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CAP Theorem and Consistency Models Questions

Understand the CAP theorem and how Consistency, Availability, and Partition Tolerance interact in distributed systems. Know different consistency models including strong consistency such as linearizability, eventual consistency, causal consistency, and session consistency, and how to apply them to different use cases. Be familiar with consensus protocols and distributed coordination primitives such as Raft and Paxos, quorum reads and writes, two phase commit and when to use them. Understand trade offs between consistency and availability under network partitions, patterns for hybrid approaches where different data uses different guarantees, and the product and developer experience implications such as latency, stale reads, and API contract clarity.

MediumBehavioral
0 practiced
A client complains that their streaming analytics results are sometimes inconsistent across regions for a short window. As a data engineer, how would you explain the likely causes in terms of consistency models and propose three mitigations that can be implemented with minimal disruption?
HardSystem Design
0 practiced
A global event-sourcing system must ensure total ordering of events for a given aggregate while remaining highly available. Propose an architecture that balances these requirements, explaining how you would enforce per-aggregate ordering and what happens during partitions.
EasyTechnical
0 practiced
Explain the CAP theorem in your own words and illustrate it with a concrete example relevant to data engineering. Describe a distributed ingestion system that must choose between consistency and availability during a network partition, and explain which property you would prioritize and why.
MediumTechnical
0 practiced
You're responsible for a global analytics store that uses leaderless, quorum-based replication (Dynamo-style). Explain how hinted handoff and read-repair work together to ensure eventual consistency and reduce stale reads.
MediumTechnical
0 practiced
Explain idempotency in distributed write paths. Provide at least three strategies for ensuring idempotent writes from mobile clients in the presence of retries and partitions, and discuss how each interacts with consistency guarantees.

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