DBS-C01 Practice Test 16 — 15 Questions

Question 1

An application using the above IAM policy is trying to perform a Scan operation on the 'Orders' table. What will happen?

Accepted Answer

The Scan operation will fail because the explicit Deny on dynamodb:Scan overrides the Allow.. Option D is correct because the explicit Deny for dynamodb:Scan overrides any Allow. Option A is wrong because the Deny is explicit and not ambiguous. Option B is wrong because the policy explicitly denies Scan. Option C is wrong because the policy does not allow Scan; the explicit Deny applies.

Answer

The Scan operation will succeed because the Deny is on all resources but the Allow is specific to the table.

Answer

The Scan operation will succeed because the policy allows other operations on the table.

Answer

The Scan operation will fail because the policy does not explicitly allow Scan.

Question 2

A company runs an OLTP workload on an RDS for MySQL instance. The database has a table with 50 million rows. The application frequently runs queries that join this table with a small lookup table (1000 rows) using a foreign key. The queries are slow. Which design change would most improve performance?

Accepted Answer

Add an index on the foreign key column in the large table.. Option D is correct because proper indexing on the join column eliminates full table scans. Option A is wrong because increasing instance size is a vertical scaling approach that may help but is not as effective as indexing. Option B is wrong because read replicas distribute read traffic but do not speed up individual queries. Option C is wrong because partitioning can help with data management but not necessarily join performance.

Answer

Partition the large table by the foreign key column.

Answer

Scale up the RDS instance to a larger size.

Answer

Create a read replica and direct all read queries to it.

Question 3

A startup is building a social media application with a news feed feature. The feed must be personalized and updated in real-time as users post. Which AWS database service is best suited for this workload?

Accepted Answer

Amazon ElastiCache for Redis with sorted sets and pub/sub. Option C is correct because Amazon ElastiCache for Redis supports sorted sets and pub/sub, ideal for real-time feeds. Option A is wrong because DynamoDB is optimized for key-value access, not for real-time feed aggregation across many users. Option B is wrong because RDS is not designed for sub-millisecond real-time updates. Option D is wrong because S3 is object storage, not a database for real-time queries.

Answer

Amazon DynamoDB with Global Secondary Indexes

Answer

Amazon S3 with Select and Glacier

Answer

Amazon RDS for PostgreSQL with read replicas

Question 4

A company needs to store and query graph data (nodes and edges) for a social network. They require low-latency traversals. Which AWS database is best suited?

Accepted Answer

Amazon Neptune. Option B is correct because Neptune is a purpose-built graph database. Option A is wrong because RDS is relational. Option C is wrong because DynamoDB is key-value. Option D is wrong because ElastiCache is in-memory cache, not a graph database.

Answer

Amazon RDS for MySQL

Answer

Amazon ElastiCache for Redis

Answer

Amazon DynamoDB

Question 5

A company is migrating an on-premises Oracle data warehouse to AWS. The warehouse contains 50 TB of data and runs complex queries that involve joins and aggregations. The team wants to minimize migration effort and cost while maintaining query performance. Which AWS service should they use?

Accepted Answer

Amazon Redshift. Option C is correct because Amazon Redshift is a fully managed petabyte-scale data warehouse optimized for complex queries. Option A is wrong because RDS is for OLTP, not OLAP. Option B is wrong because ElastiCache is in-memory caching, not a data warehouse. Option D is wrong because DynamoDB is NoSQL and not suited for complex joins.

Answer

Amazon RDS for Oracle

Answer

Amazon ElastiCache for Redis

Answer

Amazon DynamoDB

Question 6

A mobile gaming company needs a database to store player scores and leaderboards. The data must be updated in real time as players finish games. The database must support high write throughput and provide sub-millisecond read latency for leaderboard queries. Which database is best suited?

Accepted Answer

Amazon DynamoDB. Amazon DynamoDB is a NoSQL database that provides single-digit millisecond latency and can handle high write throughput. It also supports sorted data for leaderboards via Local Secondary Indexes or Global Secondary Indexes. RDS is slower and not designed for sub-millisecond reads. Redshift is for analytics. ElastiCache is a cache, not a primary database.

