DEA-C01 Practice Exam 70 — 20 Questions

Question 1

A company uses Amazon EMR to run Spark jobs on data stored in S3. After upgrading the EMR cluster to a new release, one of the Spark jobs fails with 'OutOfMemoryError' in the executor. Which configuration change is MOST likely to resolve this issue?

Accepted Answer

Increase spark.executor.memory to allocate more memory per executor.. Option D is correct because increasing spark.executor.memory gives more memory per executor. Option A is wrong because increasing driver memory helps the driver, not executors. Option B is wrong because the number of instances doesn't directly fix executor memory. Option C is wrong because reducing partitions may cause data skew and more memory pressure.

Answer

Increase the number of core nodes in the EMR cluster.

Answer

Decrease spark.sql.shuffle.partitions to reduce overhead.

Answer

Increase spark.driver.memory in the Spark configuration.

Question 2

A company uses Amazon Redshift for its data warehouse. During a routine audit, the data engineer discovers that some queries are returning stale data even though the underlying source data has been updated. The engineer confirms that the COPY command completes successfully and that no errors are reported. Which action should the engineer take to ensure queries reflect the latest data?

Accepted Answer

Refresh the materialized views that the queries are using.. Option B is correct because Redshift does not automatically maintain materialized views; they need to be refreshed to reflect changes in the base tables. Option A is wrong because Redshift does not have a cache that needs clearing in this context. Option C is wrong because VACUUM reclaims space and sorts tables, but does not refresh materialized views. Option D is wrong because ANALYZE updates statistics, not the data content.

Answer

Run the VACUUM command on the source tables.

Answer

Clear the Redshift result cache by running RESET ALL.

Answer

Run the ANALYZE command on the source tables.

Question 3

A data engineer notices that an AWS Glue ETL job is failing intermittently with the error 'Connection refused'. The job reads from Amazon RDS for MySQL and writes to Amazon S3. What is the MOST likely cause?

Accepted Answer

The security group for the RDS instance is not allowing inbound traffic from the Glue job's subnet.. Option A is correct because the error indicates a network connectivity issue to the RDS database. Option B is incorrect because the error is not about permissions. Option C is incorrect because the error is about connection, not resource limits. Option D is incorrect because the error is not about job parallelism.

Answer

The RDS instance has reached its maximum number of connections.

Answer

The Glue job is using too many DPUs and hitting resource limits.

Answer

The IAM role associated with the Glue job lacks permissions to write to the S3 bucket.

Question 4

A company runs a nightly AWS Glue ETL job that writes results to an Amazon Redshift table using the JDBC connector. Recently, the job has been failing with the error 'ERROR:  connection to server at ... failed: server closed the connection unexpectedly'. The Redshift cluster is in a private subnet with a VPC endpoint for S3. The Glue job runs in the same VPC with enhanced VPC routing enabled. Which is the most likely cause?

Accepted Answer

The JDBC driver is missing the 'redshift' compatibility mode setting.. Option D is correct because Redshift compatibility mode in the JDBC driver is required for Glue to properly handle connections. Without it, the driver may close the connection unexpectedly. Option A is wrong because Redshift does not enforce SSL by default unless configured. Option B is wrong because the Glue job is in the same VPC and uses enhanced VPC routing, so the connection should work. Option C is wrong because Glue supports Redshift as a data source.

Answer

SSL is not enabled on the Redshift cluster.

Answer

The Glue job's security group does not allow outbound traffic to the Redshift cluster.

Answer

AWS Glue does not support Redshift as a data source.

Question 5

A company is using AWS Glue DataBrew to clean and transform data from an S3 bucket. The data contains personally identifiable information (PII). The company wants to mask the PII columns before making the dataset available to analysts. Which THREE actions can the engineer perform using DataBrew to mask PII? (Choose THREE.)

Accepted Answer

Apply a 'Column masking' transformation to replace values with 'XXX'.. Options A, C, and D are correct. DataBrew provides built-in transformations for masking: 'Column masking' replaces values with a fixed pattern, 'Column hashing' replaces with a hash, and 'Column delete' removes the column. Option B is wrong because 'Column encryption' is not a DataBrew transformation; encryption is typically done at rest or with KMS. Option E is wrong because there is no 'Column tokenization' transformation in DataBrew; tokenization would require a custom recipe step.

Answer

Apply a 'Column tokenization' transformation to replace values with tokens.

Answer

Apply a 'Column encryption' transformation to encrypt the column values.

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 data engineer is monitoring an AWS Glue ETL job that processes data from Amazon DynamoDB to Amazon S3. The job is taking longer than expected. The engineer suspects that the job's parallelism is not optimal. Which THREE actions can improve the job's performance? (Choose THREE.)

