DEA-C01 Data Operations and Support Practice Test 7 — 15 Questions

Question 1

A company uses AWS Lake Formation to manage data lake permissions. A data analyst cannot query a table in Athena, although the table appears in the catalog. The analyst has IAM permissions to run Athena. What is the MOST likely cause?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

The analyst lacks Lake Formation permissions on the table.. Lake Formation permissions are separate from IAM; even if the analyst has IAM permissions to run Athena, they also need specific Lake Formation permissions (e.g., SELECT) on the table to query it. The table appears in the catalog because the analyst has DESCRIBE permission on the database or table, but querying requires additional data access permissions. Option A is incorrect because the table appears in the catalog, so it is registered. Option B is incorrect because the S3 bucket policy might allow access, but Lake Formation can override it. Option D is incorrect because the workgroup output location affects where query results are stored, not the ability to query a specific table.

Answer

The Glue Data Catalog does not have the table registered.

Answer

The S3 bucket policy denies access to the analyst's IAM role.

Answer

The Athena workgroup is not configured with the correct output location.

Question 2

A company is running a critical data pipeline using AWS Glue. The pipeline must be highly available and fault-tolerant. Which TWO strategies should the data engineer implement? (Choose TWO.)

Accepted Answer

Configure the Glue job to run in multiple Availability Zones.. Configuring the Glue job to run in multiple Availability Zones ensures that if one AZ experiences a failure, the job can continue processing in another AZ, providing high availability and fault tolerance. This is a fundamental strategy for resilient data pipeline design in AWS.

Answer

Use a single instance type for all Glue workers.

Answer

Increase the number of concurrent runs for the Glue job.

Answer

Disable job bookmarks to avoid reprocessing.

Question 3

A data pipeline uses AWS Step Functions to orchestrate multiple Lambda functions for data transformation. The pipeline occasionally fails with a 'StateMachineExecutionLimitExceeded' error. What is the MOST likely cause?

Accepted Answer

The account has reached the maximum number of concurrent state machine executions.. Step Functions has a default limit on concurrent executions (e.g., 1 million per account per region). Option A is wrong because Lambda concurrency limits would produce a different error. Option B is wrong because API Gateway is not involved. Option D is wrong because state machine definition does not affect execution limits.

Answer

The API Gateway endpoint used by Step Functions has a rate limit.

Answer

The Lambda functions have reached their concurrent execution limit.

Answer

The state machine definition has a syntax error causing infinite loops.

Question 4

A data engineer is designing an Amazon Redshift data warehouse for a high-traffic analytics workload. The engineer needs to ensure fast query performance and minimize data movement. Which THREE design decisions should be made? (Choose THREE.)

Accepted Answer

Choose DISTSTYLE KEY for tables that are frequently joined.. Correct answers are A, D, and E. DISTSTYLE KEY on frequently joined tables collocates data on the same node, reducing data movement during joins. Applying compression encodings reduces storage and I/O, improving performance. SORT KEYs on columns used in WHERE clauses enable efficient range-restricted scans. Option B is incorrect because the default distribution style (AUTO) may not be optimal; explicit distribution is better for performance. Option C is incorrect because DISTSTYLE ALL stores a copy of the table on every node, which increases storage and load time; it is suitable only for small dimension tables, not large fact tables.

Answer

Use the default distribution style for all tables.

Answer

Use DISTSTYLE ALL for all large fact tables.

Question 5

A data engineer needs to monitor the number of Amazon S3 PUT requests that result in a 403 AccessDenied error. Which AWS service should be used to capture the necessary data?

Accepted Answer

AWS CloudTrail data events. S3 request metrics do not provide filtering by status code; the 4xxErrors metric aggregates all 4xx errors. To monitor specific 403 AccessDenied errors, you should use AWS CloudTrail data events, which capture API call details including error codes. You can create a CloudWatch metric filter on the CloudTrail log group to emit a custom metric for 403 errors, enabling monitoring and alarming.

Answer

Amazon CloudWatch S3 request metrics

Answer

Amazon S3 server access logs

Answer

AWS Config

Question 6

Refer to the exhibit. A data engineer is troubleshooting an IAM policy attached to a user who cannot list objects in the S3 bucket 'example-bucket'. What is the most likely reason?

