DEA-C01 Practice Exam 64 — 20 Questions

Question 1

A data engineer is troubleshooting an AWS Glue job that reads from an Apache Kafka topic using a Glue connector. The job fails with 'TimeoutException'. The Kafka cluster is in a VPC. Which step should the engineer take FIRST?

Accepted Answer

Check the security group and network ACLs associated with the Glue job's VPC.. Option C is correct because timeout errors often indicate network connectivity issues; verifying the security group and route tables for the Glue job's VPC is the first step. Option A is wrong because the error is not about the connector library. Option B is wrong because the job type does not cause timeouts. Option D is wrong because the error is not about record format.

Answer

Increase the Kafka consumer session timeout.

Answer

Update the Glue connector to the latest version.

Answer

Change the Glue job type from Spark to Python Shell.

Question 2

A company is using AWS Glue to process data stored in Amazon S3. The Glue job runs successfully but takes longer than expected. Which TWO actions can reduce the job runtime?

Accepted Answer

Increase the number of DPUs allocated to the job. Option B is correct because increasing worker capacity speeds up processing. Option D is correct because partitioning data reduces the amount scanned. Option A is wrong because the job type (Spark vs Python) is not specified as the bottleneck. Option C is wrong because reducing worker count would increase runtime. Option E is wrong because disabling job bookmarking might affect incremental processing but not runtime significantly.

Answer

Disable job bookmarking

Answer

Reduce the number of workers

Answer

Change the job type from Spark to Python shell

Question 3

Refer to the exhibit. A data engineer sees this output from the AWS CLI for a failed Glue job. The job uses 10 workers of Standard type. What is the MOST appropriate action to resolve the OutOfMemoryError?

Accepted Answer

Increase MaxCapacity to 20. Option B is correct because increasing the number of workers adds more parallelism but does not increase memory per worker; the error is heap space per worker. Option A is wrong because G.1X has less memory. Option C is correct: increasing MaxCapacity (DPUs) per worker increases memory per worker. Option D is wrong because reducing workers exacerbates the issue.

Answer

Increase NumberOfWorkers to 20

Answer

Reduce NumberOfWorkers to 5

Answer

Change WorkerType to G.1X

Question 4

A company runs an Amazon EMR cluster that processes data from S3 and writes results back to S3. The cluster uses Spot Instances for task nodes. Some tasks are failing due to Spot Instance interruptions. What is the BEST way to handle this without manual intervention?

Accepted Answer

Enable automatic node replacement in the EMR cluster. Option A is correct because EMR's automatic node replacement detects interruptions and launches new instances. Option B is manual. Option C uses on-demand which increases cost. Option D is for checkpointing but doesn't automatically replace instances.

Answer

Manually relaunch the cluster after failures

Answer

Configure the application to checkpoint to S3 every few minutes

Answer

Use only On-Demand instances for task nodes

Question 5

Which THREE considerations are important when designing a data pipeline that uses AWS Glue to process streaming data from Amazon Kinesis Data Streams? (Choose 3.)

Accepted Answer

Set the number of Glue workers to match the number of shards for optimal parallelism. A, B, and D are correct. A: Checkpointing ensures exactly-once processing. B: Multiple workers for parallelism. D: Sufficient shards for throughput. C (batch mode) is not streaming. E (data format) is not Glue-specific for streaming.

Answer

Use batch window to accumulate data before processing

Answer

Convert data to Avro format for better compression

Question 6

A data engineer is monitoring an Amazon Redshift cluster and notices that the 'WLM query wait time' metric is consistently high during peak hours. The cluster uses automatic WLM. The engineer wants to reduce query wait times without changing the cluster size. Which action is MOST effective?

Accepted Answer

Enable concurrency scaling.. Option C is correct because enabling concurrency scaling adds transient cluster capacity to handle bursts. Option A is wrong because short query acceleration helps with short queries, not necessarily wait times. Option B is wrong because manual WLM requires tuning queues. Option D is wrong because increased concurrency without resources may worsen contention.

Answer

Change WLM to manual mode and increase the number of queues.

Answer

Increase the maximum number of queries per queue.

Answer

Enable short query acceleration (SQA).

Question 7

A data engineer is troubleshooting an AWS Glue job that writes data to an S3 bucket. The IAM role attached to the Glue job has the policy shown in the exhibit. The job fails when writing to the 'secrets/' prefix but succeeds when writing to other prefixes. What is the reason for the failure?

Accepted Answer

The Deny statement explicitly denies PutObject to the secrets/ prefix.. Option B is correct because the Deny statement explicitly denies s3:PutObject to the secrets/ prefix, which overrides the Allow. Option A is wrong because the resource is correctly specified for both statements. Option C is wrong because the Deny is explicit. Option D is wrong because the job can write to other prefixes.

Answer

The job does not have permission to write to the bucket at all.

Answer

The resource ARN in the Allow statement does not include the bucket itself.

Answer

The Deny statement is not effective because it is placed after the Allow.

