DEA-C01 Practice Test 8 — 10 Questions

Question 1

A company stores sensitive data in Amazon S3. To meet compliance requirements, they need to ensure that any data older than 1 year is automatically moved to a lower-cost storage class. Which S3 feature should they use?

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

Accepted Answer

S3 Lifecycle policies. S3 Lifecycle policies allow you to define rules to automatically transition objects between storage classes based on age. Option B is correct. Option A is incorrect because S3 Replication is used to replicate objects across buckets, not to transition storage classes. Option C is incorrect because S3 Glacier is a storage class, not a feature that automates transitions. Option D is incorrect because S3 Intelligent-Tiering automatically moves data between access tiers based on usage, not on a fixed age threshold like 1 year.

Answer

S3 Replication

Answer

S3 Glacier

Answer

S3 Intelligent-Tiering

Question 2

A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data. A Lambda function processes each record. Recently, the Lambda function has been failing with 'ProvisionedThroughputExceededException' when writing results to a DynamoDB table. The data engineer has already increased the DynamoDB write capacity. What else can the engineer do to resolve the issue?

Accepted Answer

Increase the number of shards in the Kinesis stream.. Increasing the number of shards in the Kinesis stream increases the number of concurrent Lambda invocations, distributing the write load across more Lambda functions and reducing the number of writes per second to DynamoDB from each invocation. This helps mitigate ProvisionedThroughputExceededException. Option A is incorrect: increasing Lambda memory does not directly affect DynamoDB write throttling. Option B is incorrect: increasing DynamoDB read capacity does not help with write throttling. Option C is incorrect: decreasing the batch size to 1 reduces the number of records per invocation, but since each shard still invokes Lambda, it may increase the number of invocations and potentially increase the write frequency, worsening the throttling.

Answer

Increase the Lambda function memory.

Answer

Increase the DynamoDB read capacity units.

Answer

Decrease the Lambda batch size to 1.

Question 3

A data engineer uses Amazon EMR to run a Spark job that reads from S3 and writes to HDFS on the cluster. The job fails with an 'OutOfMemoryError: Java heap space' error in the executors. Which parameter adjustment should be made to resolve this?

Accepted Answer

Increase spark.executor.memory. The 'OutOfMemoryError: Java heap space' in executors indicates that the executor memory is insufficient for the data being processed. Increasing spark.executor.memory allocates more heap space to each executor, directly addressing the issue. Option A (spark.default.parallelism) controls the number of tasks, not memory. Option B (spark.sql.shuffle.partitions) affects shuffle partitions but does not increase memory. Option D (spark.driver.memory) is for the driver, not executors.

Answer

Increase spark.default.parallelism

Answer

Increase spark.sql.shuffle.partitions

Answer

Increase spark.driver.memory

Question 4

A company is using Amazon Redshift for analytics. The cluster has 20 nodes and the data is evenly distributed. Query performance has degraded over time. The data engineer suspects that table maintenance is needed. Which set of operations should be performed to improve query performance?

Accepted Answer

Run VACUUM and ANALYZE commands on all tables. Over time, Amazon Redshift tables accumulate deleted rows and unsorted data due to UPDATE and DELETE operations, which degrades query performance. Running VACUUM reclaims space and re-sorts data according to the table's sort key, while ANALYZE updates table statistics used by the query optimizer. Together, these operations restore data layout and enable efficient query planning, directly addressing the performance degradation.

Answer

Run VACUUM FULL on all tables

Answer

Run REINDEX on all tables

Answer

Run ALTER TABLE APPEND to reorganize data

Question 5

A data engineer is troubleshooting a failed AWS Glue ETL job that reads from an S3 bucket. The job logs show the following error: 'java.lang.RuntimeException: java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3a.S3AFileSystem not found'. Which TWO actions will resolve this issue?

Accepted Answer

Include the hadoop-aws jar as an extra jar in the Glue job configuration.. The error 'ClassNotFoundException: Class org.apache.hadoop.fs.s3a.S3AFileSystem' indicates the S3A filesystem library is missing from the classpath. Option B resolves this by adding the hadoop-aws jar as an extra jar, which provides the S3AFileSystem class. Option D resolves it by using a Glue version (3.0 or later) that includes the S3A library by default. Option A (VPC endpoint) addresses networking, not classpath. Option C (IAM role) addresses permissions, not missing classes. Option E (EMRFS) is for Amazon EMR, not AWS Glue.

Answer

Enable VPC S3 endpoint for the Glue job.

Answer

Update the IAM role to allow access to S3.

