DEA-C01 Data Operations and Support Practice Test 25 — 15 Questions

Question 1

A data engineer manages an Amazon Redshift cluster that hosts a 10 TB data warehouse. The cluster uses a single node of type dc2.large (160 GB SSD). The engineer notices that the cluster's disk space is 95% full, and queries are running slowly. The engineer runs the STV_PARTITIONS view and sees that many slices have high 'tossed' counts. The engineer also runs VACUUM and ANALYZE commands, but the disk space does not improve. The engineer suspects that the cluster needs more storage. However, the company wants to minimize cost. Which action should the engineer take to resolve the disk space issue most cost-effectively?

Accepted Answer

Replace the cluster with a single ds2.xlarge node.. Option C is correct because dc2.large is a dense compute node with limited SSD storage; upgrading to ds2.xlarge provides more storage (2 TB HDD) at a lower cost per GB compared to scaling up to dc2.8xlarge. Option A is wrong because adding more dc2.large nodes increases storage but also CPU and memory, which may be unnecessary and more expensive than a single ds2 node. Option B is wrong because dc2.8xlarge has 2.56 TB SSD, which is more expensive than ds2.xlarge. Option D is wrong because switching to RA3 nodes is costly and designed for managed storage, which may be overkill.

Answer

Switch to a ra3.xlplus node with managed storage.

Answer

Scale the cluster to a single dc2.8xlarge node.

Answer

Add another dc2.large node to the cluster to increase total storage.

Question 2

A company uses AWS Glue to run ETL jobs that process data from an Amazon RDS for MySQL database and load it into an Amazon S3 data lake. The Glue job runs daily and processes incremental data. Recently, the job has been taking longer than expected. The engineer checks the CloudWatch logs and sees that the job is spending most of its time on the 'Reading from JDBC' phase. The MySQL table has 10 million rows and is indexed on the primary key. The Glue job uses a 'job bookmark' to track processed data. The engineer wants to improve the performance of the read phase. Which action is most likely to help?

Accepted Answer

Modify the job to use a 'query' parameter that selects only the new or modified rows based on a timestamp column.. Option B is correct because using a 'query' parameter with a WHERE clause that filters on the bookmark key (e.g., a timestamp column) allows Glue to read only the incremental data, reducing the amount of data transferred. Option A is wrong because increasing the number of DPUs adds parallelism but the bottleneck may be the database's ability to serve data. Option C is wrong because increasing the fetch size may cause memory issues. Option D is wrong because job bookmark already tracks processed data; disabling it would cause reprocessing.

Answer

Increase the JDBC 'fetchSize' parameter to 10000.

Answer

Disable job bookmark and perform a full refresh each time.

Answer

Increase the number of DPUs for the Glue job.

Question 3

A data engineering team is troubleshooting a failing AWS Glue ETL job that processes data from an S3 bucket. The job writes output to another S3 bucket. The job fails with an AccessDenied error when writing to the output bucket. The IAM role used by the job has the following policy attached: {"Version":"2012-10-17","Statement":[{"Effect":"Allow","Action":["s3:GetObject","s3:ListBucket"],"Resource":["arn:aws:s3:::input-bucket/*","arn:aws:s3:::input-bucket"]}]}. What is the most likely cause of the failure?

Accepted Answer

The IAM role does not have s3:PutObject permission on the output bucket.. Option B is correct because the IAM policy only grants GetObject and ListBucket permissions on the input bucket, but no permissions on the output bucket. Option A is wrong because there is no restriction on data size. Option C is wrong because there is no bucket policy mentioned. Option D is wrong because the role exists.

Answer

The ETL job is processing more than 10 TB of data.

Answer

The output bucket has a bucket policy that denies access to the IAM role.

Answer

The IAM role used by the job does not exist.

Question 4

A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by an AWS Lambda function that processes records and stores results in Amazon DynamoDB. Recently, the Lambda function has been failing with ProvisionedThroughputExceededException errors. Which action should the data engineer take to resolve this issue?

