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* [如何处理一个系统设计面试题](#如何处理一个系统设计面试题) * [如何处理一个系统设计面试题](#如何处理一个系统设计面试题)
* [系统设计面试题，**含解答**](#系统设计面试题和解答) * [系统设计面试题，**含解答**](#系统设计面试题和解答)
* [面向对象设计面试题，**含解答**](#面向对象设计面试问题及解答) * [面向对象设计面试题，**含解答**](#面向对象设计面试问题及解答)
* [其他系统设计面试题](#额外的系统设计面试问题) * [其它系统设计面试题](#其它系统设计面试题)
## 抽认卡 ## 抽认卡
@ -178,14 +178,14 @@
* [附录](#附录) * [附录](#附录)
* [2 的次方表](#2-的次方表) * [2 的次方表](#2-的次方表)
* [每个程序员都应该知道的延迟数](#每个程序员都应该知道的延迟数) * [每个程序员都应该知道的延迟数](#每个程序员都应该知道的延迟数)
* [其他系统设计面试题](#额外的系统设计面试问题) * [其它系统设计面试题](#其它系统设计面试题)
* [真实架构](#真实的设计架构) * [真实架构](#真实架构)
* [公司架构](#公司的系统架构) * [公司的系统架构](#公司的系统架构)
* [公司工程博客](#公司工程博客) * [公司工程博客](#公司工程博客)
* [开发中](#正在开发中) * [开发中](#正在开发中)
* [致谢](#Credits) * [致谢](#致谢)
* [联系方式](#联系方式) * [联系方式](#联系方式)
* [许可](#License) * [许可](#许可)
## 学习指引 ## 学习指引
@ -217,11 +217,11 @@
| ---------------------------------------- | ---- | ---- | ---- | | ---------------------------------------- | ---- | ---- | ---- |
| 阅读 [系统设计主题](#系统设计主题的索引) 以获得一个关于系统如何工作的宽泛的认识 | :+1: | :+1: | :+1: | | 阅读 [系统设计主题](#系统设计主题的索引) 以获得一个关于系统如何工作的宽泛的认识 | :+1: | :+1: | :+1: |
| 阅读一些你要面试的[公司工程博客](#公司工程博客)的文章 | :+1: | :+1: | :+1: | | 阅读一些你要面试的[公司工程博客](#公司工程博客)的文章 | :+1: | :+1: | :+1: |
| 阅读 [真实世界的架构](#真实的设计架构) | :+1: | :+1: | :+1: | | 阅读 [真实世界的架构](#真实架构) | :+1: | :+1: | :+1: |
| 复习 [如何处理一个系统设计面试题](#如何处理一个系统设计面试题) | :+1: | :+1: | :+1: | | 复习 [如何处理一个系统设计面试题](#如何处理一个系统设计面试题) | :+1: | :+1: | :+1: |
| 完成 [系统设计面试题和解答](#系统设计面试题和解答) | 一些 | 很多 | 大部分 | | 完成 [系统设计面试题和解答](#系统设计面试题和解答) | 一些 | 很多 | 大部分 |
| 完成 [面向对象设计面试题和解答](#面向对象设计面试问题及解答) | 一些 | 很多 | 大部分 | | 完成 [面向对象设计面试题和解答](#面向对象设计面试问题及解答) | 一些 | 很多 | 大部分 |
| 复习 [其他系统设计面试题和解答](#额外的系统设计面试问题) | 一些 | 很多 | 大部分 | | 复习 [其它系统设计面试题](#其它系统设计面试题) | 一些 | 很多 | 大部分 |
## 如何处理一个系统设计面试题 ## 如何处理一个系统设计面试题
> 如何处理一个系统设计面试题。 > 如何处理一个系统设计面试题。
@ -1612,7 +1612,7 @@ Notes
* [关于建设大型分布式系统的的设计方案、课程和建议](http://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf) * [关于建设大型分布式系统的的设计方案、课程和建议](http://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf)
* [关于建设大型可拓展分布式系统的软件工程咨询](https://static.googleusercontent.com/media/research.google.com/en//people/jeff/stanford-295-talk.pdf) * [关于建设大型可拓展分布式系统的软件工程咨询](https://static.googleusercontent.com/media/research.google.com/en//people/jeff/stanford-295-talk.pdf)
### 额外的系统设计面试问题 ### 其它系统设计面试题
> 常见的系统设计面试问题，给出了如何解决的方案链接 > 常见的系统设计面试问题，给出了如何解决的方案链接
@ -1641,7 +1641,7 @@ Notes
| 设计一个垃圾回收系统 | [stuffwithstuff.com](http://journal.stuffwithstuff.com/2013/12/08/babys-first-garbage-collector/)<br/>[washington.edu](http://courses.cs.washington.edu/courses/csep521/07wi/prj/rick.pdf) | | 设计一个垃圾回收系统 | [stuffwithstuff.com](http://journal.stuffwithstuff.com/2013/12/08/babys-first-garbage-collector/)<br/>[washington.edu](http://courses.cs.washington.edu/courses/csep521/07wi/prj/rick.pdf) |
| 添加更多的系统设计问题 | [Contribute](#contributing) | | 添加更多的系统设计问题 | [Contribute](#contributing) |
### 真实的设计架构 ### 真实架构
> 关于现实中真实的系统是怎么设计的文章。 > 关于现实中真实的系统是怎么设计的文章。
@ -1659,54 +1659,54 @@ Notes
| 类型 | 系统 | 引用 | | 类型 | 系统 | 引用 |
| --------------- | ---------------------------------------- | ---------------------------------------- | | --------------- | ---------------------------------------- | ---------------------------------------- |
