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Aikesheng Open Source Community
Aikesheng Open Source Community
May 11, 2022 · Databases

Using Hash Partitioning in MySQL: Scenarios, Queries, and Optimizations

This article explains MySQL hash partition tables, illustrating their suitable use cases such as equality queries on IDs or dates, demonstrating creation, data loading, and query plans, and comparing standard hash partitions with linear hash partitions to highlight performance and data distribution considerations.

Database Optimizationhash partitionmysql
0 likes · 13 min read
Using Hash Partitioning in MySQL: Scenarios, Queries, and Optimizations
Aikesheng Open Source Community
Aikesheng Open Source Community
May 6, 2022 · Databases

Analysis of MySQL Backup Blocking Issues and Optimization Strategies

The article investigates a production MySQL outage caused by FLUSH NO_WRITE_TO_BINLOG TABLES blocking during backups, presents three experimental scenarios to identify the root cause, and offers practical recommendations such as setting query timeouts, adding indexes, and using Percona XtraBackup options to avoid backup stalls.

Database OptimizationPercona XtraBackupflush tables
0 likes · 19 min read
Analysis of MySQL Backup Blocking Issues and Optimization Strategies
Java Backend Technology
Java Backend Technology
May 1, 2022 · Databases

Mastering Database Performance: 8 Proven Optimization Strategies

This article explains why databases become slow, introduces a four‑layer thinking model, and presents eight practical solutions—including reducing data volume, leveraging space for performance, and selecting the right storage system—to help backend engineers resolve 80‑90% of common performance problems.

CQRSDatabase OptimizationNoSQL
0 likes · 19 min read
Mastering Database Performance: 8 Proven Optimization Strategies
Meituan Technology Team
Meituan Technology Team
Apr 21, 2022 · Databases

Meituan's Cost-Based Optimizer for Slow Query Index Recommendation

The article explains how Meituan uses MySQL's cost‑based optimizer to analyze slow queries, generate virtual index candidates, evaluate their costs with detailed statistics, and deploy a recommendation system that validates, tracks, and governs index suggestions to reduce CPU/IO waste and prevent database failures.

Cost ModelDatabase OptimizationFakeindex
0 likes · 22 min read
Meituan's Cost-Based Optimizer for Slow Query Index Recommendation
Top Architect
Top Architect
Apr 19, 2022 · Databases

Querying Multi‑Business‑Unit Product Sales with Row Comparison in MySQL

This article explains how to retrieve sales statistics for multiple business units and their associated products in MySQL by comparing rows, discusses alternative approaches such as loop queries, OR concatenation, and mixed filtering, and demonstrates why row‑by‑row comparison is the most suitable solution.

Backend DevelopmentDatabase OptimizationDynamic SQL
0 likes · 8 min read
Querying Multi‑Business‑Unit Product Sales with Row Comparison in MySQL
ITPUB
ITPUB
Apr 14, 2022 · Databases

Eight Proven Strategies to Supercharge Database Performance

This article explains why databases become slow, introduces a four‑layer thinking model, and presents eight practical optimization techniques—including data reduction, caching, sharding, master‑slave replication, and CQRS—along with their benefits, drawbacks, and suitable scenarios.

CQRSDatabase OptimizationNoSQL
0 likes · 22 min read
Eight Proven Strategies to Supercharge Database Performance
Java Interview Crash Guide
Java Interview Crash Guide
Apr 1, 2022 · Databases

Why MySQL Uses B+ Trees Over B Trees: Deep Dive into Index Structures

Explore MySQL's comprehensive index guide, covering basic concepts, B‑tree and B+‑tree structures, storage engine differences, index types, optimization strategies, and practical tips for designing effective primary, secondary, and composite indexes to boost query performance and reduce I/O overhead.

B+TreeDatabase OptimizationInnoDB
0 likes · 35 min read
Why MySQL Uses B+ Trees Over B Trees: Deep Dive into Index Structures
Laravel Tech Community
Laravel Tech Community
Mar 31, 2022 · Databases

SQL Optimization Steps and Common Cases for Improving Query Performance

This article outlines a systematic approach to identifying and fixing slow MySQL queries, explains how to interpret EXPLAIN output and profiling information, and presents multiple real‑world cases illustrating index usage, implicit conversion, large pagination, IN queries, and other optimization techniques.

Database OptimizationExplain PlanSQL
0 likes · 10 min read
SQL Optimization Steps and Common Cases for Improving Query Performance
Architect
Architect
Mar 29, 2022 · Backend Development

Design and Implementation of Baidu's Product Promotion System

This article details the architecture, core services, user interfaces, and technical challenges of Baidu's product promotion system, explaining the roles of traffic owners and advertisers, the CPS billing model, dynamic library reporting, and database batch‑write optimizations for high‑throughput e‑commerce scenarios.