Accepted Answer

The bucket policy explicitly denies access to the user.. The IAM policy shown in the exhibit grants s3:ListBucket on the bucket and s3:GetObject on objects, which should allow listing. However, if the user still cannot list objects, the most likely reason is that a bucket policy explicitly denies access to that user. Bucket policies are evaluated separately from IAM policies, and an explicit deny in a bucket policy overrides any allow. Options B, C, and D are incorrect because the IAM policy in the exhibit includes the correct resource ARN (arn:aws:s3:::example-bucket for the bucket and arn:aws:s3:::example-bucket/* for objects), includes s3:ListBucket action, and does not require s3:GetObject for listing.

Answer

The resource ARN for the bucket is incorrect; it should be 'arn:aws:s3:::example-bucket/*'.

Answer

The policy includes s3:GetObject but not s3:ListObjects.

Answer

The policy does not include the s3:ListBucket action.

Question 7

Refer to the exhibit. A data engineer runs a Glue ETL job that reads from a CSV file and writes to a Redshift table. The job fails with the error shown. What is the most likely cause?

Accepted Answer

The source CSV file has fewer columns than the target table.. The error indicates a column count mismatch. The source file has 10 columns but the target expects 12. Option B is wrong because the error is about column count, not data type. Option C is wrong because there is no mention of partition count. Option D is wrong because the error is about validation, not permissions.

Answer

The IAM role for the Glue job does not have permission to write to Redshift.

Answer

The target Redshift table has mismatched data types for some columns.

Answer

The Glue job is using an incorrect number of partitions for the source data.

Question 8

Refer to the exhibit. A data engineer is configuring an AWS Lambda function to process records from a Kinesis stream. The function is set up with an event source mapping, but no records are being processed. The Lambda function's IAM role has the policy shown. What is the most likely reason for the issue?

Accepted Answer

The IAM policy does not include all the necessary Kinesis actions for the event source mapping to work.. The IAM policy attached to the Lambda function's execution role is missing key Kinesis actions required for the event source mapping to operate. Specifically, while the policy includes kinesis:DescribeStream and kinesis:GetRecords, it lacks kinesis:GetShardIterator and kinesis:ListShards. These actions are necessary for the Lambda service to poll the stream, retrieve shard iterators, and process records. Without them, the event source mapping cannot read from the Kinesis stream, resulting in no records being processed. Therefore, option B is correct: the policy does not include all necessary Kinesis actions.

Answer

The policy does not grant permission to describe the Kinesis stream.

Answer

The policy includes too many actions, which causes a conflict.

Answer

The resource ARN for the Lambda function in the policy is incorrect.

Question 9

A data engineer is troubleshooting an AWS Glue ETL job that fails with a memory error when processing a large dataset. Which approach can help reduce memory usage?

Accepted Answer

Increase the number of workers for the job. Increasing the number of workers distributes the workload across more resources, reducing memory pressure per worker. Option A is incorrect because using only one worker reduces parallelism and increases memory consumption per worker, worsening the issue. Option B is incorrect because reducing partitions increases the size of each partition, leading to higher memory usage per task. Option D is incorrect because although increasing the worker type to G.2X provides more memory per worker, it does not increase parallelism and may be less cost-effective than increasing the number of workers.

Answer

Set the job to use only one worker

Answer

Reduce the number of partitions in the data source

Answer

Increase the worker type to G.2X

Question 10

A company runs a data processing pipeline using Amazon EMR with Spark. The pipeline reads from S3, processes data, and writes to S3. Recently, the job started failing with 'S3AccessDeniedException' even though the EMR role has appropriate S3 permissions. Which TWO actions should the data engineer take to resolve this issue? (Choose TWO.)

Accepted Answer

Verify that the EMR service role has the necessary S3 permissions in IAM.. Options B and D are correct. B: The EMR service role (and instance profile) must have an IAM policy granting S3 permissions; verifying these ensures the role has the necessary access. D: S3 bucket policies can include explicit deny statements that override IAM permissions, even if the IAM role allows access; checking the bucket policy can reveal such denies. Option A is wrong because S3 versioning does not affect access permissions. Option C is wrong because disabling S3 Block Public Access is unrelated to IAM-based access from EMR. Option E is wrong because an S3 VPC endpoint is not required if the cluster can access S3 via the internet or a NAT gateway.

Answer

Enable S3 versioning on the bucket to allow multiple access methods.

Answer

Disable S3 Block Public Access settings on the bucket.

Answer

Ensure the EMR cluster is launched in a VPC with an S3 VPC endpoint.

Question 11

A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Lambda function that writes to an S3 bucket. Recently, the Lambda function started timing out. Which step should be taken to resolve this issue?