Answer

Amazon RDS for MySQL with read replicas

Answer

Amazon Redshift

Answer

Amazon ElastiCache for Redis

Question 7

A company wants to store session state for a web application that runs on Amazon EC2 instances behind an Application Load Balancer. The session data is ephemeral and must be highly available. Which two AWS services are suitable for this use case? (Choose two.)

Accepted Answer

Amazon DynamoDB. Option A (ElastiCache for Redis) is correct because it provides low-latency in-memory storage with replication for HA. Option C (DynamoDB) is correct because it is a highly available, fast key-value store. Option B is wrong because RDS is relational and not optimized for session state. Option D is wrong because S3 is not low-latency. Option E is wrong because Redshift is a data warehouse.

Answer

Amazon Redshift

Answer

Amazon S3

Answer

Amazon RDS for MySQL

Question 8

A social media application stores user posts in a DynamoDB table with a partition key of user_id and a sort key of timestamp. The most frequent query is to retrieve the 10 most recent posts for a given user. Which secondary index design would optimize this query?

Accepted Answer

Create an LSI with user_id as the partition key and timestamp as the sort key.. Option B is correct because a local secondary index (LSI) with the same partition key but a different sort key allows efficient retrieval of recent posts per user. Option A is wrong because a global secondary index (GSI) would require additional provisioned throughput and is unnecessary. Option C is wrong because using the sort key directly without an index still requires a scan. Option D is wrong because Elasticsearch adds operational complexity and cost for this simple query pattern.

Answer

Create a GSI with user_id as the partition key and timestamp as the sort key.

Answer

Use DynamoDB Streams to populate an Amazon Elasticsearch cluster for search queries.

Answer

Query the base table using the sort key timestamp with a limit of 10.

Question 9

Which THREE design patterns are commonly used to optimize DynamoDB performance for write-heavy workloads?

Accepted Answer

Using DynamoDB adaptive capacity to handle unbalanced access patterns.. Option A is correct because write sharding distributes writes evenly. Option C is correct because batching reduces API calls. Option E is correct because adaptive capacity helps handle uneven access patterns. Option B is wrong because global tables are for multi-region replication, not write optimization. Option D is wrong because sparse indexes are for read optimization.

Answer

Using sparse indexes on rarely accessed attributes.

Answer

Using global tables to distribute writes across regions.

Question 10

A company is migrating an on-premises MySQL database to Amazon Aurora MySQL. The database is 2 TB and the migration must have minimal downtime. The network bandwidth between the on-premises data center and AWS is 1 Gbps. Which migration approach is most appropriate?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication to keep the target in sync. AWS DMS can migrate data with minimal downtime. Using DMS with a full load and ongoing replication (change data capture) allows the source to remain active until the cutover. Option B (Aurora S3) is for importing from S3, not for live migration. Option C (RDS snapshot) is for RDS to Aurora, not on-premises. Option D (Snowball) is for large data volumes with limited bandwidth, but 2 TB at 1 Gbps can be transferred in about 5 hours (theoretical), so DMS is feasible and minimizes downtime.

Answer

Use mysqldump to export the data, upload to Amazon S3, and import into Aurora

Answer

Take a snapshot of the on-premises database and restore it to Aurora

Answer

Use AWS Snowball Edge to transfer the data physically to AWS

Question 11

A social media application uses Amazon DynamoDB with a table that has a partition key of 'user_id' and a sort key of 'post_timestamp'. The application frequently queries for the 10 most recent posts by a specific user. The query pattern uses a 'begins_with' condition on the sort key with a timestamp prefix. Recently, the query latency has increased significantly for users with many posts. Which design change would improve query performance?