Backend ArchitectureBaiduCPS
0 likes · 17 min read
Design and Implementation of Baidu's Product Promotion System
政采云技术
政采云技术
Mar 29, 2022 · Databases

Performance Comparison of Different Batch Insert Strategies in MySQL

This article evaluates single‑threaded bulk‑insert performance in MySQL by testing various batch sizes, analyzes memory usage and transaction merging, and provides practical recommendations for efficiently generating millions of records.

Bulk InsertDatabase OptimizationPerformance Testing
0 likes · 11 min read
Performance Comparison of Different Batch Insert Strategies in MySQL
Top Architect
Top Architect
Mar 14, 2022 · Databases

Implementing Multi‑Business‑Unit Sales Queries with SQL Row‑Comparison in MySQL

This article explains how to design a MySQL table for product sales statistics and compares several query strategies—including loop queries, OR concatenation, mixed filtering, and the SQL‑92 row‑comparison technique—to efficiently retrieve sales data for multiple business units and their associated products in a single indexed query.

Database OptimizationDynamic SQLMyBatis
0 likes · 7 min read
Implementing Multi‑Business‑Unit Sales Queries with SQL Row‑Comparison in MySQL
Aikesheng Open Source Community
Aikesheng Open Source Community
Feb 9, 2022 · Databases

Performance Evaluation of Parallel DDL in MySQL 8.0.27

This article investigates how the innodb_ddl_threads, innodb_ddl_buffer_size, and innodb_parallel_read_threads variables introduced in MySQL 8.0.27 affect parallel DDL execution speed and resource consumption, using a 50‑million‑row test table and presenting detailed benchmark results.

Database OptimizationInnoDBParallel DDL
0 likes · 7 min read
Performance Evaluation of Parallel DDL in MySQL 8.0.27
Tencent Cloud Developer
Tencent Cloud Developer
Jan 13, 2022 · Backend Development

Strategies for Ensuring Cache Consistency in Distributed Systems

The article reviews major cache‑consistency strategies—Cache‑Aside, Read‑Through, Write‑Through, and Write‑Behind—detailing their performance and consistency trade‑offs, discusses compensation techniques such as delayed double‑delete and MySQL binlog‑based incremental parsing (DTS) for reliable deletion and HA, and advises selecting the appropriate approach based on specific business requirements.

Cache ConsistencyDatabase OptimizationDistributed Systems
0 likes · 15 min read
Strategies for Ensuring Cache Consistency in Distributed Systems
dbaplus Community
dbaplus Community
Dec 26, 2021 · Databases

Boost Database Performance: 4 Key Optimization Strategies from Architecture to SQL

From architecture tweaks like distributed caching and read‑write separation to hardware upgrades, DB instance tuning, and concrete SQL refactoring, this guide walks through four optimization layers, illustrates each with diagrams and a full‑scale MySQL case study, and shows how performance can improve up to twentyfold.

Database OptimizationHardwareSQL Tuning
0 likes · 13 min read
Boost Database Performance: 4 Key Optimization Strategies from Architecture to SQL
Java Interview Crash Guide
Java Interview Crash Guide
Dec 24, 2021 · Fundamentals

How Bloom, Counting, and Cuckoo Filters Optimize Database I/O

This article explains how Bloom filters, counting Bloom filters, and Cuckoo filters work, their advantages and limitations, and how they can be used to reduce unnecessary database I/O by efficiently testing element membership before querying the database.

Cuckoo FilterData StructuresDatabase Optimization
0 likes · 11 min read
How Bloom, Counting, and Cuckoo Filters Optimize Database I/O
Senior Brother's Insights
Senior Brother's Insights
Dec 21, 2021 · Databases

9 Essential MySQL Optimization Techniques to Boost Performance

This article presents practical MySQL optimization methods—including proper column definitions, NOT NULL usage, JOIN over sub‑queries, UNION, transaction handling, foreign keys, table locking, indexing strategies, and a collection of query‑tuning tips—each illustrated with clear examples and code snippets to improve database speed and reliability.

Database OptimizationSQLTransactions
0 likes · 18 min read
9 Essential MySQL Optimization Techniques to Boost Performance
DeWu Technology
DeWu Technology
Dec 21, 2021 · Backend Development

Performance Optimization: From Understanding to Practice

The article guides readers from grasping hardware, OS, and software layers—including Intel Xeon, virtualization, VPC, and containers—to gathering performance data with tools like JProfiler and perf, then applying data‑driven optimization across business logic, architecture, code, caching, databases, runtime and hardware, illustrated by real‑world case studies and emphasizing continual learning.

Backend DevelopmentContainer TechnologiesDatabase Optimization
0 likes · 43 min read
Performance Optimization: From Understanding to Practice
dbaplus Community
dbaplus Community
Dec 12, 2021 · Databases

7 Common MySQL Index Pitfalls That Can Kill Query Performance

This article examines seven typical scenarios where MySQL indexes unexpectedly fail—such as OR conditions, leading wildcards in LIKE, missing quotes, functions on indexed columns, NULL checks, arithmetic operations, and composite index ordering—providing SQL examples, execution plans, and practical tips to avoid costly full‑table scans.

