The MySQL Timestamp Trap: Why Your TIMESTAMP Field Is Auto-Updating and How to Fix It
Noticed your MySQL 5.7 `TIMESTAMP` field automatically changes to the current time on every update? This isn't a bug, but an implicit feature that often leads to data corruption. This article dives into the root cause, reveals the significant risks to your business data, and provides the best practice solution of changing the column type to `DATETIME` to ensure data integrity and system robustness. This post is especially valuable for developers working on projects like wiki.lib00.com facing similar issues.
MySQL Masterclass: How to Set a Custom Starting Value for AUTO_INCREMENT IDs
By default, MySQL auto-incrementing IDs start at 1. However, sometimes we need to reserve a specific range for IDs, for instance, starting from 101. This article provides a deep dive into setting a custom starting value for an `AUTO_INCREMENT` column, both when creating a new table (using DDL) and modifying an existing one (using ALTER TABLE). We offer clear code examples and, from the perspective of architect DP, analyze common scenarios and best practices for reserving IDs to help you build more robust and scalable database models.
Beyond Simple Counters: How to Design a Professional PV/UV Tracking System for Your Website
Struggling with how to efficiently track daily Page Views (PV) and Unique Visitors (UV) in your database? A simple `UPDATE table SET pv = pv + 1` quickly becomes a performance bottleneck. This article dives into a professional and scalable design for a PV/UV tracking system, covering everything from a fundamental two-tier table architecture to privacy-compliant IP hashing and extracting business value from User-Agents, helping you build a high-performance, data-rich analytics system.
MySQL TIMESTAMP vs. DATETIME: The Ultimate Showdown on Time Zones, UTC, and Storage
Ever been confused by TIMESTAMP and DATETIME in MySQL? This article dives deep into why a TIMESTAMP column can be directly compared with a date string, uncovering the magic of implicit type casting. We'll reveal how TIMESTAMP handles time zones—storing in UTC and retrieving in the session's time zone—and explain its interaction with applications like PHP. Finally, through a detailed comparison and architectural advice from DP@lib00, you'll master when to use TIMESTAMP versus DATETIME, enabling you to design more robust and globally-aware database schemas.
MySQL PV Log Table Optimization: A Deep Dive into Slashing Storage Costs by 73%
How do you design a high-performance, cost-effective MySQL table for 100,000 daily page views? This article provides a deep dive into a real-world PV log table case study, analyzing the complete optimization process from field selection and indexing strategies to partitioning. This approach is crucial for systems handling large volumes of log data, like the analytics module at wiki.lib00.com, ultimately achieving over a 73% reduction in storage and a significant boost in write performance.
MySQL NULL vs. 0: Which Saves More Space? A Deep Dive with a Billion Rows
In MySQL database design, should you use NULL or 0 to represent 'no value'? This is a classic debate. This article provides a deep dive into the storage space differences between an `INT` field with a NULL value versus a 0, using a one-billion-row case study. You might be surprised to learn that using NULL can save you nearly 4GB of storage in certain scenarios. We will detail MySQL's internal mechanism for storing NULL values and offer trade-off advice regarding performance and query efficiency to help you make optimal design decisions.
Building a Bulletproof PHP Analytics System: From DB Schema to Self-Healing Cron Jobs
This article provides a comprehensive walkthrough of building an accurate and robust website analytics system. Starting with the common problem of duplicate sitewide UV counts, we design a scalable database schema and iteratively develop an efficient PHP statistics script. Key topics include performance optimization via in-memory processing, early filtering of bot traffic, and designing a fault-tolerant cron job that automatically backfills missing data. This serves as a complete practical guide for creating a reliable data analysis system.