DEA-C01 Data Operations and Support Practice Test 19 — 15 Questions

Question 1

A data engineer needs to schedule a daily ETL job that runs on Amazon EMR. The job should be triggered automatically and send an email on failure. Which AWS service should the engineer use to orchestrate the job?

Accepted Answer

AWS Step Functions. Option A is correct because AWS Step Functions can orchestrate EMR steps and integrate with Amazon SNS for notifications. Option B is wrong because Amazon CloudWatch Events can trigger Lambda but not directly orchestrate EMR steps. Option C is wrong because Amazon SQS is a message queue. Option D is wrong because Amazon EventBridge can trigger but not orchestrate complex workflows.

Answer

Amazon EventBridge

Answer

Amazon Simple Queue Service (SQS)

Answer

Amazon CloudWatch Events

Question 2

A company is using Amazon Redshift for its data warehouse. A data engineer notices that COPY commands from S3 are failing intermittently with 'S3ServiceException: Access Denied'. The IAM role used by Redshift has the correct permissions. What is the MOST likely cause?

Accepted Answer

The S3 bucket policy denies access to the Redshift cluster's IP addresses.. Option D is correct because S3 bucket policies may deny access even if the role allows it. Option A is wrong because the role is already attached. Option B is wrong because encryption would cause different errors. Option C is wrong because if the role exists, it should work; the issue is likely external.

Answer

The IAM role is not attached to the Redshift cluster.

Answer

The S3 bucket uses SSE-KMS encryption and the role lacks kms:Decrypt.

Answer

The IAM role name contains a typo in the COPY command.

Question 3

A company runs a data lake on Amazon S3 with AWS Glue for ETL. The data is stored in Parquet format and partitioned by date. The data engineer notices that queries using Amazon Athena are scanning large amounts of data even when filtering on the partition column. Which TWO actions would improve query performance? (Choose TWO)

Accepted Answer

Ensure that the WHERE clause uses the partition column correctly. Option B and D are correct. Partition pruning is most effective when the partition column is used correctly in the WHERE clause, and using columnar formats like Parquet with predicate pushdown reduces data scanned. Option A is wrong because adding more partitions may not help if the filter is not applied. Option C is wrong because converting to CSV would increase data scanned. Option E is wrong because using a different file format may not help if partitioning is not leveraged.

Answer

Use a different file format like Avro

Answer

Convert the data from Parquet to CSV for better compression

Answer

Increase the number of partitions by adding a second partition column

Question 4

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 5

A data engineer is designing a disaster recovery plan for an Amazon Redshift data warehouse. The cluster is in us-east-1 and must be recoverable in us-west-2 with minimal data loss. Which THREE actions should the engineer take? (Choose THREE)

Accepted Answer

Create manual snapshots and copy them to us-west-2. Options A, C, and E are correct. Cross-region snapshot copy allows recovery in another region. Automated snapshots enable point-in-time recovery. Using a multi-AZ deployment provides high availability within a region but not cross-region. Concurrent scaling does not help disaster recovery. Manual backups are not automated.

Answer

Deploy Redshift in a multi-AZ configuration

Answer

Enable Redshift concurrent scaling

Question 6

A data engineer needs to set up a disaster recovery solution for an Amazon RDS for MySQL database. The database must be available in another AWS Region with minimal data loss. What is the simplest approach?

Accepted Answer

Create a cross-Region read replica of the database.. Option B is correct because a cross-Region read replica provides asynchronous replication and can be promoted in a disaster. Option A is wrong because Multi-AZ is within a region. Option C is wrong because a manual export/import is not real-time. Option D is wrong because DMS requires ongoing replication setup and is more complex.

Answer

Enable Multi-AZ deployment in the same Region.

Answer

Set up AWS Database Migration Service (DMS) for continuous replication.

Answer

Take a manual snapshot and copy it to the other Region daily.

Question 7

A company uses Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The data must be transformed in real-time using a custom Lambda function. Which TWO steps are required to enable this? (Choose TWO)

Accepted Answer

Configure Kinesis Data Firehose to use a Lambda function for data transformation. Options A and D are correct. Kinesis Data Firehose can invoke a Lambda function for transformation. The Lambda function must return the transformed records to Firehose. Option B is wrong because Kinesis Data Analytics is for analytics, not transformation. Option C is wrong because the transformation is done by Lambda, not within Firehose. Option E is wrong because Kinesis Data Streams is not required for Firehose.

Answer

Create a Kinesis Data Analytics application to transform the data

Answer

Write the transformation logic directly in the Firehose delivery stream configuration

Answer

Use Kinesis Data Streams as the source for Firehose

Question 8

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 9

Refer to the exhibit. An IAM policy is attached to a user who needs to read objects from the 'example-bucket' S3 bucket. The user reports being unable to read any object under the 'confidential/' prefix. What is the reason for this access issue?

