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 explains why selecting only needed columns and ensuring deterministic ordering are essential for MySQL queries, then compares Offset/Limit pagination with cursor‑based pagination, detailing their syntax, advantages, drawbacks such as data drift and performance issues, and offers practical optimization tips.
This article explains how to verify whether MySQL uses an index with EXPLAIN, outlines eight common reasons why an index may be ignored—including better alternatives, low selectivity, stale statistics, full‑table scans, structural limitations, function usage, invisible indexes—and provides practical commands and hints to resolve each issue.
Index Condition Pushdown (ICP) in MySQL pushes filter conditions to the storage engine, dramatically cutting data transferred to the server layer, speeding up queries especially when using composite indexes, and requiring no changes to the original SQL statements.
This article explains the concept of table lookups in MySQL, shows how they arise from using secondary indexes, provides concrete query examples, and offers practical optimization techniques such as creating covering indexes, reducing selected columns, and analyzing execution plans to improve performance.
Understanding MySQL's clustered indexes—including their definition, selection rules, customization via primary key design, practical creation examples, and key design considerations—helps developers optimize query performance and storage efficiency in InnoDB tables for various workloads.
This article provides a comprehensive review of MySQL’s two primary index types—clustered (clustered index) and non‑clustered (non‑clustered index)—explaining their storage mechanisms, performance trade‑offs, typical use cases, and best‑practice guidelines for selecting the appropriate index in database design.
Learn how to leverage MySQL's EXPLAIN and EXPLAIN ANALYZE commands to diagnose query performance, understand each column of the output, choose appropriate indexes, and apply practical optimization steps—including multi‑column indexes—to dramatically reduce row scans and speed up queries.
This article explains how indexes boost query speed but also incur storage, write‑performance, and maintenance costs, offering practical SQL scripts and guidelines for auditing, testing, and safely removing unnecessary indexes.
This article explains the N+1 query performance issue, demonstrates a naïve Python/SQLite implementation that triggers N+1 queries, compares its runtime, and then shows how using SQL JOINs, GROUP BY, and nested data structures can dramatically improve query efficiency and reduce latency.
This guide walks through MySQL's join operations—inner, left, right, and full outer—using a simple grocery‑items schema, showing how to create tables, write correct queries, avoid common pitfalls like unintended cross joins, apply aliases, and filter unassociated rows with WHERE and UNION.
