Data Partitioning and Sharding Questions

Techniques and operational practices for horizontally partitioning data across multiple database instances or storage nodes to achieve scale, improve performance, and manage growth. Includes selection and design of partition and shard keys to evenly distribute load and avoid hotspots, with range based, hash based, and directory based approaches and consistent hashing mechanisms. Covers handling uneven distribution and data skew, hotspot detection and mitigation, and the impact of partitioning on query patterns such as joins and cross shard queries. Explains implications for transactions and consistency, including transactional boundaries that span partitions and approaches to distributed transactions and compensation. Describes resharding and online data migration strategies, rolling rebalances, and methods to minimize downtime and data movement. Emphasizes operational concerns including shard management, automation, monitoring and alerting, failure recovery, and performance tuning. Discusses trade offs between simplicity, latency, throughput, and operational complexity and highlights considerations for both transactional and analytical workloads, including routing, caching, and coordination patterns.

MediumTechnical

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Compare two approaches for atomic cross-shard transactions: two-phase commit (2PC) and the Saga pattern. For each approach discuss performance characteristics, failure modes, developer complexity, and when one is preferable over the other.

MediumSystem Design

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Design a strategy to perform schema changes across a sharded cluster (e.g., adding a nullable column to orders). Requirements: minimize downtime, avoid cross-shard inconsistencies, and support rollback. Outline steps and tooling you'd use.

EasyTechnical

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Describe three simple metrics or signals you would monitor to detect shard hotspots in production. For each metric, explain how you would set alert thresholds and one automated mitigation action you could take when triggered.

MediumTechnical

0 practiced

Design a caching and cache-invalidation strategy for a sharded datastore where most reads are per-user. Requirements: reduce load on DB, maintain strong enough freshness for user-facing reads, and scale cache invalidation when writes are frequent.

MediumSystem Design

0 practiced

Design an approach to support global secondary indexes (GSIs) in a sharded OLTP system where the primary shard key is user_id but queries require fast lookup by email (unique). Discuss options: global index service, index per shard with routing, or consistent centralized index, and state trade-offs.

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