This article details a joint research effort between Meituan and East China Normal University that combines cost‑based methods with AI‑driven, data‑centric models to automatically generate and evaluate missing indexes for billions of daily slow queries, improving recommendation accuracy and query performance.
The article explains why slow SQL queries drain I/O and CPU resources, outlines prioritization rules, details MySQL execution steps, identifies performance‑affecting factors, and provides practical solutions and best‑practice guidelines for diagnosing and optimizing slow MySQL queries in production environments.
This article introduces ZTO Technology’s Ark Platform, a database PaaS solution that automates deployment, backup, monitoring, data flashback, and slow‑SQL optimization, detailing its architecture, core features, and the operational benefits it brings to large‑scale logistics environments.
The article examines why MySQL queries become slow, detailing system‑level issues such as network latency, I/O bottlenecks, and CPU settings, alongside database‑level problems like missing indexes, type conversion, poor execution plans, lock contention, skewed data, and inefficient SQL patterns, and offers optimization strategies.
This article explains how to choose MySQL storage engines, apply effective table partitioning and indexing, identify common causes of slow queries, adopt practical SQL optimization tips, use diagnostic tools, and handle data loss or bugs with proper recovery procedures.
This article explains MySQL’s indexing fundamentals, the left‑most prefix rule, B+‑tree structure, disk I/O considerations, and provides step‑by‑step methods and real‑world cases for diagnosing and optimizing slow queries in production systems.