Accepted Answer

Create a local secondary index (LSI) with 'user_id' as partition key and 'post_timestamp' as sort key, and query using reverse order with a limit of 10.. Option D is correct because creating a secondary index with 'user_id' as partition key and 'post_timestamp' as sort key, and using a 'Query' with reverse order and limit 10, avoids scanning all posts. Option A is wrong because a global secondary index still requires scanning if not optimized. Option B is wrong because changing partition key to 'post_id' would break the query pattern. Option C is wrong because DynamoDB Accelerator (DAX) caches results but doesn't reduce the read capacity consumed per query; the query still scans all items for a user.

Answer

Enable DynamoDB Accelerator (DAX) to cache the query results.

Answer

Create a global secondary index (GSI) with 'post_timestamp' as partition key and 'user_id' as sort key.

Answer

Change the table's partition key to 'post_id' to distribute data more evenly.

Question 12

A developer is designing a DynamoDB table for an order management system using the above CloudFormation template. The application needs to query orders by CustomerID. The current design has a GSI on CustomerID. However, the developer notices that the GSI has low write throughput and often throttles. What is the most cost-effective way to improve write throughput on the GSI?

Accepted Answer

Increase the WriteCapacityUnits of the GSI from 5 to a higher value.. Option A is correct because increasing the GSI's write capacity directly addresses the throttling. Option B is wrong because increasing table write capacity does not affect GSI capacity; GSI has its own. Option C is wrong because changing projection to KEYS_ONLY reduces storage but not write throughput. Option D is wrong because SQS does not help with DynamoDB write throughput.

Answer

Change the ProjectionType of the GSI to KEYS_ONLY.

Answer

Use Amazon SQS to buffer writes to the table.

Answer

Increase the WriteCapacityUnits of the table.

Question 13

A startup wants to store session data for a web application. Each session is small (under 1 KB) and accessed frequently with low latency. The data can be ephemeral and does not require complex queries. Which AWS database service is most suitable?

Accepted Answer

Amazon ElastiCache for Redis. Option A is correct because Amazon ElastiCache for Redis provides in-memory storage with low latency, perfect for session data. Option B is wrong because RDS is relational and overkill for simple key-value session data. Option C is wrong because DynamoDB is also suitable but for this use case, ElastiCache is simpler and faster. Option D is wrong because Neptune is a graph database, not appropriate for session storage.

Answer

Amazon DynamoDB

Answer

Amazon RDS for PostgreSQL

Answer

Amazon Neptune

Question 14

A company is designing a database for an e-commerce platform that stores product catalog data. The catalog has frequent reads and occasional writes. The data is highly relational but the team wants the lowest possible latency for read queries. Which database service should they choose?

Accepted Answer

Amazon DynamoDB with DAX. DynamoDB Accelerator (DAX) is an in-memory cache for DynamoDB that provides microsecond read latency. While DynamoDB itself is NoSQL, DAX is used to speed up reads. RDS with read replicas can improve read performance but not to microsecond level. ElastiCache could be used but requires more application logic. DocumentDB is a document database not optimized for microsecond reads.

Answer

Amazon DocumentDB

Answer

Amazon RDS for PostgreSQL with read replicas

Answer

Amazon ElastiCache for Redis

Question 15

A company uses Amazon DynamoDB for a session management store. The application writes and reads session data frequently. The team notices that write requests occasionally fail with ProvisionedThroughputExceededException. They want a cost-effective solution to handle these bursts. What should they do?

Accepted Answer

Enable DynamoDB Auto Scaling for the table. DynamoDB Auto Scaling adjusts throughput capacity automatically based on traffic patterns, handling bursts without manual intervention. Option B (increase table) would waste capacity. Option C (DAX) does not help with write throughput. Option D (SQS) adds complexity.

Answer

Increase the provisioned write capacity to a higher fixed value

Answer

Use DynamoDB Accelerator (DAX) to cache writes

Answer

Implement an Amazon SQS queue to buffer writes

DBS-C01 Practice Test 16 — 15 Questions

Exhibit

DBS-C01 Practice Test 16 — 15 Questions

Exhibit