DBS-C01 Workload-Specific Database Design Practice Test 15 — 15 Questions

Question 1

A company is using Amazon DynamoDB for a gaming leaderboard that updates frequently. They need to maintain a sorted list of top 100 players by score. Which THREE design patterns can achieve this efficiently?

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

Accepted Answer

Use a Global Secondary Index (GSI) with score as the sort key and query with ScanIndexForward=false and Limit=100.. A Global Secondary Index (GSI) with score as the sort key allows you to query items in descending order using ScanIndexForward=false and limit the result to the top 100 players. This pattern efficiently retrieves the highest scores without scanning the entire table, leveraging DynamoDB's index query capabilities.

Answer

Use DynamoDB Accelerator (DAX) to cache query results.

Answer

Scan the entire table and sort the results in memory.

Question 2

A company runs a large-scale e-commerce platform using Amazon RDS for MySQL with a Multi-AZ deployment. The database has a table 'orders' with 200 million rows. Recently, they added a new index on the 'order_date' column to improve reporting queries. After adding the index, they noticed increased write latency and occasional replication lag. The application writes new orders continuously. The table experiences about 10,000 writes per second. The DB instance is db.r5.4xlarge. The index creation was done using the ALTER TABLE statement with a default algorithm. What is the most likely cause of the increased write latency and replication lag?

Accepted Answer

The index was created using the default algorithm (COPY), which locks the table and blocks writes, causing replication lag.. The default algorithm for ALTER TABLE in MySQL is COPY, which creates a new table, copies all rows, and rebuilds indexes. During this process, the table is locked with a write lock, blocking DML operations and causing increased write latency. In a Multi-AZ deployment, the DDL is replicated to the standby, but the lock on the primary delays writes, which can manifest as replication lag when the standby applies the same blocking DDL.

Answer

The index creation DDL statement is not replicated to the standby instance, causing inconsistency.

Answer

The instance size is insufficient for the write workload.

Answer

The new index is causing excessive overhead on write operations due to index maintenance.

Question 3

A company uses Amazon DynamoDB for a real-time analytics platform. The table has a partition key of 'customer_id' and a sort key of 'event_timestamp'. The table receives 50,000 write requests per second, evenly distributed across 10,000 customers. The application frequently queries the last 10 events for a given customer. The company notices that some queries are throttled during peak hours. The table's write capacity is set to 50,000 WCUs, and read capacity to 10,000 RCUs. The throttled queries are read requests. What is the most likely cause of the throttling, and what should be done to resolve it?

Accepted Answer

Optimize the query by using Query with KeyConditionExpression on the sort key and Limit=10.. The throttling occurs because the application uses Scan or an inefficient query pattern that consumes excessive read capacity. Using Query with KeyConditionExpression on the sort key and Limit=10 retrieves only the last 10 events per customer efficiently, reducing read consumption and avoiding throttling without increasing RCUs.

Answer

Increase the write capacity units to handle the write load.

Answer

Increase the read capacity units to 20,000 RCUs.

Answer

Add a global secondary index with the same keys to distribute read load.

Question 4

A company is running a MySQL database on an EC2 instance and wants to migrate to Amazon RDS for MySQL with minimal downtime. The database is 500 GB in size and has a high write workload. Which migration approach is most appropriate?

Accepted Answer

Use AWS Database Migration Service (DMS) with ongoing replication.. AWS DMS with ongoing replication (change data capture) is the most appropriate approach because it allows you to migrate the 500 GB database with minimal downtime. DMS performs a full load of the existing data and then continuously replicates ongoing changes from the source MySQL EC2 instance to the target Amazon RDS for MySQL, enabling a cutover with only a brief pause in writes.

Answer

Export data to Amazon S3 and use AWS Glue to load into RDS.

Answer

Copy the MySQL data directory to Amazon EBS and attach to RDS.

Answer

Take a mysqldump from the source and import into RDS.

Question 5

A company uses Amazon DynamoDB for a gaming leaderboard. The application updates scores frequently. Reads must be strongly consistent, and writes must be optimized for cost. Which table design minimizes cost while meeting consistency requirements?

