket, but not on the bucket itself. The error may be due to missing s3:ListBucket permission for the bucket. Option A is wrong because actions include s3:PutObject. Option C is wrong because glue actions allow StartJobRun. Option D is wrong because the job itself runs, only output fails.

Answer

The resource ARN for S3 should include the bucket itself.

Answer

The glue:StartJobRun action is not allowed.

Answer

The s3:GetObject action is missing.

Question 6

Refer to the exhibit. A data engineer runs this AWS CLI command to create a Glue job. The job processes JSON files in an S3 bucket and writes Parquet files to another bucket. After the first successful run, the job re-processes all input files instead of only new files. What is the most likely cause?

Accepted Answer

The job script does not implement job bookmark support.. Option A is correct because the command sets 'job-bookmark-enable', but if the script does not use bookmark APIs, bookmarks won't work. Option B is wrong because max-retries is 0 but that doesn't cause reprocessing. Option C is wrong because the script location is valid. Option D is wrong because the role is specified.

Answer

The ScriptLocation points to an incorrect S3 path.

Answer

The --max-retries parameter is set to 0.

Answer

The IAM role lacks permissions to read bookmark state.

Question 7

Refer to the exhibit. A data engineer runs this CLI command on an S3 bucket. The data is ingested from multiple sources. Which AWS service would be best to process these files in a single batch transformation?

Accepted Answer

AWS Glue. Option C is correct because AWS Glue can process multiple files of varying sizes in a batch ETL job. Option A is wrong because Athena is for ad-hoc queries, not transformations. Option B is wrong because Kinesis is for streaming. Option D is wrong because Lambda has limits on execution time and memory for large files.

Answer

AWS Lambda

Answer

Amazon Kinesis Data Analytics

Answer

Amazon Athena

Question 8

A data engineer needs to ingest streaming data from thousands of IoT devices and immediately process each record with minimal latency. Which AWS service should be used as the ingestion point?

Accepted Answer

Amazon Kinesis Data Streams. Amazon Kinesis Data Streams is designed for real-time streaming data ingestion with low latency. AWS Glue is for batch ETL, S3 is object storage, and Lambda is compute but not an ingestion endpoint itself.

Answer

AWS Lambda

Answer

Amazon S3

Answer

AWS Glue

Question 9

A company wants to schedule a nightly batch job to copy data from an on-premises PostgreSQL database to Amazon S3. The solution must minimize operational overhead. Which AWS service should be used?

Accepted Answer

AWS Glue. AWS Glue can connect to JDBC sources like PostgreSQL using a crawler or ETL job, and write to S3. Data Pipeline and DMS are more complex or intended for replication, not simple scheduled batch copies.

Answer

AWS Data Pipeline

Answer

Amazon EMR

Answer

AWS Database Migration Service (AWS DMS) with ongoing replication

Question 10

A data engineer needs to transform JSON data from an S3 bucket into Parquet format for efficient querying with Amazon Athena. The transformation must be serverless and event-driven. Which approach meets these requirements?

Accepted Answer

Use S3 event notifications to invoke a Lambda function that runs PySpark to convert the data.. S3 event notifications trigger a Lambda function that uses PySpark to convert JSON to Parquet. Athena is query-only, Glue requires a job trigger, and EMR is not serverless.

Answer

Use AWS Glue with a scheduled crawler to convert the data.

Answer

Use Amazon Athena to convert JSON to Parquet on the fly.

Answer

Use Amazon EMR with a long-running cluster to process S3 data.

Question 11

A company is ingesting streaming data into Kinesis Data Streams. The consumer application experiences high latency due to a single shard bottleneck. What is the most effective way to reduce latency?

Accepted Answer

Increase the number of shards in the data stream.. Increasing the number of shards increases throughput and reduces latency. Waiting for autoscaling is passive, using KCL is for processing, and switching to Firehose changes the architecture.

Answer

Wait for automatic scaling to add shards.

Answer

Use the Kinesis Client Library (KCL) to process records.

Answer

Switch to Amazon Kinesis Data Firehose.

Question 12

A data engineering team uses AWS Glue ETL jobs to process data daily. They notice that job run times are increasing as data volume grows. Which action will most effectively improve performance without changing the code?

Accepted Answer

Increase the number of DPUs for the Glue job.. Increasing the number of DPUs (Data Processing Units) allocated to the job provides more parallelism and memory, speeding up processing without code changes.

Answer

Use a smaller instance type for the Glue job.

Answer

Enable job bookmark to skip previously processed data.

Answer

Split the data into more files in S3.

Question 13

A company uses Amazon Kinesis Data Firehose to deliver data to an S3 bucket. The data must be delivered within 60 seconds of ingestion. Currently, the delivery takes 3 minutes due to large buffer sizes. How should the engineer adjust the Firehose configuration?

Accepted Answer

Decrease the buffer interval to 60 seconds.. Amazon Kinesis Data Firehose delivers data to S3 based on either a buffer size threshold or a buffer interval (in seconds), whichever is reached first. To ensure delivery within 60 seconds, you must decrease the buffer interval to 60 seconds, which forces Firehose to flush data to S3 every 60 seconds regardless of buffer size. The current 3-minute delay is caused by the buffer interval being larger than 60 seconds, so reducing it directly meets the requirement.

Answer

Increase the buffer interval to 120 seconds.

Answer

Increase the buffer size to 128 MB.

Answer

Decrease the buffer size to 1 MB.

Question 14

A company ingests millions of small files (1-10 KB) into Amazon S3 every hour. These files are then processed by AWS Glue ETL jobs. The Glue jobs are slow because of the overhead of reading many small files. Which strategy will most effectively improve Glue job performance?

Accepted Answer

Use a Lambda function to merge small files into larger ones before Glue processes them.. Grouping small files into larger ones (e.g., by merging in a preprocessing step) reduces the number of file read operations and improves Glue's efficiency. Using S3 Select or increasing DPUs helps but doesn't address the root cause.

Answer

Enable Glue job bookmark.

Answer

Increase the number of DPUs for the Glue job.

Answer

Use S3 Select to filter data before Glue reads it.

Question 15

A data pipeline uses Amazon Kinesis Data Streams with enhanced fan-out consumers. The team notices that one consumer falls behind and data accumulates. Which action will help this consumer catch up without affecting other consumers?

Accepted Answer

Register an enhanced fan-out consumer for the slow consumer.. Registering a new enhanced fan-out consumer with its own dedicated read throughput allows it to catch up independently. Increasing shards affects all consumers, and increasing iterator age may help but doesn't increase throughput.

Answer

Increase the retention period of the stream.

Answer

Increase the number of shards in the stream.

Answer

Use a Lambda consumer instead of an enhanced fan-out consumer.