Database OptimizationQuery TuningSQL
0 likes · 9 min read
7 Common MySQL Index Pitfalls That Can Kill Query Performance
dbaplus Community
dbaplus Community
Nov 28, 2021 · Databases

Mastering MySQL Indexes: When to Use, Combine, and Optimize Them

This article explains why indexes are vital for MySQL performance, how to decide when to add ordinary, composite, prefix, or unique indexes, the pitfalls of using non‑sequential primary keys, and advanced optimizations such as change buffer, index condition pushdown, and MRR to reduce I/O.

B+TreeDatabase OptimizationSQL
0 likes · 18 min read
Mastering MySQL Indexes: When to Use, Combine, and Optimize Them
macrozheng
macrozheng
Nov 26, 2021 · Databases

7 Common MySQL Index Pitfalls and How to Avoid Them

This article examines seven typical scenarios where MySQL indexes fail—such as OR conditions, leading wildcards, missing quotes, functions, NULL checks, arithmetic on indexed columns, and composite index order—explaining why they happen and offering practical solutions to maintain query performance.

Database OptimizationSQLindex
0 likes · 12 min read
7 Common MySQL Index Pitfalls and How to Avoid Them
Big Data Technology Architecture
Big Data Technology Architecture
Nov 16, 2021 · Databases

ByteHouse: ClickHouse Enterprise Edition Case Studies and Optimizations at ByteDance

ByteDance’s ByteHouse, a ClickHouse enterprise edition, showcases large‑scale real‑time analytics through two detailed case studies—recommendation system metrics and ad‑delivery data—detailing technical selection, challenges, multi‑threaded Kafka Engine, async indexing, buffer engine enhancements, and the resulting performance gains.

Big DataByteHouseClickHouse
0 likes · 10 min read
ByteHouse: ClickHouse Enterprise Edition Case Studies and Optimizations at ByteDance
Java Architect Essentials
Java Architect Essentials
Nov 15, 2021 · Databases

MySQL Optimization: Concepts, Schema Design, Indexes, and Query Tuning

This article provides a comprehensive overview of MySQL fundamentals—including logical architecture, locks, transactions, and storage engines—and offers practical optimization strategies for schema design, data types, indexing, and query execution, supplemented with code examples and performance‑analysis tips.

Database OptimizationQuery TuningTransactions
0 likes · 14 min read
MySQL Optimization: Concepts, Schema Design, Indexes, and Query Tuning
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 5, 2021 · Databases

How PolarDB MySQL’s In‑Memory Column Index Supercharges HTAP Performance

This article explains how PolarDB MySQL introduces an In‑Memory Column Index (IMCI) to combine row‑store OLTP strength with column‑store analytical speed, detailing the architectural innovations, optimizer decisions, data organization, resource isolation strategies, and benchmark results that show IMCI achieving tens to hundreds of times faster query execution than native MySQL and matching ClickHouse performance.

Column StoreDatabase OptimizationHTAP
0 likes · 32 min read
How PolarDB MySQL’s In‑Memory Column Index Supercharges HTAP Performance
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 25, 2021 · Databases

How PolarDB’s In-Memory Column Index Turns MySQL into a High‑Performance HTAP Engine

This article explores PolarDB MySQL’s In‑Memory Column Index (IMCI) technology, detailing its hybrid row‑column storage architecture, optimizer enhancements, parallel execution engine, and performance gains that enable real‑time analytical queries alongside OLTP workloads, and compares its benchmarks against MySQL and ClickHouse.

Column StoreDatabase OptimizationHTAP
0 likes · 32 min read
How PolarDB’s In-Memory Column Index Turns MySQL into a High‑Performance HTAP Engine
Architect's Tech Stack
Architect's Tech Stack
Oct 20, 2021 · Databases

MySQL Performance Optimization: Data Volume, Concurrency, Query Time, Table Design, Index and SQL Tuning

This article presents a comprehensive guide to MySQL performance, covering maximum data volume and concurrency limits, recommended query response times, practical table‑design rules, index classification and optimization techniques, as well as detailed SQL tuning patterns such as batch processing, operator, OR, IN, LIKE, JOIN and LIMIT improvements.

Database OptimizationSQL Tuningdata modeling
0 likes · 15 min read
MySQL Performance Optimization: Data Volume, Concurrency, Query Time, Table Design, Index and SQL Tuning
Python Crawling & Data Mining
Python Crawling & Data Mining
Sep 12, 2021 · Databases

How ClickHouse Projections Supercharge Query Performance

The article explains ClickHouse's new Projection feature, how it overcomes MergeTree's single‑sort limitation and materialized view drawbacks, provides step‑by‑step commands to create, materialize, and query projections, demonstrates massive performance gains, and outlines the rules for automatic projection selection.

