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The article explains MySQL's Index Merge optimization, detailing its three types—Intersection, Union, and Sort‑Union—when it is beneficial, how to design indexes and rewrite queries for better performance, and the associated costs and limitations.
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This article examines MySQL's recommendation against UUID primary keys by creating three tables with different key strategies, running large‑scale insert tests using Spring JdbcTemplate, and analyzing the resulting performance, index behavior, and trade‑offs of auto‑increment, UUID, and random keys.
This article investigates MySQL's recommendation to avoid UUID or random Snowflake IDs as primary keys, comparing auto‑increment, UUID, and random long keys through Java/JDBC performance tests, analyzing their insertion speed, index structure impact, and the trade‑offs of each approach.
Learn how to identify and resolve extreme CPU usage spikes—up to 900%—in MySQL and Java applications by using top, show processlist, indexing, caching, thread analysis, and code adjustments, with real‑world examples and step‑by‑step command guides.
This article provides comprehensive guidance on effective database indexing, covering when and how to create various index types, practical SQL examples, strategies for equality, range, fuzzy, join, and composite queries, and tips for verifying index usage with EXPLAIN.
This article explains the purpose and inner workings of various database indexing algorithms—including B‑Tree, Hash, Bitmap, and Full‑Text indexes—illustrates their strengths and weaknesses with SQL examples, and provides guidance on when to choose each type for optimal query performance.
This comprehensive guide covers high‑performance development techniques—including I/O optimization, zero‑copy, multiplexing, concurrency, thread‑pool design, lock‑free programming, inter‑process communication, RPC, serialization, database indexing, caching strategies, Bloom filters, full‑text search, and load balancing—to help developers build fast, scalable, and reliable systems.
This article provides a comprehensive overview of B‑tree, B+‑tree, B*‑tree and R‑tree data structures, explaining their definitions, node layouts, height analysis, insertion and deletion algorithms with examples, and their roles in external‑memory indexing for databases and file systems.
This article explains how to leverage MySQL 5.7's built‑in ngram full‑text parser to implement lightweight Chinese full‑text search, covering configuration, index creation, query modes, operator usage, and performance considerations.
This article explains the fundamentals of B‑Tree and B+Tree data structures, their search algorithms, and how MySQL's MyISAM and InnoDB storage engines implement these indexes to achieve efficient disk‑based query performance.
This article explains the evolution of tree-based index structures—from basic binary search trees through AVL and red‑black trees to B‑trees and B+‑trees—highlighting their trade‑offs and why MySQL adopts B+‑trees for efficient disk‑based indexing.
This article demonstrates how creating a covering composite index on MySQL tables can reduce a 55‑second aggregation query on five million rows to about two seconds by eliminating the need for row lookups and fully utilizing index data.
This article presents a comprehensive set of MySQL optimization guidelines, covering the avoidance of SELECT *, proper use of specific columns, eliminating OR and != in WHERE clauses, preferring numeric types, choosing VARCHAR over CHAR, using TRUNCATE, batch operations, index design, join selection, GROUP BY efficiency, and other practical tips to improve query performance.
This article explains the value of short URLs, the HTTP redirection principle behind them, and provides detailed design and implementation strategies—including hash‑based and distributed‑ID approaches, base‑62 encoding, database storage, caching, indexing, and security measures—to build a scalable short‑link service.
The article explains why using LIMIT together with ORDER BY in MySQL 5.6 can cause duplicate records on subsequent pages, analyzes the priority‑queue optimization that makes the sort unstable, and offers practical solutions such as indexing, proper pagination logic, and query adjustments.
This article explains the fundamentals of B‑Tree and B+Tree data structures, covering their definitions, differences from red‑black trees, node properties, and detailed insertion procedures, while highlighting why B+Tree is preferred for database and file indexing.
This article explains why MySQL's default full‑text index struggles with Chinese, demonstrates how to configure token size parameters, activate the ngram parser plugin, and adjust queries (including Boolean mode) to achieve reliable Chinese full‑text search results.
This article explains InnoDB's storage hierarchy (sector, block, page), calculates how many rows fit in a 16KB page, shows how B+‑tree height and pointer counts determine total record capacity, and demonstrates the I/O cost of primary and secondary index lookups using practical MySQL commands.