Cross-shard queries in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Cross-Shard Query Challenges

Which of the following best describes a primary challenge when executing cross-shard queries in a distributed database system?

A Ensuring data consistency and atomicity across multiple shards during query execution

B Reducing the size of individual shards to improve query speed

C Increasing the number of shards to reduce network latency

D Using a single master node to handle all queries

💡 Hint

Think about what happens when data is spread across multiple independent storage units.

Cross-shard queries must coordinate data from multiple shards, which can lead to challenges in maintaining consistency and atomicity.

❓ Architecture

intermediate

Choosing a Cross-Shard Query Coordination Method

Which architecture pattern is commonly used to coordinate cross-shard queries to ensure consistency and minimize latency?

A Using a single shard to store all data to avoid cross-shard queries

B Centralized coordinator that collects partial results from shards and merges them

C Random shard selection to reduce load on any single shard

D Each shard independently returns full query results without coordination

💡 Hint

Consider how partial results from different shards can be combined efficiently.

A centralized coordinator collects partial results from each shard and merges them to produce the final query result, balancing consistency and performance.

❓ scaling

advanced

Scaling Cross-Shard Query Performance

To improve the performance of cross-shard queries in a system with many shards, which approach is most effective?

A Implementing parallel query execution across shards with asynchronous result aggregation

B Reducing the number of shards to minimize network hops

C Increasing the replication factor of each shard to reduce read latency

D Using synchronous blocking calls to each shard sequentially

💡 Hint

Think about how to use concurrency to reduce total query time.

Parallel execution with asynchronous aggregation allows queries to run concurrently on shards, reducing overall latency.

❓ tradeoff

advanced

Tradeoffs in Cross-Shard Query Consistency Models

Which tradeoff is typically encountered when choosing between strong consistency and eventual consistency for cross-shard queries?

A Eventual consistency requires locking all shards, increasing latency

B Strong consistency reduces latency but risks stale data; eventual consistency increases latency but guarantees up-to-date data

C Both models provide the same latency and data freshness guarantees

D Strong consistency increases latency but guarantees up-to-date data; eventual consistency reduces latency but may return stale data

💡 Hint

Consider how data freshness and response time relate in distributed systems.

Strong consistency ensures the latest data but can slow queries due to coordination; eventual consistency is faster but may serve outdated data.

❓ estimation

expert

Estimating Network Overhead in Cross-Shard Queries

A system has 10 shards. Each shard returns 1 MB of data per query. The network bandwidth between coordinator and shards is 100 Mbps. Approximately how long will it take to transfer all shard data to the coordinator if queries are executed in parallel and network bandwidth is fully utilized?

A About 80 seconds

B About 8 seconds

C About 0.8 seconds

D About 0.08 seconds

💡 Hint

Calculate total data size and convert bandwidth to MB/s for transfer time.

Total data is 10 MB. 100 Mbps equals 12.5 MB/s. Transfer time = 10 MB / 12.5 MB/s = 0.8 seconds.