Accepted Answer

Use Amazon DynamoDB Accelerator (DAX) for caching.. Amazon DynamoDB Accelerator (DAX) provides an in-memory cache that supports strongly consistent reads, which meets the application's requirement for strongly consistent reads. By caching frequently accessed leaderboard data, DAX reduces the number of read capacity units consumed from the DynamoDB table, thereby lowering read costs. Writes are still performed directly on the DynamoDB table, and DAX does not affect write costs, so the design optimizes overall cost while maintaining consistency.

Answer

Use eventually consistent reads with a conditional write.

Answer

Store scores in Amazon S3 and use S3 Select for reads.

Answer

Use DynamoDB Streams to replicate reads to a separate table.

Question 6

A company needs to store application logs for 90 days and run periodic analytical queries. The logs are generated at 1 TB per day. Which storage solution is most cost-effective?

Accepted Answer

Store logs in Amazon S3 and use S3 Select for queries.. Amazon S3 is the most cost-effective storage solution for 90-day retention of 1 TB/day of application logs, as it offers low-cost object storage with lifecycle policies to automatically expire data after 90 days. S3 Select allows you to run analytical queries (e.g., filtering, aggregations) directly on the data stored in S3 using SQL-like statements, without needing to load data into a separate analytics engine, thus minimizing compute costs and operational overhead.

Answer

Store logs in Amazon RDS for MySQL with partitioning.

Answer

Store logs in Amazon Redshift with automatic compression.

Answer

Store logs in Amazon DynamoDB with TTL for expiration.

Question 7

A company is designing a database for a global e-commerce platform that requires sub-millisecond read latencies from multiple AWS regions. The data is mostly read, with occasional writes. Which database solution meets these requirements?

Accepted Answer

Amazon DynamoDB with Global Tables.. Amazon DynamoDB with Global Tables is the correct choice because it provides a fully managed, multi-Region, multi-master database that replicates data across AWS Regions with sub-second latency, enabling sub-millisecond read latencies for a globally distributed, mostly-read workload. The occasional writes are handled efficiently by the multi-master design, which automatically resolves conflicts using last-writer-wins semantics, ensuring strong eventual consistency.

Answer

Amazon ElastiCache for Redis with global datastore.

Answer

Amazon Aurora MySQL with Aurora Global Database.

Answer

Amazon RDS for MySQL with Multi-AZ and read replicas.

Question 8

A company runs a MongoDB workload on Amazon EC2 and wants to migrate to Amazon DocumentDB. The database has a total size of 2 TB and experiences 10,000 writes per second during peak. Which migration strategy minimizes downtime?

Accepted Answer

Use AWS DMS with continuous replication.. AWS DMS with continuous replication (change data capture) is the correct strategy because it allows you to keep the source MongoDB and target DocumentDB synchronized in near-real time, minimizing downtime to a brief cutover window. For a 2 TB database with 10,000 writes per second, a full export/import would take hours and require significant downtime, while DMS handles the initial full load and then continuously applies ongoing changes until you switch over.

Answer

Export data using mongodump and import with mongorestore.

Answer

Use AWS Glue to stream data to DocumentDB.

Answer

Copy data files to Amazon S3 and load into DocumentDB.

Question 9

A company needs a database for a serverless web application that stores user sessions. The sessions expire after 24 hours. The database must be highly available and require no server management. Which AWS service is most appropriate?

Accepted Answer

Amazon DynamoDB with TTL.. Amazon DynamoDB with TTL is the most appropriate choice because it provides a fully managed, serverless, highly available NoSQL database that can automatically expire user sessions after 24 hours using the Time to Live (TTL) feature. DynamoDB's on-demand capacity mode eliminates server management, and its built-in replication across multiple Availability Zones ensures high availability without any manual intervention.

Answer

Amazon ElastiCache for Redis with cluster mode.

Answer

Amazon RDS for PostgreSQL with Multi-AZ.

Answer

Amazon S3 with lifecycle policies.

Question 10

A company is migrating an on-premises Oracle database to Amazon Aurora PostgreSQL. The database is 1 TB and has complex stored procedures. The migration must be completed within a 4-hour downtime window. Which migration approach is most efficient?

Accepted Answer

Use AWS SCT to convert schema and code, then AWS DMS for data migration.. AWS SCT converts the Oracle schema and complex stored procedures to Aurora PostgreSQL-compatible code, while AWS DMS performs the full data migration within the 4-hour window. This combination handles both schema/code conversion and bulk data transfer efficiently, meeting the time constraint.