ClickHouseDatabase OptimizationProjection
0 likes · 12 min read
How ClickHouse Projections Supercharge Query Performance
Architecture Digest
Architecture Digest
Sep 8, 2021 · Databases

Why Optimize Slow SQL and Practical MySQL Performance Tuning Techniques

This article explains the impact of slow SQL on database resources and user experience, outlines priority rules for addressing slow queries, details MySQL execution steps, identifies key performance factors, and provides concrete optimization methods including enabling slow‑query logs, indexing, I/O merging, and distributed architecture.

Database OptimizationSQLmysql
0 likes · 17 min read
Why Optimize Slow SQL and Practical MySQL Performance Tuning Techniques
Kuaishou Tech
Kuaishou Tech
Aug 30, 2021 · Databases

ClickHouse Projection: Design, Implementation, and Production Performance

This article presents an in‑depth overview of ClickHouse Projection, covering its background, definition, practical use cases, underlying architecture, query analysis, consistency guarantees, performance comparisons, and real‑world production results, highlighting how it enhances OLAP workloads while maintaining strong data consistency.

ClickHouseDatabase OptimizationMaterialized Views
0 likes · 19 min read
ClickHouse Projection: Design, Implementation, and Production Performance
FunTester
FunTester
Aug 20, 2021 · Databases

Why Is One MySQL CPU Core at 99%? A Step‑by‑Step Troubleshooting Guide

During a performance test a MySQL server showed one CPU core constantly at 99% while the others were idle, prompting a detailed investigation that checks I/O thread settings, multi‑core utilization, transaction locks, slow‑query logging, and index optimization to resolve the bottleneck.

Database OptimizationInnoDBSQL
0 likes · 6 min read
Why Is One MySQL CPU Core at 99%? A Step‑by‑Step Troubleshooting Guide
Python Programming Learning Circle
Python Programming Learning Circle
Aug 12, 2021 · Databases

Understanding MySQL Slow Queries, Index Optimization, ElasticSearch Basics, and HBase Overview

This article explains why MySQL queries become slow, how proper indexing—including B+‑tree, left‑most prefix, index push‑down, and covering indexes—can improve performance, outlines common causes of index failure, and then introduces ElasticSearch search capabilities and HBase column‑family storage as complementary solutions for large‑scale data handling.

Database OptimizationElasticsearchHBase
0 likes · 16 min read
Understanding MySQL Slow Queries, Index Optimization, ElasticSearch Basics, and HBase Overview
Programmer DD
Programmer DD
Aug 3, 2021 · Databases

Why MySQL Uses B+ Trees for Indexes and How to Design Effective Indexes

This article explains why MySQL chooses B+ trees for its indexes, covers the left‑most prefix rule for composite indexes, offers practical index‑design tips, discusses MyBatis caching, master‑slave replication, and sharding strategies for large‑scale databases.

B+TreeDatabase OptimizationMyBatis
0 likes · 10 min read
Why MySQL Uses B+ Trees for Indexes and How to Design Effective Indexes
Selected Java Interview Questions
Selected Java Interview Questions
Aug 2, 2021 · Databases

Why Store IPv4 Addresses as UNSIGNED INT in MySQL: Benefits, Drawbacks, and Conversion Methods

Storing IPv4 addresses as a 32‑bit UNSIGNED INT in MySQL saves space, enables faster range queries, and leverages built‑in conversion functions like INET_ATON/INET_NTOA, while requiring manual readability handling, and can be complemented by Java utilities for application‑level conversions.

Database OptimizationINET_ATONIPv4
0 likes · 5 min read
Why Store IPv4 Addresses as UNSIGNED INT in MySQL: Benefits, Drawbacks, and Conversion Methods
Open Source Linux
Open Source Linux
Aug 1, 2021 · Databases

Why Is MySQL Consuming CPU? Identify and Reduce CPU Bottlenecks

This article explains which components (user processes, IO wait, system interrupts) consume CPU in MySQL, shows their impact on performance, and provides practical strategies to reduce CPU usage through IO optimization, query tuning, data modeling, caching, and hardware upgrades.

CPU BottleneckDatabase OptimizationIO Wait
0 likes · 6 min read
Why Is MySQL Consuming CPU? Identify and Reduce CPU Bottlenecks
MaGe Linux Operations
MaGe Linux Operations
Jul 29, 2021 · Databases

How to Efficiently Remove Duplicate Rows in Large MySQL Tables

This article explains why a naïve Python script for deduplicating millions of rows is too slow, then walks through a series of MySQL queries—including how to identify duplicate names, avoid the 1093 error, and delete duplicates while keeping a single representative row—demonstrating fast, reliable cleanup of large tables.