Accepted Answer

Enable auto scaling on the DynamoDB table to handle increased write capacity.. Option A is correct because enabling DynamoDB auto scaling dynamically adjusts throughput to match demand. Option B is wrong because increasing Lambda batch size would increase write requests, worsening the problem. Option C is wrong because Lambda retries are already built-in but would still fail. Option D is wrong because disabling retries would lose data.

Answer

Reduce the number of shards in the Kinesis stream to lower the ingestion rate.

Answer

Increase the batch size in the Lambda event source mapping to process more records per invocation.

Answer

Configure the Lambda function to discard records that cause throttling errors.

Question 5

A data pipeline uses AWS Glue to run ETL jobs that read from and write to an Amazon Redshift cluster. The pipeline recently started failing with the error 'ERROR: cannot execute INSERT in a read-only transaction'. The Glue job's IAM role has the necessary permissions. What could be the cause of this error?

Accepted Answer

The Glue job is using a transaction that was opened in read-only mode.. Option D is correct because Redshift uses a read-only transaction when connected via a read-only workload or if the connection string specifies auto_commit=False and the job tries to write without committing. Option A is wrong because insufficient permissions would cause a different error. Option B is wrong because Redshift is not in read-only mode. Option C is wrong because Glue connections do not have a read-only setting.

Answer

The Redshift cluster is in read-only mode due to maintenance.

Answer

The Glue connection is configured with 'read-only' set to true.

Answer

The Glue job's IAM role does not have sufficient Redshift permissions.

Question 6

A data engineer is troubleshooting an AWS Glue ETL job that fails intermittently. The job is triggered by an AWS Lambda function that uses the IAM policy shown. The Lambda function invokes the Glue job, but sometimes the job does not start. Which action should the engineer take to ensure the job starts reliably?

Accepted Answer

Add the iam:PassRole permission for the IAM role used by the Glue job.. Option C is correct because the policy only allows glue:StartJobRun on any resource (*), but does not allow glue:GetJobRun or glue:GetJob to check job status, which may be needed by the Lambda function to confirm job start. However, the immediate issue is that the policy might be missing glue:StartJobRun on the specific job ARN, but since it's on *, it's allowed. The failure may be due to missing permissions to describe the job or pass role. Option C addresses the need to pass the IAM role to Glue. Option A is wrong because S3 permissions are sufficient. Option B is wrong because batching is not the issue. Option D is wrong because the policy already allows StartJobRun on *.

Answer

Replace the resource "*" in the Glue action with the specific Glue job ARN.

Answer

Add s3:GetObject and s3:PutObject permissions for the Glue job's output bucket.

Answer

Modify the Lambda function to batch multiple job start requests.

Question 7

A company uses Amazon S3 as a data lake. A data engineer needs to ensure that all objects uploaded to the 'incoming' prefix are automatically encrypted at rest using AWS KMS with a specific customer managed key. What is the simplest way to enforce this?

Accepted Answer

Use a bucket policy that denies PutObject requests without the required encryption header.. Option B is correct because S3 bucket policies can enforce encryption using a condition key. Option A is wrong because default encryption does not enforce customer managed keys. Option C is wrong because S3 Inventory does not enforce encryption. Option D is wrong because S3 Transfer Acceleration does not affect encryption.

Answer

Enable S3 Transfer Acceleration to force encryption in transit.

Answer

Configure S3 Inventory to report on encryption status and alert on non-compliance.

Answer

Enable default encryption on the bucket with SSE-S3.

Question 8

A data engineering team uses Amazon EMR to run Spark jobs on a transient cluster. The jobs read data from S3 and write results back to S3. The team notices that jobs are taking longer than expected. Which configuration change is most likely to improve performance?

Accepted Answer

Enable EMRFS consistent view and use S3 as the direct input source.. Option D is correct because EMRFS consistent view is important for eventually consistent S3; lack of consistency can cause retries. Option A is wrong because reducing node count reduces parallelism. Option B is wrong because fewer instances reduce compute capacity. Option C is wrong because HDFS is slower for S3 access.