Answer

Change the S3 access mode from S3A to EMRFS.

Question 6

A company uses Amazon Kinesis Data Streams to ingest clickstream data. The data is consumed by a custom consumer application that writes to Amazon S3 every 5 minutes. The consumer is falling behind and processing lag is increasing. Which action is MOST effective to reduce the lag?

Accepted Answer

Increase the number of shards in the Kinesis stream. The consumer is falling behind because the stream's throughput capacity is insufficient for the incoming data volume. Increasing the number of shards in the Kinesis stream directly increases the total read capacity (each shard provides 2 MB/s read throughput and 5 transactions/second), allowing the consumer to process more data in parallel and reduce lag.

Answer

Switch to Amazon Kinesis Data Firehose to deliver data directly to S3

Answer

Increase the batch size of records written to S3

Answer

Reduce the retention period of the stream

Question 7

A company runs an Amazon RDS for PostgreSQL database. To meet disaster recovery requirements, they set up a cross-Region read replica. The replica has been lagging by several minutes. Which action is MOST effective to reduce the replica lag?

Accepted Answer

Increase the instance size (memory and CPU) of the replica.. Increasing the instance size (memory and CPU) of the cross-Region read replica is the most effective action because replica lag in Amazon RDS for PostgreSQL is often caused by the replica being unable to keep up with the volume of write-ahead log (WAL) data arriving from the primary. A larger replica instance provides more compute and memory resources to apply WAL changes faster, reducing the replay lag. This directly addresses the bottleneck at the replica side without impacting the primary database.

Answer

Enable Multi-AZ on the primary database.

Answer

Increase the instance size of the primary database.

Answer

Decrease the instance size of the replica to reduce cost.

Question 8

A company uses AWS Lake Formation to manage access to data in S3. A data analyst reports being unable to query a table in Amazon Athena, receiving an 'Access Denied' error. The analyst has SELECT permission on the table in Lake Formation. What additional configuration is MOST likely causing the issue?

Accepted Answer

The IAM role used by Athena does not have S3 GetObject permission on the underlying data. In AWS Lake Formation, even when a user has SELECT permission on a table, the IAM role that Athena uses must have S3 GetObject permission on the underlying data files. Lake Formation manages permissions at the metadata level, but the actual data access is enforced by S3 bucket policies and IAM. Without GetObject permission, Athena fails with 'Access Denied'. Option A is incorrect because Athena typically has access to the Glue Data Catalog if the table is visible; the error is about data access. Option C is incorrect because SELECT permission usually includes DESCRIBE, and the error message is about access denied, not missing describe. Option D is incorrect because the table is registered with Lake Formation since the analyst has SELECT permission.

Answer

Athena does not have permission to access the Glue Data Catalog

Answer

The analyst does not have DESCRIBE permission

Answer

The table is not registered with Lake Formation

Question 9

A company stores sensitive user data in an Amazon RDS for PostgreSQL DB instance. A security audit requires that all data be encrypted at rest. The database is currently unencrypted. What is the MOST operationally efficient way to enable encryption at rest?

Accepted Answer

Take a snapshot of the DB instance, copy it with encryption enabled, and restore the snapshot to a new DB instance.. RDS for PostgreSQL does not support enabling encryption at rest on an existing unencrypted DB instance directly. The only way to achieve this is by taking a snapshot of the unencrypted instance, creating an encrypted copy of that snapshot, and then restoring it to a new encrypted DB instance. This method is operationally efficient as it uses native RDS snapshot copy and restore capabilities without requiring additional infrastructure or manual data migration.

Answer

Create a read replica with encryption enabled and promote it.

Answer

Modify the DB instance and enable encryption in the console.

Answer

Modify the DB parameter group to include encryption parameters and reboot the instance.

Question 10

Which THREE are valid considerations when troubleshooting data loss in an AWS Glue ETL job? (Choose three.)

Accepted Answer

Job bookmarks may be skipping new data if not configured properly.. Options A, D, and E are correct. Job bookmarks may skip new data if not configured properly (A). Dynamic frame transformations can drop rows if errors occur during processing (D). Incorrect mapping of source columns to target columns can cause data loss (E). Option B is incorrect because disabling server-side encryption on S3 does not cause data loss; it affects data at rest encryption but not data integrity during ETL. Option C is incorrect because setting the job timeout too low may cause the job to fail prematurely, but it does not directly cause data loss; data can be reprocessed after adjusting the timeout.

Answer

Server-side encryption is disabled on the S3 bucket.

Answer

The job timeout is set too low.