Database OptimizationSQLdata cleaning
0 likes · 5 min read
How to Efficiently Remove Duplicate Rows in Large MySQL Tables
Python Crawling & Data Mining
Python Crawling & Data Mining
Jul 18, 2021 · Databases

How Indexing Can Slash Oracle Query Time from Minutes to Seconds

This article examines a real‑world Oracle SQL query, identifies costly full‑table scans and low‑selectivity columns, and demonstrates how creating an index on a key column reduces execution time from 24 minutes to just one second, highlighting essential SQL performance‑tuning techniques.

AWRDatabase OptimizationOracle
0 likes · 7 min read
How Indexing Can Slash Oracle Query Time from Minutes to Seconds
Java Captain
Java Captain
Jul 17, 2021 · Databases

Optimizing Existence Checks: Use SELECT 1 LIMIT 1 Instead of SELECT count(*)

Developers often use SELECT count(*) to check record existence, but replacing it with SELECT 1 … LIMIT 1 improves performance by stopping after the first match, allowing simpler Java null checks and potentially reducing index usage, especially when only a binary presence test is needed.

Database OptimizationExistence CheckJava
0 likes · 3 min read
Optimizing Existence Checks: Use SELECT 1 LIMIT 1 Instead of SELECT count(*)
macrozheng
macrozheng
Jul 12, 2021 · Backend Development

50+ Proven Tips to Slash Bugs in Your Backend Development

This article compiles over fifty practical tips covering database design, code practices, and cache usage to help developers dramatically reduce bugs, improve reliability, and boost overall software quality in everyday backend projects.

Cache StrategyDatabase Optimizationbug reduction
0 likes · 30 min read
50+ Proven Tips to Slash Bugs in Your Backend Development
Java Architect Essentials
Java Architect Essentials
Jun 21, 2021 · Databases

Understanding MySQL Slow Queries, Index Optimization, and Integration with Elasticsearch and HBase

This article explains why MySQL queries become slow, how index design and common pitfalls affect performance, introduces MDL locks and large‑table strategies, then compares Elasticsearch and HBase as complementary storage and search solutions, providing practical code examples and best‑practice recommendations.

Database OptimizationHBaseindexing
0 likes · 16 min read
Understanding MySQL Slow Queries, Index Optimization, and Integration with Elasticsearch and HBase
IT Xianyu
IT Xianyu
Jun 1, 2021 · Databases

Improving MySQL Insert Performance with Multithreading, Prepared Statements, and Batch Transactions

The article explains why multithreaded inserts can be faster than single‑threaded ones in MySQL, breaks down the time spent on each step of an insert operation, and presents practical techniques such as using PreparedStatement, multi‑value INSERT statements, and transaction batching to dramatically reduce insertion time.

Batch TransactionDatabase OptimizationInsert Performance
0 likes · 6 min read
Improving MySQL Insert Performance with Multithreading, Prepared Statements, and Batch Transactions
Top Architect
Top Architect
May 31, 2021 · Databases

How to Achieve Fast Queries: MySQL Index Optimization, Large‑Table Strategies, Elasticsearch Basics, and HBase Overview

This article explains common causes of slow MySQL queries, how proper indexing and lock handling can improve performance, introduces Elasticsearch’s inverted‑index advantages and suitable use cases, and outlines HBase’s column‑family storage model and row‑key design for large‑scale data.

Big DataDatabase OptimizationHBase
0 likes · 18 min read
How to Achieve Fast Queries: MySQL Index Optimization, Large‑Table Strategies, Elasticsearch Basics, and HBase Overview
Programmer DD
Programmer DD
May 22, 2021 · Databases

Master MySQL Indexes: B+Tree Deep Dive & Optimization Tips

This article explains MySQL's B‑Tree index fundamentals, compares MyISAM and InnoDB implementations, outlines how B+Tree structures work, and provides practical guidelines for designing effective indexes and tuning MySQL configuration to boost query performance.

B+TreeDatabase OptimizationInnoDB
0 likes · 27 min read
Master MySQL Indexes: B+Tree Deep Dive & Optimization Tips
php Courses
php Courses
May 19, 2021 · Databases

Fundamentals of Relational Databases: Key Concepts and Common Questions

This article provides a comprehensive overview of relational database fundamentals, covering common DBMS products, SQL language components, integrity constraints, transactions, locking, views, stored procedures, indexes, normalization, key differences, constraints, optimization techniques, storage engines, and performance strategies for high‑traffic sites.

Database OptimizationRelational DatabaseTransactions
0 likes · 12 min read
Fundamentals of Relational Databases: Key Concepts and Common Questions
Full-Stack Internet Architecture
Full-Stack Internet Architecture
May 10, 2021 · Databases

MySQL Index Design Principles and Common Index Pitfalls

This article explains MySQL index fundamentals, covering primary and unique indexes, best practices for choosing indexed columns, handling functions and large fields, avoiding excessive or frequently updated indexes, and enumerates typical scenarios where indexes become ineffective.

