Distributed Data Systems / Najlacnejšie knihy
Distributed Data Systems

Code: 53879355

Distributed Data Systems

by Miguel Torres

When important state spans machines, familiar database assumptions become distributed-systems questions. Which replica is authoritative? What does a timeout mean? Can a write remain correct during a partition? Who repairs conflict ... more

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Book synopsis

When important state spans machines, familiar database assumptions become distributed-systems questions. Which replica is authoritative? What does a timeout mean? Can a write remain correct during a partition? Who repairs conflicting histories after the network recovers?

Distributed Data Systems is a rigorous, practical guide to designing data architectures around explicit guarantees and realistic failure schedules. It develops replication, partitioning, consistency, consensus, time, transactions, rebalancing, and repair as connected mechanisms rather than isolated buzzwords.

The book begins with the promises an application must preserve and works backward toward the protocols capable of preserving them. A running inventory and reservation system makes abstract concepts concrete: stale reads can be acceptable for a catalog, while allocating the final unit of stock requires a much stronger invariant.

Inside, you will learn how to:

- Compare leader-based, multi-leader, and leaderless replication
- Calculate quorum intersections and reason about acknowledged durability
- Choose partition keys and control hotspots, movement, and rebalancing
- Describe consistency through observable histories and session guarantees
- Understand consensus logs, membership changes, leases, and split brain
- Separate two-phase commit, distributed transactions, and sagas
- Design repair, anti-entropy, tombstone, and resurrection controls
- Test correctness through fault schedules, histories, and explicit unknowns

The explanations are connected to foundational papers, production engineering accounts, open-source databases, small executable models, and operational review checklists. Documented guarantees are kept separate from inference, and failure is examined as a timeline rather than a single red icon on a diagram.

For intermediate and advanced backend engineers, Distributed Data Systems builds the judgment needed to evaluate real databases and protocols without hiding behind labels such as strongly consistent or eventually consistent. The result is a clearer way to reason about authority, ambiguity, progress, and recovery.

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