A public account focused on workplace, career growth, team management, and self-improvement. The author is the writer of books including 'SpringBoot Technology Insider' and 'Drools 8 Rule Engine: Core Technology and Practice'.
This article provides a detailed overview of MySQL’s four‑layer architecture—including the client, server, storage engine, and system file layers—explaining each layer’s responsibilities, key modules, and the role of various built‑in and third‑party storage engines.
This article explains the concepts of driving and driven tables in MySQL JOIN queries, shows how the optimizer chooses their order based on data size, indexes and filters, provides concrete examples with EXPLAIN output, and offers practical tips to control and improve table selection for better performance.
This guide explains MySQL partitioning fundamentals, shows how to create RANGE, LIST, and KEY partitions with concrete CREATE TABLE examples, compares the performance benefits and maintenance trade‑offs, and clarifies the differences between partitioning and sharding to help you decide when to use each technique.
This article explains how MySQL indexes work, why wrapping indexed columns in functions can implicitly mask them, and how adding logical or domain‑knowledge‑based redundant conditions can unlock index usage to dramatically improve query efficiency.
This article explains why defining MySQL table columns as NOT NULL—unless business logic demands NULL—improves query speed, reduces storage overhead, enhances index efficiency, prevents aggregation distortion, simplifies application code, and strengthens data consistency, while also noting scenarios where NULL is appropriate.
This article compares PostgreSQL and MySQL, covering their definitions, core similarities, key differences in performance, scalability, features, ecosystem, and community, and provides practical guidance on selecting the right database for various project scenarios.
This article explains how MySQL's implicit type conversion during table joins can render indexes unusable or alter join order, and provides practical solutions such as aligning column types, using optimizer hints, and forcing indexes to restore query performance.
This article explores how MySQL decides whether queries with IS NULL or IS NOT NULL predicates can use an index, presenting three concrete examples with varying data sizes and NULL distributions, and explains the underlying storage of NULL values and optimizer cost decisions.
This article explains the five MySQL temporal column types—DATE, DATETIME, TIMESTAMP, YEAR, and TIME—detailing their storage size, valid ranges, typical use‑cases, timezone behavior, and the 2038 problem, helping developers pick the most suitable type for any scenario.
This article explains how MySQL's OR conditions can cause index loss, provides concrete query examples, analyzes why the optimizer falls back to full table scans, and offers practical solutions such as rewriting with UNION or adding missing indexes to restore efficient index usage.