Database OptimizationSQLindex design
0 likes · 12 min read
MySQL Index Design Principles and Common Index Pitfalls
Java Interview Crash Guide
Java Interview Crash Guide
May 10, 2021 · Databases

Master MySQL Indexes: From B‑Tree to Hash and When to Use Them

This article explains MySQL indexing fundamentals, covering index types, underlying data structures such as B‑Tree and Hash, the differences between clustered and non‑clustered indexes, practical performance tips, and advanced features like adaptive hash indexes and index condition pushdown.

B-TreeDatabase OptimizationHash Index
0 likes · 26 min read
Master MySQL Indexes: From B‑Tree to Hash and When to Use Them
ITPUB
ITPUB
Apr 30, 2021 · Databases

How Index Pushdown Cuts Unnecessary Table Lookups in MySQL

This article explains MySQL's table‑lookup (回表) process, the difference between primary‑key and secondary indexes, and how the index‑pushdown feature introduced in MySQL 5.6 reduces unnecessary lookups by filtering rows directly in the index.

Database OptimizationIndex PushdownInnoDB
0 likes · 7 min read
How Index Pushdown Cuts Unnecessary Table Lookups in MySQL
Programmer DD
Programmer DD
Apr 29, 2021 · Databases

Loading 2 Billion Rows into MySQL Fast with TokuDB – 570k Rows/s

This article details a real‑world test of loading over 200 million rows into MySQL using XeLabs TokuDB, showing configuration tweaks, bulk‑loader commands, performance metrics (≈570 k rows per second), file‑size reductions, and comparisons with InnoDB under a 8‑core, 8 GB RAM, 500 GB SSD environment.

Database OptimizationLarge DataTokuDB
0 likes · 6 min read
Loading 2 Billion Rows into MySQL Fast with TokuDB – 570k Rows/s
Liangxu Linux
Liangxu Linux
Apr 20, 2021 · Databases

Master MySQL Indexes: From Fundamentals to B+ Tree Mechanics

This article explains the core principles of MySQL indexes, covering their essence, various types such as hash, binary, B‑tree and B+‑tree, the structure of primary key directories and index pages, clustered versus non‑clustered indexes, and the back‑table lookup process.

B+TreeDatabase OptimizationSQL
0 likes · 16 min read
Master MySQL Indexes: From Fundamentals to B+ Tree Mechanics
Top Architect
Top Architect
Apr 19, 2021 · Databases

Understanding MySQL Index Structures, B+ Trees, and Practical Optimization Techniques

This article explains why MySQL uses B+‑tree indexes, describes the left‑most prefix rule for composite indexes, offers practical index‑design and optimization tips, outlines MyBatis first‑ and second‑level caching, details master‑slave replication, and introduces common sharding strategies and their implementation considerations.

B+TreeDatabase OptimizationMyBatis
0 likes · 12 min read
Understanding MySQL Index Structures, B+ Trees, and Practical Optimization Techniques
Top Architect
Top Architect
Mar 24, 2021 · Databases

Understanding the Use of WHERE 1=1 in Dynamic SQL

The article explains why developers insert the clause "WHERE 1=1" in dynamically generated SQL statements, shows example Java code, discusses how it prevents syntax errors when concatenating AND conditions, and offers advice on adding selective filters and indexes to avoid full table scans.

Database OptimizationDynamic QuerySQL
0 likes · 3 min read
Understanding the Use of WHERE 1=1 in Dynamic SQL
360 Smart Cloud
360 Smart Cloud
Mar 19, 2021 · Databases

Root Cause Analysis and Performance Optimization of InfluxDB 1.8 Memory and Disk I/O on a Production Server

The article investigates why an InfluxDB 1.8 instance on a 32‑core, 64 GB production server consumes over 95% memory and generates heavy disk I/O, analyzes runtime statistics, pprof data, and Go memory‑release behavior, and presents configuration and runtime tweaks that reduce memory usage to ~55% and I/O load to acceptable levels.

Database OptimizationDisk I/OInfluxDB
0 likes · 12 min read
Root Cause Analysis and Performance Optimization of InfluxDB 1.8 Memory and Disk I/O on a Production Server
Wukong Talks Architecture
Wukong Talks Architecture
Mar 16, 2021 · Backend Development

Comprehensive Guide to Performance Testing and Monitoring with JMeter, JConsole, and JVisualVM

This article explains how to conduct stress testing using JMeter, monitor Java applications with jconsole and jvisualvm, optimize gateway and microservice performance, improve database query speed with indexing, and tune garbage collection by enlarging the Eden space, providing step‑by‑step instructions and results.

Database OptimizationJConsoleJMeter
0 likes · 14 min read
Comprehensive Guide to Performance Testing and Monitoring with JMeter, JConsole, and JVisualVM
Architect's Tech Stack
Architect's Tech Stack
Mar 15, 2021 · Databases

Optimizing a 20‑Million‑Row MySQL Table: Design, Indexing, Partitioning, and Migration Strategies

This article describes how to improve the performance of a massive MySQL 5.6 user‑log table by redesigning schema, applying proper indexes, using partitioning, considering table sharding, and evaluating upgrade paths to compatible cloud or big‑data databases, with concrete SQL examples and cost analysis.