| Data processing | **MapReduce** - Distributed data processing from Google | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/mapreduce-osdi04.pdf) | | Data processing | **MapReduce** - Google的分布式数据处理 | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/mapreduce-osdi04.pdf) |
| Data processing | **Spark** - Distributed data processing from Databricks | [slideshare.net](http://www.slideshare.net/AGrishchenko/apache-spark-architecture) | | Data processing | **Spark** - Databricks 的分布式数据处理 | [slideshare.net](http://www.slideshare.net/AGrishchenko/apache-spark-architecture) |
| Data processing | **Storm** - Distributed data processing from Twitter | [slideshare.net](http://www.slideshare.net/previa/storm-16094009) | | Data processing | **Storm** - Twitter 的分布式数据处理 | [slideshare.net](http://www.slideshare.net/previa/storm-16094009) |
| | | | | | | |
| Data store | **Bigtable** - Distributed column-oriented database from Google | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/chang06bigtable.pdf) | | Data store | **Bigtable** - Google 的列式数据库 | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/chang06bigtable.pdf) |
| Data store | **HBase** - Open source implementation of Bigtable | [slideshare.net](http://www.slideshare.net/alexbaranau/intro-to-hbase) | | Data store | **HBase** - Bigtable 的开源实现 | [slideshare.net](http://www.slideshare.net/alexbaranau/intro-to-hbase) |
| Data store | **Cassandra** - Distributed column-oriented database from Facebook | [slideshare.net](http://www.slideshare.net/planetcassandra/cassandra-introduction-features-30103666) | | Data store | **Cassandra** - Facebook 的列式数据库 | [slideshare.net](http://www.slideshare.net/planetcassandra/cassandra-introduction-features-30103666) |
| Data store | **DynamoDB** - Document-oriented database from Amazon | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/decandia07dynamo.pdf) | | Data store | **DynamoDB** - Amazon 的文档数据库 | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/decandia07dynamo.pdf) |
| Data store | **MongoDB** - Document-oriented database | [slideshare.net](http://www.slideshare.net/mdirolf/introduction-to-mongodb) | | Data store | **MongoDB** - 文档数据库 | [slideshare.net](http://www.slideshare.net/mdirolf/introduction-to-mongodb) |
| Data store | **Spanner** - Globally-distributed database from Google | [research.google.com](http://research.google.com/archive/spanner-osdi2012.pdf) | | Data store | **Spanner** - Google 的全球分布数据库 | [research.google.com](http://research.google.com/archive/spanner-osdi2012.pdf) |
| Data store | **Memcached** - Distributed memory caching system | [slideshare.net](http://www.slideshare.net/oemebamo/introduction-to-memcached) | | Data store | **Memcached** - 分布式内存缓存系统 | [slideshare.net](http://www.slideshare.net/oemebamo/introduction-to-memcached) |
| Data store | **Redis** - Distributed memory caching system with persistence and value types | [slideshare.net](http://www.slideshare.net/dvirsky/introduction-to-redis) | | Data store | **Redis** - 能够持久化及具有值类型的分布式内存缓存系统 | [slideshare.net](http://www.slideshare.net/dvirsky/introduction-to-redis) |
| | | | | | | |