Accepted Answer

Enable the 'groupFiles' option in the S3 sink to coalesce small files.. Option A is correct because increasing the number of DynamoDB reads per segment increases parallelism when reading from DynamoDB. Option C is correct because increasing the number of DPUs (data processing units) allocated to the job increases parallelism. Option E is correct because using the 'groupFiles' option can reduce the number of small files written to S3, reducing write overhead. Option B is wrong because decreasing the batch size reduces throughput. Option D is wrong because disabling job bookmark may cause reprocessing but does not improve performance; it may actually degrade it.

Answer

Decrease the 'dynamodb.splits' parameter to reduce the number of parallel readers.

Answer

Disable job bookmark to avoid storing metadata.

Question 8

A data engineer is monitoring an Amazon Kinesis Data Streams application that processes real-time events. The application uses a Kinesis Client Library (KCL) consumer. The engineer notices that the consumer is lagging behind the producer, and the lag is increasing over time. The stream has 10 shards. Which action will MOST effectively reduce the lag?

Accepted Answer

Increase the number of shards in the Kinesis data stream.. Option C is correct because increasing the number of shards increases the stream's capacity and allows more parallel processing. Option A is wrong because reducing the number of records per shard per second would decrease throughput. Option B is wrong because using a single worker per shard is the default; adding more workers per shard is not recommended. Option D is wrong because decreasing the number of shards reduces capacity, worsening lag.

Answer

Use multiple KCL workers per shard to increase processing capacity.

Answer

Decrease the number of records per shard per second.

Answer

Decrease the number of shards in the Kinesis data stream.

Question 9

A data engineer is setting up a data pipeline using Amazon Kinesis Data Firehose to deliver data to Amazon S3. The data must be transformed using an AWS Lambda function before delivery. Which THREE steps are required to configure this?

Accepted Answer

Create an AWS Lambda function that transforms the data.. Options B, C, and D are correct. The Lambda function must be created (B), Firehose must be configured to invoke the Lambda function (C), and the IAM role must allow Firehose to invoke Lambda (D). Option A is wrong because Lambda@Edge is for CloudFront. Option E is wrong because S3 events are not used for Firehose transformation.

Answer

Create a Lambda@Edge function in the same Region.

Answer

Configure an S3 event notification to trigger the Lambda function when new data arrives.

Question 10

A data engineer is using AWS DMS to migrate a 2 TB Oracle database to Amazon Aurora PostgreSQL. The migration is running in full load mode with ongoing replication. After the full load completes, the ongoing replication task shows a 'TargetMetadata' error: 'ERROR:  duplicate key value violates unique constraint'. The engineer verifies that the target table already contains the data. What should the engineer do to resolve this issue?

Accepted Answer

Enable 'BatchApplyEnabled' and set 'TaskRecoveryTableEnabled' to false in the task settings.. Option C is correct because the error indicates that the task is trying to insert rows that already exist. Enabling 'BatchApplyEnabled' and setting 'TaskRecoveryTableEnabled' to false prevents duplicate handling errors during replication. Option A is wrong because truncating would lose data. Option B is wrong because disabling constraints may cause data integrity issues. Option D is wrong because dropping indexes does not prevent duplicate key violations.

Answer

Disable the unique constraint on the target table.

Answer

Truncate the target table and restart the full load.

Answer

Drop the indexes on the target table and recreate them after the migration.

Question 11

A data engineer is troubleshooting an AWS Glue ETL job that fails with an 'Access Denied' error when trying to write to an S3 bucket. The IAM role used by the job has the policy shown in the exhibit. The bucket 'my-bucket' uses S3 default encryption with AWS KMS. What is the most likely missing permission?

Accepted Answer

kms:GenerateDataKey and kms:Decrypt. Option D is correct because when S3 default encryption uses KMS, the IAM role must have kms:GenerateDataKey and kms:Decrypt permissions on the KMS key. The policy in the exhibit does not include any KMS actions. Option A is wrong because s3:PutObject is already granted. Option B is wrong because s3:GetObject is allowed for reading. Option C is wrong because s3:ListBucket is allowed for listing. Option E is wrong because Glue GetObject is not a valid action.

Answer

s3:GetObjectVersion

Answer

glue:GetObject

Answer

s3:ListBucketMultipartUploads

Answer

s3:PutObjectAcl

Question 12

A company runs an Amazon EMR cluster with Spark jobs that process data from Amazon S3. The data engineer receives an alert that one of the Spark jobs failed with an OutOfMemoryError. The job processes large files and uses the default Spark configurations. Which configuration change is MOST likely to resolve the issue?

Accepted Answer

Increase the spark.executor.memory configuration.. Option D is correct because increasing spark.executor.memory gives each executor more memory to handle large data processing. Option A is wrong because reducing the number of cores would reduce parallelism, potentially worsening the problem. Option B is wrong because dynamic allocation is enabled by default and helps, but the issue is executor memory. Option C is wrong because increasing the number of executors without increasing memory per executor does not address the OOM per executor.

Answer

Increase the number of executors.

Answer

Disable dynamic resource allocation.