Question 8

A data engineer is troubleshooting an AWS Step Functions workflow that calls a Lambda function to process data. The workflow sometimes fails with a 'StateMachineExecutionLimitExceeded' error. What is the MOST likely cause?

Accepted Answer

Number of concurrent executions exceeds the account limit. Option C is correct because Step Functions has a default execution limit per account; hitting it causes this error. Option A is wrong because Lambda concurrency limits cause throttling errors, not state machine execution limits. Option B is wrong because execution time limits cause 'ExecutionTimedOut' errors. Option D is wrong because the error is specific to state machine executions, not Lambda.

Answer

Execution time exceeds the maximum allowed duration

Answer

Lambda function memory limit exceeded

Answer

Lambda function concurrency limit reached

Question 9

A data engineer needs to export data from an Amazon DynamoDB table to Amazon S3 for archival purposes. The export should be a one-time operation and must not impact the read capacity of the table. Which approach meets these requirements?

Accepted Answer

Use DynamoDB on-demand backup feature to export to S3. Option B is correct because DynamoDB's on-demand backup exports to S3 without consuming read capacity. Option A impacts read capacity. Option C is for Spark jobs. Option D is for real-time streaming.

Answer

Use a Scan operation in a script to read all items and write to S3

Answer

Use AWS Glue ETL with a DynamoDB connector

Answer

Set up a DynamoDB Stream to Lambda that writes to S3

Question 10

A company uses Amazon S3 to store raw data and AWS Lambda to process files as they arrive. The Lambda function sometimes times out when processing large files. The team wants to improve reliability and scalability. Which approach should the team take?

Accepted Answer

Use Amazon S3 event notifications to send events to an Amazon SQS queue, and then have Lambda poll the queue in batches.. Option A is correct because S3 event notifications to SQS decouple the producer and consumer, allowing Lambda to poll at its own pace and process in batches. Option B is wrong because SNS is push-based and can still cause timeouts. Option C is wrong because increasing Lambda timeout is a temporary fix. Option D is wrong because AWS Batch is for long-running batch jobs, not event-driven processing.

Answer

Replace Lambda with AWS Batch and use S3 event notifications to trigger the batch job.

Answer

Use Amazon S3 event notifications to send events to an Amazon SNS topic, which triggers Lambda.

Answer

Increase the Lambda function timeout to 15 minutes and memory to 3 GB.

Question 11

A data engineer runs an AWS Glue ETL job that reads from an S3 bucket containing JSON files. The job fails with an error indicating that some records are malformed. The engineer wants to skip the malformed records and continue processing. Which approach should the engineer take?

Accepted Answer

Configure the Glue DynamicFrame to use the `withErrorThreshold` option to skip corrupt records.. Option C is correct because Glue's DynamicFrame has a `recurse` option in `withErrorThreshold` or can use `from_options` with `multiLine` and `allowQuotedRecordDelimiters`. However, the best approach is to use the `from_catalog` or `from_options` with `withErrorThreshold` to skip bad records. Option A is wrong because modifying the data source is not always possible. Option B is wrong because using a different file format does not fix malformed JSON. Option D is wrong because AWS Glue Schema Registry validates schemas, not malformed records.

Answer

Pre-process the JSON files to correct the malformed records before Glue reads them.

Answer

Convert the JSON files to Parquet format and use Glue to read Parquet.

Answer

Use AWS Glue Schema Registry to reject invalid records.

Question 12

A data engineer is troubleshooting an Amazon Redshift cluster that has experienced a node failure. The engineer needs to ensure that the cluster is highly available and can withstand a single node failure without downtime. Which TWO actions should the engineer take?

Accepted Answer

Enable automated snapshots with cross-region copy.. Options B and D are correct. Enabling multi-node cluster with RA3 node types provides managed storage and resilience. Enabling cross-region snapshot copy ensures data can be restored in another region. Option A is incorrect because concurrency scaling does not provide high availability. Option C is incorrect because single-node clusters are not highly available. Option E is incorrect because VPC routing does not affect node failure.

Answer

Enable concurrency scaling to handle increased read traffic.

Answer

Deploy the cluster as a single-node cluster for simplicity.

Answer

Place the cluster in a public subnet with an internet gateway.

Question 13

A data engineer is designing a data pipeline that ingests JSON files from an S3 bucket, transforms them using AWS Glue, and loads into Amazon Redshift. The data is updated daily, and the pipeline must handle late-arriving data from the previous day. Which approach minimizes reprocessing?

Accepted Answer

Use AWS Glue job bookmarks to process only new files based on S3 event notifications.. Option A is correct because incrementally processing only new files avoids reprocessing. Option B (full reload) is inefficient. Option C (versioning) handles overwrites but not late-arriving data. Option D (Kinesis) is for streaming, not batch with late data.

Answer

Stream data using Amazon Kinesis Data Firehose to Redshift.

Answer

Enable S3 versioning and process only the latest version of each object.

Answer

Schedule a full reload of all data from S3 to Redshift each day.

Question 14

A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data. The consumer application is falling behind and the iterator age is increasing. Which action would most effectively improve throughput?