Accepted Answer

Increase the Lambda function timeout. The Lambda function is timing out, indicating that the current timeout is insufficient for processing the records from Kinesis within the allowed time. Increasing the timeout gives the function more time to complete its work, resolving the timeout issue. Option B is incorrect because setting reserved concurrency to 1 limits the number of concurrent executions but does not increase the time available per invocation. Option C is incorrect because decreasing the batch size reduces the number of records per invocation but does not extend the timeout; it may even increase the number of invocations. Option D is incorrect because increasing the number of shards increases the stream's throughput and may increase the number of concurrent Lambda invocations, but it does not address the root cause of the function timing out.

Answer

Set the Lambda reserved concurrency to 1

Answer

Decrease the batch size in the event source mapping

Answer

Increase the number of shards in the Kinesis stream

Question 12

A data engineer is troubleshooting an AWS Glue job that fails with 'java.lang.OutOfMemoryError: Java heap space'. The job processes a large dataset. Which TWO configuration changes should the engineer consider to resolve this issue? (Choose TWO.)

Accepted Answer

Increase the Spark shuffle partitions configuration (spark.sql.shuffle.partitions).. Options B and D are correct. Increasing Spark shuffle partitions (B) reduces the amount of data shuffled per partition, lowering memory pressure and preventing heap overflow. Increasing the number of DPUs (D) allocates more memory and compute resources to the Glue job, directly addressing heap space limitations. Option A is incorrect because changing the output format from Parquet to CSV does not reduce memory usage and may increase it due to lack of compression. Option C is incorrect because reducing the number of source partitions can increase partition size, worsening memory issues. Option E is incorrect because disabling job bookmarks does not affect memory usage; it may cause processing of already processed data but doesn't resolve heap space.

Answer

Change the output format from Parquet to CSV.

Answer

Reduce the number of partitions in the source data.

Answer

Disable job bookmarks to avoid incremental processing.

Question 13

A data engineer is designing a data pipeline that uses AWS Glue to process data from an RDS MySQL database. The pipeline must capture only incremental changes (inserts and updates) and run every hour. Which approach is most cost-effective and reliable?

Accepted Answer

Use Glue job bookmarks to track and process only new and updated records. AWS Glue job bookmarks track processed data and enable incremental processing by automatically storing state information about previously processed data, so only new and updated records are processed in subsequent runs. This approach is cost-effective because it avoids full table scans and reduces data processing. Option B is not optimal because AWS DMS with CDC adds extra cost and operational overhead for a simple hourly incremental load, and it is not directly integrated with Glue. Option C can work but is less reliable if timestamps are not updated on changes or if there are late-arriving records, and it may require additional indexing. Option D is inefficient because full table scans each hour are costly and slow, especially for large tables.

Answer

Use AWS DMS with change data capture (CDC) to replicate changes to S3

Answer

Add a timestamp column and query rows where timestamp > last run

Answer

Perform a full table scan each hour and compare with previous snapshot

Question 14

A company uses Amazon Kinesis Data Firehose to deliver streaming data to Amazon S3. The delivery stream is failing with 'Insufficient capacity' errors. Which THREE actions should the data engineer take to resolve this issue? (Choose THREE.)

Accepted Answer

Increase the buffer size and buffer interval in the Firehose delivery stream configuration.. Options B, D, and E are correct. B: Increasing buffer size and interval allows Firehose to batch more records before delivery, reducing the rate of PUT requests and alleviating temporary capacity issues. D: Requesting a service quota increase for Kinesis Data Firehose raises the default limits on data delivery throughput, directly addressing insufficient capacity errors caused by throttling. E: Increasing the number of shards in the source Kinesis data stream provides higher write throughput to Firehose, reducing backpressure and 'Insufficient capacity' errors. Option A is incorrect because S3 bucket versioning handles object versioning, not write capacity or Firehose throughput. Option C is incorrect because CloudWatch alarms only monitor and alert, they do not resolve capacity issues.

Answer

Enable S3 bucket versioning to handle concurrent writes.

Answer

Configure a CloudWatch alarm to monitor the error rate.

Question 15

A company runs a Redshift cluster and notices that query performance has degraded over time. The data engineer suspects that table statistics are stale. What should the engineer do to improve query performance?

Accepted Answer

Run the ANALYZE command on the tables. Stale table statistics cause the Redshift query optimizer to generate suboptimal execution plans, leading to degraded query performance. Running the ANALYZE command updates these statistics, allowing the optimizer to make better decisions about join order, distribution, and data scan strategies. This directly addresses the root cause of performance degradation over time.

Answer

Rebuild the tables by using CREATE TABLE AS

Answer

Increase the number of slices in the cluster

Answer

Run the VACUUM command on the tables