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NoSQL Overview NoSQL Use Cases Traditional relational databases face limitations with modern web-scale applications: Single-machine MySQL systems struggle with large datasets exceeding storage capacity Index sizes can surpass available memory resources Read/write workloads overwhelm single-server capabilities Caching solutions like Memcached ...

Understanding Redis Performance Redis is renowned for its exceptional speed, a characteristic derived from several fundamental design choices: In-Memory Operation: As a memory-based data store, Redis inherently benefits from the much faster read and write speeds of RAM compared to disk I/O. Optimized Data Structures: It leverages highly effici ...

Implementation Strategy To monitor processing progress in ASP.NET MVC applications, we ipmlement a polling mechanism using JavaScript to periodically query server-side status updates. Below are the implementation details. Front end Implementation The JavaScript function timedCount() sends AJAX requests at regular intervals to fetch the latest p ...

Scenario: Exposing System Resource Usage via API When building APIs that expose system metrics like CPU and memory utilization, performance optimization becomes critical. This article explores how the Proxy Pattern can efficiently handle resource monitoring requests. The Challenge Multiple servers may simultaneously call a resource monitoring e ...

Introduction to Caching Caching is a common feature in ORM frameworks, designed to enhance query performance and reduce database load by storing frequently accessed data in memory. Cache Architecture In the MyBatis source code, classes related to caching are located in the cache package. The core of this system is the Cache interface, with the ...

Why caching matters Every request that reaches the database consumes CPU, memory, and disk I/O. When traffic spikes, the database becomes the first bottleneck. A cache layer—placed between the application and the datastore—absorbs the majority of read requests, reduces latency, and acts as a circuit-breaker when the primary store is unavailable ...

Stateless Authentication with RedisIn a distributed architecture, relying on Tomcat's local sessions for user state leads to inconsistencies across instances. Redis serves as a centralized session store to solve this. When a user logs in via SMS, a unique token is generated and stored in Redis as the key, with the serialized user DTO as the val ...

Understanding MyBatis Caching Mechanisms MyBatis incorporates an internal caching system designed to enhance application performance by minimizing redundant database interactions. This caching operates at two distinct levels: a local, session-scoped cache and a global, application-scoped cache. First-Level Cache: SqlSession Scope The first-leve ...

In the previous article, we explored Spring Boot integration with Redis. This article focuses on implementing Redis caching in MyBatis operations. We'll examine four key annotations: @CachePut, @Cacheable, @CacheEvict, and @CacheConfig. Fundamentals @Cacheable The @Cacheable annotation configures method-level caching, storing results based on m ...

Introduction to LFU Caching LFU (Least Frequently Used) is a caching algorithm that removes the least frequently accessed items when the cache reaches its capacity. Unlike LRU (Least Recently Used), which considers only recency, LFU prioritizes access frequency. Comparison of LFU and LRU Consider a cache with capacity 3 and the following access ...