Accepted Answer

Increase the number of shards in the stream. Option C is correct because increasing shards increases parallelism. Option A is wrong because it reduces batch size. Option B is wrong because it doesn't help throughput. Option D is wrong because it adds latency.

Answer

Switch from Kinesis Data Streams to Kinesis Data Firehose

Answer

Decrease the batch size in the consumer

Answer

Enable enhanced fan-out for the consumer

Question 15

A data engineer needs to transform a large dataset stored in Amazon S3 using Apache Spark. The engineer wants to minimize startup time and use a serverless approach. Which AWS service should the engineer use?

Accepted Answer

AWS Glue. Option A is correct because AWS Glue provides a serverless Spark environment with fast startup. Option B is wrong because Amazon EMR requires cluster provisioning. Option C is wrong because Amazon Redshift is a data warehouse, not a Spark environment. Option D is wrong because Amazon Athena is for querying, not transforming with Spark.

Answer

Amazon Redshift

Answer

Amazon EMR

Answer

Amazon Athena

Question 16

A data pipeline uses AWS Lambda to process records from an Amazon Kinesis Data Stream. The Lambda function is idempotent and runs once per record. Recently, the function started failing with 'ProvisionedThroughputExceededException' when writing to a DynamoDB table. Which action should the data engineer take to resolve this?

Accepted Answer

Implement retry logic with exponential backoff in the Lambda function.. Option C is correct because implementing exponential backoff with jitter is a best practice to handle throttling. Option A is wrong because increasing Lambda concurrency would increase the write rate, worsening the issue. Option B is wrong because Kinesis shard count does not affect DynamoDB. Option D is wrong because reducing batch size would increase the number of concurrent Lambda invocations.

Answer

Decrease the Lambda function's batch size to process fewer records per invocation.

Answer

Increase the Lambda function's reserved concurrency.

Answer

Increase the number of shards in the Kinesis stream.

Question 17

A company uses AWS Lake Formation to manage access to data in S3. A data analyst reports being unable to query a table in Amazon Athena, receiving an 'Access Denied' error. The analyst has SELECT permission on the table in Lake Formation. What additional configuration is MOST likely causing the issue?

Accepted Answer

The IAM role used by Athena does not have S3 GetObject permission on the underlying data. Option D is correct because Lake Formation enforces access at the S3 level via IAM; if the IAM role lacks S3 permissions, access is denied. Option A is wrong because the table is registered. Option B is wrong because the analyst has SELECT permission. Option C is wrong because Athena permissions are typically granted via Lake Formation.

Answer

Athena does not have permission to access the Glue Data Catalog

Answer

The analyst does not have DESCRIBE permission

Answer

The table is not registered with Lake Formation

Question 18

A data engineer is designing a data pipeline that ingests streaming data from an IoT fleet using Kinesis Data Streams and processes it with a Lambda function. The Lambda function often times out when the data volume spikes. What is the most scalable solution?

Accepted Answer

Increase the number of shards and use a Kinesis Data Analytics application for windowed aggregation before Lambda.. Option D is correct because increasing shard count increases throughput, and using a fan-out pattern with Kinesis Data Analytics involves windowed processing that can handle spikes without Lambda timeouts. Option A is wrong because increasing Lambda timeout may not be enough for large spikes. Option B is wrong because Lambda reserved concurrency limits scaling. Option C is wrong because reducing batch size decreases throughput.

Answer

Reduce the batch size in the event source mapping.

Answer

Increase the Lambda function timeout to 15 minutes.

Answer

Increase the Lambda function memory and set reserved concurrency.

Question 19

Which TWO AWS services can be used to schedule and orchestrate ETL workflows that involve multiple steps and dependencies? (Choose 2.)

Accepted Answer

AWS Step Functions. A and C are correct. A: Step Functions can orchestrate Glue, Lambda, etc. C: Managed Workflows for Apache Airflow (MWAA) is designed for orchestration. B (Data Pipeline) is an older service, but not as common. D (Batch) is for batch computing, not orchestration. E (Lambda) is for individual functions.

Answer

AWS Batch

Answer

AWS Lambda

Answer

AWS Data Pipeline

Question 20

A data engineer sees the CloudWatch log entry in the exhibit for a Lambda function that processes data from an Amazon SQS queue. What is the MOST likely cause of the timeout?

Accepted Answer

The Lambda function's timeout is too short for the processing required.. Option B is correct because the log shows the function used only 64 MB of the allocated 128 MB memory, indicating that memory is not the issue. The function timed out after 30 seconds, and the duration is 30001.23 ms, which is just over the default timeout of 30 seconds. Therefore, increasing the timeout will resolve the issue. Option A is incorrect because memory usage is low. Option C is incorrect because the function is not hitting memory limits. Option D is incorrect because SQS visibility timeout does not affect Lambda execution timeout directly; the Lambda timeout is separate.

Answer

The Lambda function's reserved concurrency is set too low.

Answer

The Lambda function is running out of memory.

Answer

The SQS queue's visibility timeout is set too low.