This comprehensive guide explains why MySQL indexes often become ineffective, outlines ten typical failure scenarios with concrete EXPLAIN examples, and provides practical solutions, scripts, best‑practice recommendations, and monitoring techniques to dramatically improve slow‑query performance.
The VLDB‑2025 paper RCRank introduces a multimodal framework that collects slow‑query data, uses rule‑based and LLM analysis to identify root causes, quantifies their impact, and ranks them, achieving a 14% boost in optimization efficiency for cloud databases.
This guide presents eight practical MongoDB shell scripts—covering database size analysis, connection monitoring, long‑running query termination, table‑scan detection, replica‑set health checks, and slow‑query profiling—plus usage tips and cautions for reliable administration.
This article explains why slow SQL becomes a critical risk during large‑scale promotions, outlines a three‑step method—observing the query, analyzing it with EXPLAIN, and designing fixes—then demonstrates each step with concrete MySQL examples, tips, and overall optimization principles.
This article explains how to detect, analyze, and resolve slow SQL queries that threaten service stability, offering step‑by‑step guidance, EXPLAIN analysis, and real‑world case studies to help developers quickly pinpoint and fix performance bottlenecks.
This article provides a comprehensive guide to MySQL performance optimization, covering CPU and I/O bottlenecks, index types and tuning, slow query capture and analysis, and best practices for table design and partitioning to improve query efficiency.
This article analyzes a MySQL large‑table performance issue caused by slow queries and full‑table scans, demonstrates using pt‑query‑digest, explains execution plans, proposes index redesign, shows backup and restore with mydumper, compares online DDL and pt‑osc, and presents batch delete strategies to reduce latency.
This article explains how to collect comprehensive MySQL performance metrics—including connections, buffer cache, locks, statement counts, throughput, server variables, and slow‑query analysis—using only MySQL's native SHOW commands, providing a fast, low‑overhead monitoring solution.
This article explains why using indexes in MySQL does not always prevent slow queries, analyzes full‑index scans, index selectivity, back‑table lookups, virtual columns, and provides practical optimization techniques to reduce scanned rows and improve performance.
This article discusses MySQL table design choices, partitioning methods, index best practices, common causes of slow queries with optimization tips, useful diagnostic tools, and recommended actions when accidental operations or bugs affect data.
This article reviews common MySQL pitfalls—including engine choice, table partitioning, index design, slow‑query causes and optimizations, diagnostic tools, and how to recover from accidental data loss—offering practical guidance for developers to improve performance and reliability.
This article walks through a real‑world MySQL performance case at Meituan‑Dianping, showing how systematic monitoring, packet capture, and step‑by‑step analysis identified the Thread‑Pool as the bottleneck and how disabling and fine‑tuning its parameters reduced slow queries from thousands to just a few dozen.