Cloud DatabasesDatabase OptimizationLarge Tables
0 likes · 16 min read
Optimizing a 20‑Million‑Row MySQL Table: Design, Indexing, Partitioning, and Migration Strategies
Selected Java Interview Questions
Selected Java Interview Questions
Feb 16, 2021 · Databases

Analysis of MySQL Index Usage Cases and Best Practices

This article demonstrates how to create a test table, build indexes, and analyze their effectiveness across multiple query scenarios using MySQL's EXPLAIN output, highlighting the best‑left‑prefix rule, range condition impacts, ORDER BY considerations, and common pitfalls such as Using filesort and temporary tables.

Database OptimizationSQLexplain
0 likes · 6 min read
Analysis of MySQL Index Usage Cases and Best Practices
Code Ape Tech Column
Code Ape Tech Column
Feb 8, 2021 · Databases

Evaluating the ‘No Join Over Three Tables’ Rule from Alibaba Java Development Manual with MySQL and Oracle Experiments

This article investigates why the Alibaba Java Development Manual advises against joining more than three tables by designing and executing large‑scale MySQL and Oracle experiments, analyzing query performance, indexing effects, and data‑generation scripts to determine the practical limits of multi‑table joins.

Data GenerationDatabase OptimizationJoin Performance
0 likes · 11 min read
Evaluating the ‘No Join Over Three Tables’ Rule from Alibaba Java Development Manual with MySQL and Oracle Experiments
Architecture Digest
Architecture Digest
Feb 2, 2021 · Databases

Why Alibaba's Java Development Manual Prohibits Joins Over Three Tables – MySQL and Oracle Performance Experiments

The article investigates the Alibaba Java Development Manual's rule against joining more than three tables by designing and executing extensive MySQL and Oracle experiments, generating massive test data, measuring query performance, and concluding that the restriction stems from join scalability limits on large datasets.

Data GenerationDatabase OptimizationJoin Performance
0 likes · 11 min read
Why Alibaba's Java Development Manual Prohibits Joins Over Three Tables – MySQL and Oracle Performance Experiments
vivo Internet Technology
vivo Internet Technology
Jan 20, 2021 · Databases

Why HikariCP Is the Fastest Database Connection Pool: A Deep Dive

The article explains how HikariCP outperforms other JDBC pools by using bytecode‑generated proxies, a custom FastList, and a thread‑local ConcurrentBag, delivering superior speed, low resource use, and easy migration, making it the default high‑performance connection pool for Spring Boot 2.0.

Concurrent ProgrammingConcurrentBagDatabase Connection Pool
0 likes · 14 min read
Why HikariCP Is the Fastest Database Connection Pool: A Deep Dive
Architect's Tech Stack
Architect's Tech Stack
Jan 9, 2021 · Databases

High‑Speed Loading of 2 Billion Rows into MySQL Using TokuDB

This article describes a real‑world requirement to import over 2 billion records into MySQL, analyzes the challenges, introduces XeLabs TokuDB with its optimizations, details the test schema and configuration, demonstrates bulk loading commands, presents performance metrics showing up to 570 k rows per second, and concludes with practical recommendations and environment details.

Database OptimizationLarge DataTokuDB
0 likes · 7 min read
High‑Speed Loading of 2 Billion Rows into MySQL Using TokuDB
Architect
Architect
Jan 5, 2021 · Databases

MySQL Index Fundamentals: Types, Structures, and Design Principles

This article introduces MySQL index basics, covering index concepts, advantages and disadvantages, various index types such as B‑Tree, B+Tree, hash, and full‑text, their storage structures, creation syntax, left‑most prefix and covering indexes, and practical design guidelines for effective indexing.

B-TreeDatabase OptimizationSQL
0 likes · 22 min read
MySQL Index Fundamentals: Types, Structures, and Design Principles
dbaplus Community
dbaplus Community
Jan 3, 2021 · Databases

21 Essential SQL Habits to Boost Performance and Avoid Mistakes

This article presents 21 practical SQL habits covering safe delete/update usage, testing changes, backups, transaction handling, performance tuning with EXPLAIN and indexes, concise SELECT statements, proper data types, batch operations, and clean coding conventions to make your database work more reliable and efficient.

Database OptimizationSQLmysql
0 likes · 12 min read
21 Essential SQL Habits to Boost Performance and Avoid Mistakes
Architect's Tech Stack
Architect's Tech Stack
Dec 29, 2020 · Databases

Implementing Database Read‑Write Separation with Spring Boot and MyBatis

This article explains how to implement database read‑write separation in a Spring Boot application using Druid connection pools, custom DataSource routing, a ThreadLocal context holder, and AOP‑based annotations, providing step‑by‑step configuration and usage examples with full Java code.

