非常全面的高性能高并发服务器架构解决方案.doc

由于自己正在做一个高性能大用户量的论坛程序，对高性能高并发服务器架构比较感兴趣

于是在网上收集了不少这方面的资料和大家分享。

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初创网站与开源软件........................................................................................................................7

谈谈大型高负载网站服务器的优化心得!....................................................................................10

Lighttpd+Squid+Apache 搭建高效率 Web 服务器........................................................................11

浏览量比较大的网站应该从哪几个方面入手？.........................................................................18

用负载均衡技术建设高负载站点..................................................................................................21

总概关键点：...................................................................................................................53

1，Mysql 切分，采用 Innodb 运行................................................................................53

2，动态 Cache 服务器 --.................................................................................................54

美国 Facebok.com, 中国 Yeejee.com, 日本 mixi.jp 均采用开 源分布式缓存 服务器

Memcache.........................................................................................................................54

3，图片缓存和加.............................................................................................................54

memcached+squid+apache deflate 解决网站大访问量问题.........................................................54

FeedBurner:基于 MySQL 和 JAVA 的可扩展 Web 应用...............................................................55

YouTube 的架构扩展......................................................................................................................57

了解一下 Technorati 的后台数据库架构......................................................................................59

二、LiveJournal 架构现状概况.......................................................................................72

三、从 LiveJournal 发展中学习......................................................................................73

1、一台服务器.................................................................................................................73

2、两台服务器.................................................................................................................74

3、四台服务器.................................................................................................................75

4、五台服务器.................................................................................................................75

5、更多服务器.................................................................................................................76

6、现在我们在哪里：.....................................................................................................77

7、现在我们在哪里.........................................................................................................80

8、现在我们在哪里.........................................................................................................82

Second Life 的数据拾零.................................................................................................................85

eBay 架构的思想金矿....................................................................................................................86

七种缓存使用武器 为网站应用和访问加速发布时间:...............................................................96

可缓存的 CMS 系统设计................................................................................................................97

开发大型高负载类网站应用的几个要点[nightsailer]................................................................108

Memcached 和 Lucene 笔记..........................................................................................................113

使用开源软件，设计高性能可扩展网站....................................................................................114

High Performance Web Sites by Nate Koechley...........................................................................127

One dozen rules for faster pages.....................................................................................127

Why talk about performance?.........................................................................................128

Case Studies....................................................................................................................128

Conclusion.......................................................................................................................128

Rules for High Performance Web Sites.........................................................................................128

对于应用高并发，DB 千万级数量该如何设计系统哪？.........................................................129

高性能服务器设计........................................................................................................................134

优势与应用：再谈 CDN 镜像加速技术.....................................................................................136

.........................................................................................................................................................140

海量数据处理分析........................................................................................................................169

一个很有意义的 SQL 的优化过程（一个电子化支局中的大数据量的统计 SQL）.............171

如何优化大数据量模糊查询（架构，数据库设置，SQL..）..................................................174

求助:海量数据处理方法...............................................................................................................174

#re: 求助:海量数据处理方法 回复 更多评论 .......................................................174

海量数据库查询方略....................................................................................................................175

SQL Server 2005 对海量数据处理...............................................................................................175

分表处理设计思想和实现............................................................................................................187

Linux 系统高负载 MySQL 数据库彻底优化(1).........................................................................191

大型数据库的设计与编程技巧 本人最近开发一个访问统计系统，日志非常的大，都保存在

web 软件设计时考虑你的性能解决方案....................................................................................204

大型 Java Web 系统服务器选型问题探讨...................................................................................208

1.1 互联网的发展...................................................................................................................225

1.2 互联网网站建设的新趋势...............................................................................................226

1.3 新浪播客的简介...............................................................................................................226

2.1 镜像网站技术...................................................................................................................227

2.2 CDN 内容分发网络.........................................................................................................228

资料收集：高并发 高性能 高扩展性 Web 2.0 站点架构设计及优化策略.............................262

CommunityServer 性能问题浅析.................................................................................................267

鸡肋式的多站点支持.....................................................................................................268

内容数据的集中式存储.................................................................................................268

过于依赖缓存.................................................................................................................268

CCS 的雪上加霜............................................................................................................268

如何解决？.....................................................................................................................268

Digg PHP's Scalability and Performance.......................................................................................269

YouTube Architecture.....................................................................................................................271

Information Sources................................................................................................................272

What's Inside?.........................................................................................................................272

Serving Thumbnails........................................................................................................275

Databases.........................................................................................................................276

Data Center Strategy.......................................................................................................278

Lessons Learned......................................................................................................................278

1. Jesse · Comments (78) · April 10th............................................................................279

Library.....................................................................................................................................285

Friendster Architecture............................................................................................................292

Information Sources................................................................................................................292

Platform...................................................................................................................................292

What's Inside?.........................................................................................................................292

Related Articles.......................................................................................................................297

Comments................................................................................................................................297

Re: Feedblendr Architecture - Using EC2 to Scale........................................................297

Re: Feedblendr Architecture - Using EC2 to Scale........................................................298

Re: Feedblendr Architecture - Using EC2 to Scale........................................................299

PlentyOfFish Architecture..............................................................................................................300

Information Sources................................................................................................................301

The Platform............................................................................................................................301

The Stats..................................................................................................................................301

What's Inside...........................................................................................................................302

Information Sources................................................................................................................307

Platform...................................................................................................................................307

The Stats..................................................................................................................................308

The Architecture......................................................................................................................308

Lessons Learned......................................................................................................................310

Scaling Early Stage Startups..........................................................................................................311

Information Sources................................................................................................................312

The Platform............................................................................................................................312

The Architecture......................................................................................................................312

Database parallelism choices greatly impact scalability...............................................................314

Remote Procedure Calls..................................................................................................324

Some Distributed Design Principles...............................................................................326

Exercises..........................................................................................................................327

References.......................................................................................................................328

Flickr Architecture..........................................................................................................................329

Information Sources................................................................................................................329

Platform...................................................................................................................................329

The Stats..................................................................................................................................330

The Architecture......................................................................................................................330

Lessons Learned......................................................................................................................335

The Stats..................................................................................................................................340

The Architecture......................................................................................................................340

Lessons Learned......................................................................................................................344

Comments................................................................................................................................349

Jeff.. Bazos?....................................................................................................................349

Werner Vogels, the CTO of.............................................................................................349

Re: Amazon Architecture................................................................................................349

Re: Amazon Architecture................................................................................................350

Re: Amazon Architecture................................................................................................350

It's WSDL........................................................................................................................350

Scaling Twitter: Making Twitter 10000 Percent Faster.................................................................351

Information Sources................................................................................................................352

The Platform............................................................................................................................352

The Stats..................................................................................................................................352

The Architecture......................................................................................................................353

Lessons Learned......................................................................................................................355

Related Articles.......................................................................................................................357

Comments................................................................................................................................358

Re: Scaling Twitter: Making Twitter 10000 Percent Faster...........................................358

Re: Scaling Twitter: Making Twitter 10000 Percent Faster...........................................358

Re: Scaling Twitter: Making Twitter 10000 Percent Faster...........................................361

Google Architecture.......................................................................................................................361

Information Sources................................................................................................................362

Platform...................................................................................................................................362

What's Inside?.........................................................................................................................363

The Stats..........................................................................................................................363

The Stack.........................................................................................................................363

Reliable Storage Mechanism with GFS (Google File System)......................................363

Do Something With the Data Using MapReduce...........................................................364

Storing Structured Data in BigTable...............................................................................366