Answer

Decrease the number of cores per executor.

Question 13

A data engineer needs to set up a data catalog for a new data lake in AWS Glue. The data resides in S3 in Parquet format. The engineer wants to ensure that the schema is automatically detected and updated when new columns are added to the data. Which configuration should the engineer use?

Accepted Answer

Configure the crawler's 'Schema updates' option to 'Update the table schema'.. Option D is correct because Glue crawlers can be configured to update the table schema when new columns are detected. Option A is wrong because partition indexing does not update schema. Option B is wrong because the crawler's output is a table, not a database. Option C is wrong because adding partition indexes does not update schema.

Answer

Add a partition index to the Glue Data Catalog table.

Answer

Set the crawler's 'Database' output to a new database.

Answer

Enable partition indexing on the table.

Question 14

A data engineer is tasked with reducing costs for an Amazon Redshift cluster. The cluster is used for both ETL workloads and BI reporting. The engineer observes that the cluster is over-provisioned during off-peak hours. Which action would be MOST effective in reducing costs while maintaining performance during peak hours?

Accepted Answer

Enable concurrency scaling to automatically add cluster capacity during peak hours.. Option B is correct because concurrency scaling adds additional capacity on demand and is cost-effective for variable workloads. Option A is incorrect because reserved instances require upfront payment and are for steady-state, not variable. Option C is incorrect because reducing node count may impact performance during peak hours. Option D is incorrect because RA3 nodes are for managed storage, not cost reduction for variable workloads.

Answer

Switch to RA3 node types for managed storage.

Answer

Purchase Reserved Instances for the cluster.

Answer

Reduce the number of nodes in the cluster.

Question 15

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 16

A data engineer uses AWS Database Migration Service (DMS) to migrate an on-premises Oracle database to Amazon Aurora MySQL. The migration is successful, but the engineer notices that the target Aurora cluster has a higher CPU utilization than expected during the full load phase. What is the MOST likely cause?

Accepted Answer

The DMS task is configured to use multiple parallel threads to load data, overwhelming the target instance.. Option A is correct because DMS uses multiple tasks in parallel to maximize throughput, which can cause high CPU on the target. Option B is wrong because DMS does not use read replicas during full load. Option C is wrong because LOB settings affect column size handling, not CPU load. Option D is wrong because validation occurs after migration, not during full load.

Answer

The DMS task has LOB mode set to 'Full LOB mode', causing additional processing.

Answer

DMS is performing data validation during the full load phase.

Answer

DMS is reading from an Amazon Aurora read replica instead of the primary instance.

Question 17

A company uses Amazon EMR to run Spark jobs on a transient cluster. The jobs are submitted via a step in the cluster. The cluster is configured to auto-terminate after the last step completes. However, the cluster is not terminating even though the step shows as 'COMPLETED'. What could be the cause?

Accepted Answer

The step's 'ActionOnFailure' parameter is set to 'CONTINUE' and 'KeepClusterAliveOnFailure' is true.. Option B is correct because if KeepClusterAliveOnFailure is set to true for a step, the cluster will not terminate even if the step succeeds. Option A is wrong because 'COMPLETED' indicates success. Option C is wrong because the root volume size does not affect termination. Option D is wrong because cluster is transient, not long-running.

Answer

The cluster's root device size is too large.

Answer

The step failed with an error, but the status shows 'COMPLETED' due to a reporting bug.

Answer

The cluster is configured as a long-running cluster.

Question 18

A data engineer is troubleshooting an access issue. A user has the IAM policy shown in the exhibit. The user attempts to upload an object to `s3://data-lake-bucket/confidential/report.pdf`. What will happen?

Accepted Answer

The upload will fail with an 'Access Denied' error.. Option B is correct because the explicit Deny overrides the Allow, so the upload will be denied. Option A is incorrect because the user has s3:PutObject allowed for the bucket, but the Deny for the confidential path takes precedence. Option C is incorrect because the policy is valid. Option D is incorrect because the Deny is explicit.

Answer

The upload will succeed because the Deny statement is not valid without a condition.

Answer

The upload will succeed because the Allow statement is more specific than the Deny.

Answer

The upload will succeed because the user has s3:PutObject permission on the bucket.

Question 19

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 20

A data engineer needs to move data from an Amazon S3 bucket to an Amazon Redshift cluster on a daily schedule. The data is in CSV format and the target table already exists. Which AWS service should the engineer use to automate this task?

Accepted Answer

AWS Glue. Option B is correct because AWS Glue can be used to run ETL jobs that copy data from S3 to Redshift on a schedule. Option A is wrong because Amazon Athena is a query service, not an ETL scheduler. Option C is wrong because Amazon EMR is a big data platform but requires more setup for simple scheduling. Option D is wrong because Amazon Kinesis Data Analytics is for real-time streaming data.

Answer

Amazon Athena

Answer

Amazon EMR

Answer

Amazon Kinesis Data Analytics