Answer

Use a larger instance type for the master node.

Answer

Enable HDFS as the intermediate storage and copy data from S3 to HDFS before processing.

Answer

Increase the number of core nodes to improve parallelism.

Question 9

A company uses Amazon Kinesis Data Firehose to deliver streaming log data to an Amazon S3 bucket. The delivery stream uses dynamic partitioning with a custom prefix. Recently, the delivery stream has been failing with the error 'InvalidArgumentException: The number of partitions exceeds the limit'. What is the likely cause?

Accepted Answer

The incoming data contains more distinct partition key values than the allowed limit.. Option C is correct because dynamic partitioning in Firehose has a limit of 20 unique partition values per batch. Option A is wrong because data volume does not cause this error. Option B is wrong because S3 bucket policy would cause different errors. Option D is wrong because buffer size does not affect partition count.

Answer

The S3 bucket has a bucket policy that restricts the number of prefixes.

Answer

The buffer size and interval are set too low, causing many small files.

Answer

The data volume exceeds the maximum throughput of the delivery stream.

Question 10

A data engineer needs to monitor the performance of an Amazon Redshift cluster. Which TWO Amazon CloudWatch metrics should the engineer monitor to detect disk space issues?

Accepted Answer

PercentageDiskSpace. Options A and B are correct. PercentageDiskSpace is direct. ReadIOPS and WriteIOPS indicate I/O but not disk space. NetworkThroughput does not relate to disk. CPUUtilization is compute.

Answer

ReadIOPS

Answer

WriteIOPS

Answer

NetworkThroughput

Answer

CPUUtilization

Question 11

A company is using AWS Glue Data Catalog to store metadata about datasets in S3. The data engineer wants to implement a data governance solution that tracks lineage and versioning of datasets. Which TWO AWS services can be used together to achieve this?

Accepted Answer

AWS Lake Formation. Option A and D are correct. AWS Lake Formation provides data lineage and versioning. AWS Glue Data Catalog stores metadata and can be integrated with Lake Formation. Option B is wrong because S3 does not provide lineage. Option C is wrong because CloudTrail logs API calls but not lineage. Option E is wrong because Data Pipeline is for data movement.

Answer

AWS Data Pipeline

Answer

AWS CloudTrail

Answer

Amazon S3

Question 12

A data engineer is designing a disaster recovery plan for an Amazon RDS for PostgreSQL database. The database is 500 GB and has a multi-AZ deployment. The recovery point objective (RPO) is 5 minutes, and the recovery time objective (RTO) is 2 hours. Which THREE actions should the engineer take to meet these objectives?

Accepted Answer

Enable Multi-AZ deployment for automatic failover.. Option A, B, and D are correct. Automated backups (A) provide point-in-time recovery. Multi-AZ (B) provides automatic failover. Read replica promotion (D) can be faster for cross-region recovery. Option C is wrong because snapshot export to S3 is for archival, not fast recovery. Option E is wrong because deleting logs prevents point-in-time recovery.

Answer

Take daily manual snapshots and export them to Amazon S3.

Answer

Disable automatic backups to reduce storage costs.

Question 13

Your company runs a critical data processing pipeline that ingests data from multiple sources into an Amazon S3 bucket. An AWS Glue ETL job processes this data and writes the output to an Amazon Redshift cluster. The pipeline is triggered by an S3 event notification that invokes an AWS Lambda function, which starts the Glue job. Recently, you have observed that the Glue job occasionally fails with an AccessDenied error when trying to access the S3 bucket. The IAM role used by the Glue job has the following policy: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:GetObject", "s3:ListBucket" ], "Resource": [ "arn:aws:s3:::input-bucket", "arn:aws:s3:::input-bucket/*" ] }, { "Effect": "Allow", "Action": [ "redshift:CopyData" ], "Resource": "*" } ] }. The S3 bucket has a bucket policy that allows access only from a specific VPC. The Glue job runs in a VPC with the appropriate VPC endpoints configured. The error occurs intermittently and sometimes retries succeed. What is the most likely cause and correct course of action?

