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This article provides a comprehensive introduction to distributed systems, covering their definition, purpose, key characteristics such as transparency and scalability, and enumerates the mainstream technologies and tools commonly used to build and operate them.
This article introduces core concepts of distributed systems, covering node models, replica types, consistency levels, data distribution strategies, lease and quorum mechanisms, logging techniques, two‑phase commit, MVCC, Paxos, and the CAP theorem, providing a comprehensive overview for engineers and researchers.
This article explains Zookeeper’s core concepts, its ZAB consensus protocol, and surveys its essential roles in major big‑data components such as Kafka, Hadoop, HBase, and Solr, illustrating how it provides configuration, naming, coordination, leader election, and high‑availability services across distributed architectures.
Spring Session enables distributed session sharing by storing HTTP session data in Redis, using a filter and listener configuration to replace Tomcat’s in‑memory storage, managing three Redis keys with coordinated expirations, and subscribing to keyspace events for reliable cleanup and cross‑instance access.
This article provides a comprehensive overview of distributed‑system fundamentals, covering node concepts, failure types, replication models, consistency levels, performance and availability metrics, data‑distribution strategies, replica control protocols, lease mechanisms, quorum, two‑phase commit, MVCC, Paxos, and the CAP theorem.
This article explains the CAP theorem, the trade‑offs among consistency, availability and partition tolerance, describes strong, weak and eventual consistency models, and introduces the BASE approach as a practical alternative for large‑scale distributed systems.
The article traces website architecture evolution from a single‑server LAMP setup to distributed clusters, highlighting stages such as service separation, caching, load‑balanced application servers, read‑write database splitting, CDN/reverse proxy use, distributed storage, NoSQL/search integration, and finally SOA‑based business and service segmentation.
This article provides a comprehensive introduction to distributed systems, outlining recent research trends, practical technologies such as Paxos and MapReduce, and classifying the field into storage, computation, and management sub‑domains while highlighting why studying this area remains valuable today.
The article commemorates Joe Armstrong, the creator of Erlang, outlining his life, contributions to fault‑tolerant distributed computing, his influential talks in China, and the programming wisdom he shared, while providing links to his historic presentations.
The article explains the CAP theorem, detailing how distributed systems must trade off consistency, availability, and partition tolerance, and explores CP vs AP designs, then introduces the BASE model—Basically Available, Soft State, Eventual Consistency—as a practical complement for real‑world architectures.