Introducing full-stack Internet architecture technologies centered on Java
This guide explains how to install Ollama on a Windows machine, configure its environment, and use it to download and run the DeepSeek‑R1 1.5B large language model locally, enabling offline AI interactions without relying on remote servers.
This article explains the probabilistic Bloom filter data structure, its characteristics and typical use cases such as cache‑penetration prevention, details its simple implementation steps, demonstrates how Redis (via Redisson) provides built‑in Bloom filter support with Java code examples, and summarizes its practical benefits.
This article explains the concept and importance of MySQL database transactions, describes the ACID properties, shows how to use transaction control statements and savepoints, and demonstrates each isolation level (read uncommitted, read committed, repeatable read, serializable) with practical SQL examples.
This article explains the different MySQL JOIN types—including INNER, LEFT, RIGHT, and simulated FULL OUTER joins—by creating sample order and customer tables, inserting test data, and showing the corresponding SQL statements and result sets with visual diagrams.
This article explains MySQL's various numeric, date/time, and string data types, discusses their characteristics such as signed/unsigned integers, floating‑point precision, fixed‑point accuracy, and provides practical best‑practice recommendations for choosing optimal types in database design.
This article introduces core relational database concepts, covering tables, data models and ER diagrams, the fundamentals of SQL, and the first three normal forms, providing clear explanations and examples to build a solid foundation for further database study.
This article explains MySQL's logical architecture, detailing the four main layers—connection, core service, storage engine, and data storage—while providing code examples and insights into each component's role in the widely used open‑source relational database.
This article explains how to implement distributed locks in Redis using the SETNX command, atomic Lua scripts, the Redisson Java client, and the RedLock algorithm, providing code examples and discussing their advantages and limitations in distributed backend systems.
This article explains why Redis achieves extremely high performance, reaching up to 100,000 QPS, by leveraging its in‑memory design, I/O multiplexing, optimized data structures such as SDS, ziplist and skiplist, and a single‑threaded event loop, each detailed with examples and code.
This article explains how Redis as a distributed cache can cause data inconsistency with relational databases during write operations, outlines read and update workflows, compares five cache‑update strategies, and presents a delayed double‑delete solution with sample code to maintain consistency.