Answer

Use AWS Schema Conversion Tool (SCT) to convert schema only.

Answer

Use Oracle Data Pump to export and pg_restore to import.

Answer

Use AWS DMS with ongoing replication.

Question 11

A company runs a financial application on Amazon RDS for PostgreSQL that requires point-in-time recovery (PITR) with a recovery point objective (RPO) of 1 second and recovery time objective (RTO) of 5 minutes. Which configuration meets these requirements at the lowest cost?

Accepted Answer

Multi-AZ RDS with synchronous standby.. Multi-AZ RDS for PostgreSQL with synchronous standby replication provides automatic failover to a standby in a different Availability Zone, enabling an RTO of typically 1–2 minutes, well within the 5-minute requirement. Automated backups and transaction logs allow PITR with an RPO of 1 second by restoring to any point within the retention period, and the synchronous standby ensures zero data loss during failover, meeting the strict RPO at the lowest cost for this high-availability need.

Answer

Single-AZ RDS with automated backups and manual snapshot restore.

Answer

Single-AZ RDS with a read replica and promote on failure.

Answer

Single-AZ RDS with cross-region snapshot copy.

Question 12

A company uses Amazon DynamoDB for a time-series IoT application. Each device sends a data point every second. The application queries data by device ID and timestamp range. Which table design is most efficient?

Accepted Answer

Use device ID as the partition key and timestamp as the sort key.. It models the access pattern directly: using device ID as the partition key ensures all data for a device is co-located, and timestamp as the sort key enables efficient range queries (e.g., Query with KeyConditionExpression on timestamp between start and end). This design avoids hot partitions and allows DynamoDB to retrieve the exact time-series slice without scanning.

Answer

Use a composite key of device ID and timestamp as the partition key.

Answer

Use device ID as the partition key and a random suffix as the sort key.

Answer

Use timestamp as the partition key and device ID as the sort key.

Question 13

A company is designing a database for an analytics workload that requires storing 5 TB of data and running complex SQL queries with joins. The workload is read-heavy and requires high concurrency. Which TWO services are suitable for this workload? (Choose two.)

Accepted Answer

Amazon RDS for MySQL with read replicas. Amazon RDS for MySQL with read replicas is suitable because the workload is read-heavy and requires high concurrency. Read replicas offload SELECT traffic from the primary instance, allowing complex SQL queries with joins to scale horizontally while maintaining ACID compliance for the 5 TB dataset.

Answer

Amazon ElastiCache for Redis

Answer

Amazon DynamoDB

Answer

Amazon S3

Question 14

A company runs a PostgreSQL database on Amazon RDS for a CRM application. The database is 500 GB and experiences high read traffic. The company wants to improve read scalability and reduce latency. Which TWO actions should the company take? (Choose two.)

Accepted Answer

Implement Amazon ElastiCache for Redis to cache common queries.. Amazon ElastiCache for Redis can cache the results of frequently executed read queries, offloading read traffic from the RDS PostgreSQL instance and reducing latency for repeated queries. This is especially effective for read-heavy workloads where the same data is requested many times, as Redis provides sub-millisecond response times and reduces the load on the database.

Answer

Store large objects in Amazon S3 and reference them.

Answer

Enable Multi-AZ for automatic failover.

Answer

Migrate data to Amazon DynamoDB with Global Tables.

Question 15

A company runs a critical e-commerce platform on Amazon Aurora MySQL. The database is 2 TB and experiences a sudden spike in write latency during flash sales. The application uses auto-generated UUIDs as primary keys. The CPU utilization on the writer instance is 80%, and the read replicas show low utilization. Write latency has increased from 5 ms to 200 ms. The company needs to reduce write latency with minimal application changes. Which course of action is MOST effective?

Accepted Answer

Change the primary key to an auto-increment BIGINT and recreate indexes.. B is correct because UUID primary keys cause random writes that fragment the B-tree index, leading to frequent page splits and high write latency. Changing to an auto-increment BIGINT allows sequential writes, which fill index pages contiguously and reduce the write amplification that drives latency from 5 ms to 200 ms. This requires no application logic changes beyond the schema migration, making it the most effective minimal-change solution.

Answer

Implement sharding across multiple Aurora clusters.

Answer

Add more read replicas and redirect write-heavy queries to replicas.

Answer

Upgrade the writer instance to a larger instance type with more IOPS.