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II
Part Two
Distributed Data
In a distributed system, there are many more things that can go wrong: networks can fault, clocks can desynchronize, and nodes can fail independently. These chapters explore the techniques used to build reliable distributed systems despite these challenges.
5
Chapters
20+
Interactive Demos
~4hr
Estimated Time
Prerequisite: Part I Foundations
These chapters build upon the concepts from Part I. Make sure you understand the foundations of data systems before diving into distributed systems.
Review Part I →Chapters
5
Replication
Learn how to keep data consistent across multiple nodes.
Leader-followerMulti-leaderLeaderlessConsistency issues
6
Partitioning
Understand how to split data across nodes for scalability.
Key range vs hashSecondary indexesRebalancingRequest routing
7
Transactions
Explore the concept of transactions and isolation levels.
ACID propertiesIsolation levelsSerializabilityDistributed transactions
8
The Trouble with Distributed Systems
Understand the fundamental challenges of distributed computing.
Unreliable networksClocks and timeProcess pausesKnowledge and truth
9
Consistency and Consensus
Deep dive into consistency models and consensus algorithms.
LinearizabilityCausal consistencyConsensus protocolsMembership services