This series finale presents a universal 6-step SOP for Java production troubleshooting, a bottom-up layered diagnosis model, a quick-reference guide for 10 common failure patterns with symptoms, root causes, and tools, plus five golden principles for incident handling.
This comprehensive guide covers the complete slow SQL troubleshooting lifecycle: enabling slow query logs, interpreting EXPLAIN plans, diagnosing nine common index failure patterns, resolving transaction lock contention, and applying architectural optimizations for large datasets, plus emergency mitigation and long-term governance practices.
A production incident where core API latency spiked from 50ms to 30s+ due to connection leaks and exhausted MySQL max_connections is dissected, revealing how default HikariCP settings become time bombs under load and how to build a defense system with leak detection, parameter tuning, slow SQL interception, and kill mechanisms.
Faced with massive MyBatis log files that made manual slow‑SQL hunting impossible, the author designed a SpringBoot‑Vue‑MySQL system that parses logs with multithreaded batch processing, flexible regex templates, real‑time performance monitoring, and virtual‑scroll UI, achieving 55 000 lines/s throughput and over 95% matching accuracy.
This article provides a detailed walkthrough of JD’s open‑source sql‑analysis component, dissecting its eight functional modules, MyBatis interceptor flow, SQL extraction logic, query‑plan analysis, rule‑based scoring, and output strategies, while highlighting design patterns and potential extension points for developers.
This article introduces JD’s open‑source sql‑analysis component, explains its design based on a MyBatis interceptor, demonstrates how it analyzes SQL execution plans with Explain and a rule engine to warn about potential slow queries, and shows step‑by‑step usage and its advantages for early detection and rapid hot‑swap remediation.
A detailed post‑mortem of a three‑time service outage reveals how hidden bugs, frequent FullGC, a saturated connection pool, and an unindexed slow SQL query crippled a Spring Boot backend, and shows the step‑by‑step troubleshooting, temporary fixes, and lasting improvements applied.
The article describes a high‑traffic core application with a MySQL master‑slave setup facing high resource usage; it details analysis of hardware, disk, table space, QPS, slow SQL, and presents governance actions including data archiving, moving reads to replicas, a MyBatis interceptor, and monitoring scripts, achieving significant performance improvements.
During a Monday incident where the backend service became unavailable three times, the author details step-by-step investigations—checking frontend responses, container status, JVM and thread pool metrics, and database connection pool usage—ultimately identifying a slow, unindexed SQL query that exhausted connections, and describes the remediation and lessons learned.
This article details a multi‑phase slow‑SQL governance initiative that defines clear goals, metrics, and operational steps—from data preparation and ticket flow to trend analysis and process tracking—culminating in measurable improvements in system stability and performance.
A detailed postmortem shows how a poorly optimized SQL query, triggered by a cache‑removal update, saturated MySQL's CPU and connection pool, causing cascading failures across a sales‑critical system despite low overall traffic.
During nightly peaks, a social‑e‑commerce startup experienced hour‑long service outages due to MySQL timeouts; by analyzing traffic spikes, CPU usage, and slow‑SQL logs, the team identified un‑cached ranking queries and a 20‑minute cache refresh bottleneck, then implemented targeted caching, monitoring scripts, and fallback static pages to eliminate the issue.
This article shares practical collaboration strategies through real‑world cases, explaining why framing proposals around others' benefits, identifying the right partners, and aligning mutual goals can turn complex technical challenges—like slow‑SQL governance and barcode‑scale integration—into successful joint projects.
This article presents a detailed investigation of intermittent slow SQL queries observed in Meituan‑Dianping’s services, identifies the MySQL 5.6 thread‑pool as the primary cause, and demonstrates how adjusting thread‑pool parameters dramatically reduced slow‑query counts and improved overall service availability.