DataSource RoutingDatabase OptimizationMyBatis
0 likes · 11 min read
Implementing Database Read‑Write Separation with Spring Boot and MyBatis
Liangxu Linux
Liangxu Linux
Dec 26, 2020 · Databases

Master MySQL Performance: Practical Soft and Hard Optimization Techniques

This guide explains how to boost MySQL performance through soft optimizations like query analysis, index usage, and table restructuring, as well as hard optimizations involving hardware upgrades, configuration tuning, sharding, read‑write splitting, and cache clustering.

CacheDatabase Optimizationindexing
0 likes · 8 min read
Master MySQL Performance: Practical Soft and Hard Optimization Techniques
Top Architect
Top Architect
Dec 24, 2020 · Databases

Understanding MySQL Indexes: B+Tree Structure, Implementation, and Optimization

This article explains why MySQL uses B+‑tree indexes, describes the principles of B‑tree and B+‑tree structures, compares MyISAM and InnoDB index implementations, and provides practical optimization tips such as using auto‑increment primary keys, the left‑most prefix rule, and proper configuration settings.

B+TreeDatabase OptimizationInnoDB
0 likes · 22 min read
Understanding MySQL Indexes: B+Tree Structure, Implementation, and Optimization
NetEase Media Technology Team
NetEase Media Technology Team
Dec 23, 2020 · Databases

Practical Experience of MyRocks in NetEase Media Business

Since 2019 NetEase Media has migrated several recommendation and account services from RDS to MyRocks, cutting disk usage by up to 68 % and halving response times while handling 40‑50 k QPS write‑heavy workloads, though the engine lacks partitioning, online DDL, and certain index types, requiring careful workload assessment.

Database OptimizationLSM‑TreeMyRocks
0 likes · 12 min read
Practical Experience of MyRocks in NetEase Media Business
Code Ape Tech Column
Code Ape Tech Column
Dec 23, 2020 · Databases

Master MySQL Indexes: Why B+Tree Outperforms Other Structures

This article explains how proper index creation boosts MySQL query performance, detailing the mechanics of indexes, why B+Tree is chosen over binary and balanced trees, the storage differences between MyISAM and InnoDB, and practical guidelines for designing effective single‑column, composite, and covering indexes.

B+TreeDatabase OptimizationSQL
0 likes · 19 min read
Master MySQL Indexes: Why B+Tree Outperforms Other Structures
Architect
Architect
Dec 19, 2020 · Databases

Understanding MySQL Indexes: B+ Tree Principles and Optimization

This article explains why MySQL uses B+ trees for indexing, describes the underlying principles of various index types, compares MyISAM and InnoDB implementations, and provides practical optimization guidelines such as using auto‑increment primary keys, left‑most prefix rules, and configuration tuning.

B+TreeDatabase OptimizationInnoDB
0 likes · 22 min read
Understanding MySQL Indexes: B+ Tree Principles and Optimization
Laravel Tech Community
Laravel Tech Community
Dec 10, 2020 · Databases

MySQL Single‑Table Optimization, Partitioning, Sharding and Scaling Strategies

This article provides a comprehensive guide to improving MySQL performance by optimizing single‑table schemas, indexes, queries, engine settings, system parameters, and then discusses read/write separation, caching layers, table partitioning, vertical and horizontal sharding, compatible scalable databases and when to consider NoSQL alternatives.

Database OptimizationPartitioningScalability
0 likes · 21 min read
MySQL Single‑Table Optimization, Partitioning, Sharding and Scaling Strategies
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Nov 4, 2020 · Databases

Differences Between SELECT and UPDATE Execution in MySQL: Process, Optimizer, Redo Log and Binlog

The article explains how MySQL processes SELECT and UPDATE statements, detailing each execution stage—from client authentication and cache lookup to parsing, optimization, and execution—while highlighting the additional redo log and binlog handling required for UPDATE operations and offering practical code examples.

BinlogDatabase OptimizationSQL Execution
0 likes · 14 min read
Differences Between SELECT and UPDATE Execution in MySQL: Process, Optimizer, Redo Log and Binlog
Fulu Network R&D Team
Fulu Network R&D Team
Nov 2, 2020 · Databases

Optimizing Large MySQL Tables on Alibaba Cloud: Design, Indexing, PolarDB Migration, X‑Engine Partitioning, and Parallel Query

This article details how to improve performance of massive MySQL tables on Alibaba Cloud by redesigning schemas and indexes, migrating to PolarDB with read‑write separation, partitioning historical data using the X‑Engine storage engine, and leveraging PolarDB's parallel query capabilities for faster analytics.

Database OptimizationParallel QueryPartitioning
0 likes · 12 min read
Optimizing Large MySQL Tables on Alibaba Cloud: Design, Indexing, PolarDB Migration, X‑Engine Partitioning, and Parallel Query