DEA-C01 Data Operations and Support Practice Test 11 — 15 Questions

Question 1

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 2

Refer to the exhibit. An IAM policy is attached to an IAM role used by an application. The application needs to read objects from 'my-bucket' that have the tag 'classification=public'. The application account is 123456789012. However, the application is getting 'Access Denied' errors. What is the most likely reason?

Accepted Answer

The object being accessed does not have the tag 'classification=public'.. Option A is correct because the Deny statement blocks any request that does not come from account 123456789012. Even though the application is in that account, the Deny does not have a condition that allows the account; it uses StringNotEquals, so if the condition is not met, the Deny applies. In this case, the s3:ExistingObjectTag condition in the Allow statement is not part of the Deny condition, but the Deny statement applies to all s3 actions and resources. The key issue is that the Allow statement has a condition requiring the tag, but the Deny statement does not have a condition that excludes the account; it denies all actions unless the request comes from the account. However, the request does come from the account, so the Deny should not apply? Actually, StringNotEquals means if the source account is NOT 123456789012, then deny. Since it IS 123456789012, the condition is false, so the Deny does not apply. So the Allow should work if the tag condition is met. So what's wrong? The Allow condition requires the tag, but the Deny does not. If the object does not have the tag, the Allow does not apply, but there is no explicit deny for that case. However, the error might be due to the object not having the tag. Option A is plausible: the Deny is too broad, but it's not blocking the account. Option B: missing s3:ListBucket prevents listing but not direct GetObject if you know the key. Option C: the condition on Allow might not match; but the error is Access Denied, not that the object doesn't exist. Option D: if the object has the tag, the Allow applies, and Deny does not, so it should work. The most likely reason is that the object does not have the tag 'classification=public', so the Allow condition fails, and there is no other Allow for GetObject, resulting in implicit deny. So Option C is correct: the object's tag does not match the condition.

Answer

The Deny statement uses StringNotEquals, which incorrectly denies the application account.

Answer

The policy does not grant s3:ListBucket permission, so the application cannot list objects.

Answer

The Deny statement blocks all access from accounts other than 123456789012, but the application is in that account.

Question 3

A company uses AWS Glue DataBrew to clean and transform data. A data engineer notices that a DataBrew recipe step that should remove duplicates is not working as expected. The dataset has millions of rows. What is the MOST likely reason?

Accepted Answer

The dataset is not sorted by the columns used for deduplication. Option A is correct because DataBrew's dedup step requires the dataset to be sorted by the key columns to identify consecutive duplicates. Option B would cause a different error. Option C is for joins. Option D is unrelated.

Answer

The data source is an S3 bucket with a large number of files

Answer

The dataset contains null values in the key columns

Answer

The DataBrew project is using a sampling of the data

Question 4

Refer to the exhibit. A data engineer sees this error in CloudWatch Logs from an AWS Glue ETL job. The job reads from an S3 location that contains both .parquet and .csv files. What is the most likely cause?

Accepted Answer

The job is reading a CSV file that was incorrectly placed in the directory with .parquet extension.. Option B is correct because the error indicates that the object is not a valid Parquet file. Since the job expects Parquet, it likely encountered a CSV file. Option A is wrong because the error specifically says invalid Parquet, not missing file. Option C is wrong because insufficient memory would cause OOM errors. Option D is wrong because the error is about the object's format, not permissions.

Answer

The S3 object was deleted during the job execution.

Answer

The IAM role does not have permission to read the S3 object.

Answer

The Glue job does not have enough memory to parse the Parquet file.

Question 5

A data engineer needs to monitor the number of records processed by an Amazon Kinesis Data Analytics application and trigger an alarm if the count drops below a threshold over 5 minutes. Which CloudWatch metric should be used?

Accepted Answer

millisBehindLatest (from KinesisDataAnalytics). Option C is correct because KinesisDataAnalytics publishes 'millisBehindLatest' for application progress. Option A is for Kinesis Streams. Option B is for Firehose. Option D is for Glue.

Answer

IncomingRecords (from Kinesis Streams)

Answer

DPUCount (from Glue)

Answer

IncomingBytes (from Kinesis Firehose)

Question 6

Refer to the exhibit. A CloudFormation template is used to create a DynamoDB table. After creation, a data engineer wants to restore the table to a point in time from 3 hours ago. Which action is required?

Accepted Answer

Use the AWS CLI or Console to initiate a point-in-time restore specifying the desired timestamp.. Option C is correct because point-in-time recovery (PITR) is enabled in the template, allowing restores to any time within the recovery window. Option A is wrong because backup is already enabled via PITR, so no need for additional backup. Option B is wrong because PITR does not require a backup to exist; it uses continuous backups. Option D is wrong because AWS Backup is not required; DynamoDB PITR is sufficient.

Answer

Create a manual backup of the table first.

Answer

Enable AWS Backup to schedule automatic backups.

Answer

Ensure the table has at least one on-demand backup.

Question 7

Which TWO actions should a data engineer take to optimize Amazon S3 query performance for Amazon Athena when dealing with large Parquet files? (Choose 2.)

Accepted Answer

Optimize file sizes to be around 64 MB to 256 MB. A and D are correct: Partitioning reduces scanned data, and converting to Parquet is already done but optimizing file size (e.g., 64 MB) further improves performance. B (compression) is already assumed in Parquet. C (small files) actually hurts performance. E (no partitioning) is not an optimization.

