In a read-heavy system, what is the primary bottleneck that typically limits performance?

Network latency for write operations

Memory bandwidth for write operations

Consider a distributed system architecture for a read-heavy application. Which of the following replication strategies would offer the lowest read latency for geographically dispersed users?

Master-Slave replication with read replicas near users

In a system designed for read-heavy workloads, what is the primary advantage of using a columnar database over a row-oriented database?

Reduced I/O for analytical queries that read specific columns

More efficient for transactional operations (OLTP)

Better support for complex joins on many-to-many relationships

What is a common disadvantage of implementing aggressive caching in a read-heavy system, especially when some writes do occur?

Cache invalidation complexity leading to stale data

Higher network bandwidth consumption

In a system with a read-heavy workload, how does denormalization typically affect read performance?

It increases read performance by reducing the need for joins.

It decreases read performance by increasing data redundancy.

It has no significant impact on read performance.

It decreases read performance due to increased write overhead.

Which of the following is a key consideration when optimizing a read-heavy system for low latency read requests?

Prioritizing eventual consistency over strong consistency for reads.

Minimizing write operations to the primary data store.

Maximizing the use of complex stored procedures.

Reducing the number of database indexes to simplify writes.

What trade-off is commonly made in read-heavy systems to achieve higher read throughput, even at the expense of write performance?

Simplified data structures and fewer constraints

Increased data consistency guarantees

More complex query execution plans

Consider a system that uses a Content Delivery Network (CDN). How does a CDN primarily benefit a read-heavy website?

By reducing the load on origin servers for static content and caching.

By accelerating database write operations.

By providing real-time data synchronization between servers.

By encrypting all outgoing traffic for enhanced security.

Which of the following scenarios would most strongly indicate a system is experiencing a read-heavy workload?

A large number of SELECT queries compared to INSERT/UPDATE/DELETE queries.

High CPU utilization due to complex calculations.

Frequent deadlocks and lock contention on write operations.

Significant network traffic related to large file uploads.

In a read-heavy distributed database, what is the primary benefit of sharding data based on a read-heavy access pattern (e.g., user ID)?

Distributes read load across multiple shards, improving parallel processing.

Ensures all writes go to a single shard for simplicity.

Simplifies data backup and recovery processes.

Reduces the need for indexing within each shard.

What is a potential downside of using read replicas in a read-heavy system if not managed carefully?

Potential for read-after-write inconsistency.

Increased cost of maintaining multiple database instances.

Reduced overall system availability.

Limited scalability of read operations.

For a read-heavy analytical system, which storage format is generally preferred for efficiency when querying large datasets?

Columnar storage (e.g., Parquet, ORC)

Row-based storage (e.g., standard relational tables)

Document-based storage (e.g., JSON files)

Read Heavy vs Write Heavy System

Read Heavy vs Write Heavy System - Test Paper