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The article explains how to detect and troubleshoot Redis latency spikes by measuring baseline performance, using slowlog and latency‑monitor, checking network RTT, fork‑induced pauses, huge pages, swap usage, AOF settings, expiration handling, and big‑key problems, providing concrete commands and mitigation steps.
This article explains how MySQL writes data to cache before flushing to disk, compares single‑row versus batch inserts, discusses how hardware limits, transaction size, and lock contention affect performance, and shows how to estimate an optimal batch size with concrete calculations and MyBatis examples.
This article explains how Redis Bitmap stores binary states using bit arrays, details its commands and use cases, then introduces Bloom Filter's probabilistic set membership, compares their advantages, limitations, and typical scenarios such as cache penetration protection and blacklist filtering.
This article walks through Spring Boot’s built‑in utilities—including request logging with CommonsRequestLoggingFilter, request/response wrappers, the OncePerRequestFilter base class, and AOP helpers like AopContext, AopUtils, and ReflectionUtils—showing how to configure and apply them in real code.
This article explains how Spring’s ResponseBodyEmitter, SseEmitter, and StreamingResponseBody can be used to build asynchronous streaming endpoints that continuously push data to clients, avoid servlet thread blocking, and prevent request‑timeout problems, with complete code examples and usage guidelines.
The article demonstrates how combining Java generics with functional programming—using lambda‑based callbacks and generic pagination utilities—can transform repetitive data‑access code into a concise, reusable structure, while also discussing the benefits, trade‑offs, and potential debugging challenges of this approach.
The article walks through how to assess MySQL table size, explains why large tables slow down due to B+‑tree index overhead, and compares three practical solutions—table partitioning, database sharding (horizontal, vertical, hash‑range), and hot‑cold archiving—while outlining their trade‑offs and selection criteria.
COUNT(*), COUNT(1) and COUNT(column) may look similar, but they differ in how MySQL processes them, the rows they count, and performance implications, especially with NULL values and index usage; this article explains each form, cites official InnoDB behavior, and guides proper usage.
This article explains how Guava's RateLimiter, built on the token‑bucket algorithm, provides smooth burst handling, configurable rates, warm‑up support, and thread safety, and demonstrates its usage through detailed code examples and best‑practice recommendations for API, database, and crawler throttling.
The article explains how using a large OFFSET with MySQL LIMIT forces the engine to scan and sort hundreds of thousands of index and data pages, then presents three concrete optimizations—covering index scans, subqueries, and partitioned tables—to dramatically reduce the work.