Accepted Answer

Add a VPC endpoint for S3 and configure the bucket policy to allow access from the Glue job's VPC endpoint.. Option D is correct because the Glue job runs in a VPC, but if the S3 bucket policy requires requests to come from the VPC endpoint, the Glue job's requests must originate from that endpoint. However, Glue jobs running in a VPC do not automatically route S3 traffic through VPC endpoints; they go through the internet unless a VPC endpoint is explicitly used. The intermittent success might be due to other requests coming from the same IP range. The correct action is to ensure the Glue job uses a VPC endpoint for S3. Option A is wrong because the bucket policy is the issue, not the IAM policy. Option B is wrong because the Lambda function is not directly accessing S3. Option C is wrong because the Glue job already runs in the VPC.

Answer

Ensure the Glue job's VPC configuration includes a NAT gateway to route traffic to S3.

Answer

Change the Lambda function to use a different IAM role with broader S3 permissions.

Answer

Modify the Glue job's IAM role to include s3:PutObject permission for the output bucket.

Question 14

Your team uses Amazon Kinesis Data Analytics to process real-time streaming data from an Amazon Kinesis Data Stream. The application calculates windowed aggregations and writes results to an Amazon S3 bucket using a delivery stream. Recently, the application has been failing with a 'LimitExceededException' when writing to the delivery stream. You have checked the CloudWatch metrics and see that the IncomingBytes and IncomingRecords for the delivery stream are well below the provisioned limits. The delivery stream has a buffer size of 5 MB and a buffer interval of 60 seconds. The application generates about 500 records per second, each about 1 KB. What is the most likely cause and correct action?

Accepted Answer

Modify the application to use PutRecordBatch with smaller batch sizes to stay within the 4 MB per-call limit.. Option B is correct because Kinesis Data Analytics writes to Firehose through a PutRecord or PutRecordBatch call. Each call has a maximum payload size of 1 MB (for PutRecord) or 4 MB (for PutRecordBatch). If the application uses PutRecordBatch and the total payload exceeds 4 MB, it gets a LimitExceededException. Increasing the buffer size or interval does not affect the per-call limit. Option A is wrong because the stream is not the source of the error. Option C is wrong because the buffer settings are not causing the per-call limit. Option D is wrong because the data size is small.

Answer

Increase the number of shards in the Kinesis Data Stream to reduce the load on the application.

Answer

Reduce the buffer interval of the delivery stream to 30 seconds to flush data more frequently.

Answer

Increase the buffer size of the delivery stream to 10 MB to accommodate larger writes.

Question 15

Your company has an Amazon S3-based data lake partitioned by year/month/day. An AWS Glue crawler runs daily to update the Data Catalog. A Spark job on Amazon EMR reads the latest partition and performs transformations. Recently, the Spark job has been failing with a 'FileNotFoundException' for a file that is expected to exist. You check the S3 bucket and see that the file exists. The job is configured to use S3 as the direct input source with EMRFS consistent view enabled. The IAM role for the EMR cluster has full S3 access. What is the most likely cause?

Accepted Answer

The EMR cluster is experiencing eventual consistency issues despite EMRFS consistent view.. Option C is correct because even with EMRFS consistent view enabled, there can be a propagation delay between the crawler updating the catalog and the actual S3 objects being visible. The Spark job may be reading stale metadata. Option A is wrong because the crawler updates the catalog, but the job may read from S3 directly. Option B is wrong because the file exists. Option D is wrong because the catalog is updated.

Answer

The Data Catalog partition metadata is out of sync because the crawler runs after the job.

Answer

The Glue crawler did not update the Data Catalog because of insufficient permissions.

Answer

The file was deleted by a lifecycle policy after the job started.