Accepted Answer

The explicit deny statement overrides the allow statement. Option B is correct because an explicit deny overrides any allow, even if the allow is more general. The policy allows all GetObject but denies GetObject for the confidential prefix. Option A is wrong because the order of statements does not matter; explicit deny always wins. Option C is wrong because there is no explicit allow for confidential; the deny applies. Option D is wrong because the resource ARN is correct.

Answer

The allow statement is evaluated before the deny statement

Answer

The deny statement is missing an explicit allow for the confidential prefix

Answer

The resource ARN in the deny statement is incorrect

Question 10

A data engineer is troubleshooting an AWS Glue ETL job that suddenly started failing with 'An error occurred while calling o103.pyWriteDynamicFrame. Unknown error'. The job writes data to an Amazon Redshift table. Which step should the engineer take FIRST?

Accepted Answer

Review the job's CloudWatch Logs for detailed error messages.. Option A is correct because the error is generic; checking CloudWatch Logs provides more details. Option B is wrong because it assumes a JDBC driver issue without evidence. Option C is wrong because testing a small dataset may not reproduce the issue. Option D is wrong because the error is not specific to table structure.

Answer

Recreate the Redshift table with a different distribution style.

Answer

Test the job with a small sample dataset to isolate the issue.

Answer

Update the Redshift JDBC driver version in the Glue job.

Question 11

Refer to the exhibit. A company has an S3 bucket 'my-data-lake' with the lifecycle policy shown. Objects under the 'logs/' prefix are being moved to GLACIER after 30 days and expire after 365 days. A data engineer notices that objects older than 365 days are still present in the bucket and are not being deleted. What is the most likely cause?

Accepted Answer

Lifecycle expiration does not apply to objects in GLACIER storage class. Option C is correct because objects in GLACIER storage class can only be expired if they are restored first, or the expiration action must be applied to the current version. The policy does not specify a filter for current version, and GLACIER objects are not deletable by lifecycle without restoration. Option A is wrong because 365 days have passed. Option B is wrong because the prefix is correct. Option D is wrong because the rule is enabled.

Answer

The rule status is disabled

Answer

The prefix filter does not match the objects

Answer

The expiration days count from the transition date, not the object creation date

Question 12

A data engineer needs to monitor the number of records processed by an AWS Glue ETL job and send an alert if the count drops below a threshold. Which AWS service should be used to create this custom metric?

Accepted Answer

Amazon CloudWatch. Amazon CloudWatch is the correct service for creating custom metrics because it allows you to publish your own data points, such as the number of records processed by an AWS Glue ETL job. You can use the CloudWatch PutMetricData API or the AWS Glue job script to emit a custom metric, then set an alarm on that metric to trigger an alert when the count drops below a threshold.

Answer

Amazon S3

Answer

AWS Config

Answer

AWS CloudTrail

Question 13

Refer to the exhibit. A data engineer runs two queries on an Athena table partitioned by 'ds'. Both queries scan the same amount of data. What does this indicate?

Accepted Answer

The partition column is not being used as a filter. Option D is correct because if the partition filter is not pushed down, Athena scans all partitions. Option A is wrong because the data is partitioned. Option B is wrong because partition pruning should reduce data scanned. Option C is wrong because the table is partitioned.

Answer

The table does not have any partitions defined

Answer

The table is not partitioned

Answer

Partition pruning is working correctly

Question 14

A company's Amazon Redshift cluster is running slowly. The data engineer suspects that table design is the cause. Which TWO design practices can improve query performance? (Choose TWO.)

Accepted Answer

Define appropriate sort keys on frequently filtered columns.. Options A and B are correct. Sort keys help the query optimizer prune blocks, and distribution keys reduce data movement. Option C is wrong because VARCHAR is variable-length and may not improve performance. Option D is wrong because GROUP BY is not a design practice. Option E is wrong because adding more slices (via cluster resize) is not a table design change.

Answer

Use GROUP BY instead of DISTINCT in queries.

Answer

Increase the number of slices per node by resizing the cluster.

Answer

Use VARCHAR instead of CHAR for fixed-length strings.

Question 15

A data engineer is troubleshooting an AWS Glue ETL job that fails intermittently with the error 'Rate exceeded.' The job reads from an Amazon RDS for MySQL source and writes to Amazon S3. What is the MOST likely cause of this error?

Accepted Answer

The number of Glue job workers or parallel queries is exceeding the maximum connections or IOPS of the RDS instance.. Option D is correct because the 'Rate exceeded' error in AWS Glue when reading from RDS typically indicates that the number of connections or queries per second exceeds the RDS instance's maximum limits. Option A is wrong because AWS Glue does not directly use Amazon Kinesis. Option B is wrong because insufficient IAM permissions would cause an access denied error, not rate exceeded. Option C is wrong because Amazon S3 does not have a rate exceeded error for writes; it would be a 503 SlowDown error.

Answer

The Glue job is using Amazon Kinesis Data Streams as a source, which has a shard throughput limit.

Answer

The Amazon S3 bucket has a bucket policy that limits the number of objects written per second.

Answer

The IAM role attached to the Glue job does not have sufficient permissions to read from RDS.