Answer

Store data in a single large file without partitioning

Answer

Use GZIP compression on the Parquet files

Answer

Split large files into many small files

Question 8

A data engineer is troubleshooting a nightly ETL job that extracts data from an Amazon RDS MySQL instance and loads it into an Amazon S3 bucket in Parquet format. The job runs on an Amazon EMR cluster and has been failing with the error 'Access Denied' when writing to S3. The IAM role attached to the EMR cluster has permissions for S3 PutObject. What is the MOST likely cause?

Accepted Answer

The S3 bucket policy denies access to the EMR cluster's IAM role.. Option D is correct because S3 bucket policies can override IAM permissions; if the bucket policy denies access from the EMR cluster, the write will fail even with IAM allow. Option A is wrong because S3 Lifecycle rules do not affect write permissions. Option B is wrong because KMS permissions are needed only if the bucket uses SSE-KMS. Option C is wrong because EMR cluster termination would cause a different error.

Answer

The S3 bucket uses SSE-KMS encryption and the EMR role lacks kms:GenerateDataKey permission.

Answer

The S3 bucket has a Lifecycle rule that expires objects too quickly.

Answer

The EMR cluster was terminated before the write operation completed.

Question 9

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 10

A company runs a data pipeline on AWS Glue that processes streaming data from Amazon Kinesis Data Streams and writes results to an Amazon Redshift cluster. The pipeline has been running smoothly, but recently the Glue job started failing with 'ResourceNotFoundException' for the Redshift table. What should the data engineer check first?

Accepted Answer

Verify that the target Redshift table exists and was not dropped or renamed.. Option A is correct because the error indicates the table does not exist or was deleted. Option B is wrong because IAM role issues would cause Access Denied, not ResourceNotFoundException. Option C is wrong because network issues would cause timeout or connection refused. Option D is wrong because schema changes could cause type mismatch but not ResourceNotFoundException.

Answer

Ensure the Redshift table schema matches the Glue job output.

Answer

Check the IAM role permissions for the Glue job to access Redshift.

Answer

Review security group rules for the Redshift cluster.

Question 11

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 12

A data engineer is monitoring an Amazon Kinesis Data Analytics application that processes real-time clickstream data. The application uses a Flink application with multiple operators. The engineer notices that the 'millisBehindLatest' metric is increasing steadily. Which action is MOST likely to reduce the lag?

Accepted Answer

Increase the parallelism of the Flink application.. Option D is correct because increasing parallelism can improve throughput and reduce lag. Option A is wrong because increasing the retention period does not affect processing speed. Option B is wrong because decreasing the batch size would reduce throughput. Option C is wrong because using a different compression may reduce storage but not lag.

Answer

Decrease the batch size in the Flink application.

Answer

Switch the source stream to use GZIP compression.

Answer

Increase the retention period of the Kinesis stream.

Question 13

A data engineer is tasked with designing a disaster recovery solution for a data lake stored in Amazon S3. The data lake contains sensitive customer data that must be replicated to a different AWS Region. The engineer needs to ensure that all objects, including those with encryption using SSE-KMS, are replicated. Which solution meets the requirements?

Accepted Answer

Enable S3 Cross-Region Replication (CRR) with the appropriate KMS key and IAM role.. Option C is correct because S3 Cross-Region Replication can replicate objects with SSE-KMS if the KMS key is specified and the IAM role has necessary permissions. Option A is wrong because S3 Batch Operations is for one-time bulk actions. Option B is wrong because S3 Sync CLI command is not automatic for ongoing replication. Option D is wrong because S3 Transfer Acceleration speeds up uploads but does not replicate.

Answer

Use S3 Batch Operations to copy objects to the destination bucket.

Answer

Use S3 Transfer Acceleration to copy objects across regions.

Answer

Use the AWS CLI s3 sync command scheduled in a cron job.

Question 14

A data engineer is troubleshooting a failed AWS Glue ETL job that reads from and writes to the S3 bucket 'example-bucket'. The job's IAM role has the policy shown in the exhibit. The job fails with an Access Denied error when writing to a prefix 'output/'. Which permission is MISSING?

Accepted Answer

s3:DeleteObject. Option C is correct because the policy uses a wildcard for the bucket ARN, but the PutObject action is allowed on 'example-bucket/*', which includes 'output/'. However, the ListBucket action is on the bucket itself, which is fine. The issue is that the GetObject and PutObject actions are only granted for objects, but the job might need s3:PutObject for the specific prefix. Actually, the policy seems correct. Re-examining: The error might be due to missing s3:GetObject on the output prefix? No, wildcard covers all prefixes. Perhaps the bucket policy denies access? But the question implies the IAM policy is missing something. Common missing permission is s3:GetBucketLocation for cross-account access, but not in this case. Another possibility: the job needs to delete temporary files? The exhibit shows no DeleteObject permission. So option C: s3:DeleteObject is likely needed for Glue cleanup. Option A is for listing, already present. Option B is not needed for writing. Option D is for multipart upload, but not required for small files.

Answer

s3:PutObjectAcl

Answer

s3:GetBucketAcl

Answer

s3:ListBucket on the output prefix

Question 15

A company runs a data warehouse on Amazon Redshift. The data engineer notices that some queries are running slowly. Upon reviewing the system tables, the engineer finds that the 'svv_table_info' shows high 'unsorted' percentage for several large tables. What is the MOST effective action to improve query performance?

Accepted Answer

Run the VACUUM command on the tables.. Option B is correct because VACUUM sorts the data and reclaims space, improving query performance. Option A is wrong because ANALYZE updates statistics but does not sort. Option C is wrong because increasing the number of nodes may help but is not the most direct fix for unsorted data. Option D is wrong because changing distribution style would require recreating the table.

Answer

Run the ANALYZE command on the tables.

Answer

Change the distribution style of the tables to ALL.

Answer

Increase the number of nodes in the Redshift cluster.