| File system | **Google File System (GFS)** - Distributed file system | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/gfs-sosp2003.pdf) | | File system | **Google File System (GFS)** - 分布式文件系统 | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/gfs-sosp2003.pdf) |
| File system | **Hadoop File System (HDFS)** - Open source implementation of GFS | [apache.org](https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html) | | File system | **Hadoop File System (HDFS)** - GFS 的开源实现 | [apache.org](https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html) |
| | | | | | | |
| Misc | **Chubby** - Lock service for loosely-coupled distributed systems from Google | [research.google.com](http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/archive/chubby-osdi06.pdf) | | Misc | **Chubby** - Google 的分布式系统的低耦合锁服务 | [research.google.com](http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/archive/chubby-osdi06.pdf) |
| Misc | **Dapper** - Distributed systems tracing infrastructure | [research.google.com](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36356.pdf) | | Misc | **Dapper** - 分布式系统跟踪基础设施 | [research.google.com](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36356.pdf) |
| Misc | **Kafka** - Pub/sub message queue from LinkedIn | [slideshare.net](http://www.slideshare.net/mumrah/kafka-talk-tri-hug) | | Misc | **Kafka** - LinkedIn 的发布订阅消息系统 | [slideshare.net](http://www.slideshare.net/mumrah/kafka-talk-tri-hug) |
| Misc | **Zookeeper** - Centralized infrastructure and services enabling synchronization | [slideshare.net](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper) | | Misc | **Zookeeper** - 集中的基础架构和协调服务 | [slideshare.net](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper) |
| | Add an architecture | [Contribute](#contributing) | | | 添加更多 | [Contribute](#contributing) |
### 公司的系统架构 ### 公司的系统架构
| Company | Reference(s) | | Company | Reference(s) |
| -------------- | ---------------------------------------- | | -------------- | ---------------------------------------- |
| Amazon | [Amazon architecture](http://highscalability.com/amazon-architecture) | | Amazon | [Amazon 的架构](http://highscalability.com/amazon-architecture) |
| Cinchcast | [Producing 1,500 hours of audio every day](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html) | | Cinchcast | [每天产生 1500 小时的音频](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html) |
| DataSift | [Realtime datamining At 120,000 tweets per second](http://highscalability.com/blog/2011/11/29/datasift-architecture-realtime-datamining-at-120000-tweets-p.html) | | DataSift | [每秒实时挖掘 120000 条 tweet](http://highscalability.com/blog/2011/11/29/datasift-architecture-realtime-datamining-at-120000-tweets-p.html) |
| DropBox | [How we've scaled Dropbox](https://www.youtube.com/watch?v=PE4gwstWhmc) | | DropBox | [我们如何缩放 Dropbox](https://www.youtube.com/watch?v=PE4gwstWhmc) |
| ESPN | [Operating At 100,000 duh nuh nuhs per second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) | | ESPN | [每秒操作 100000 次](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html) |
| Google | [Google architecture](http://highscalability.com/google-architecture) | | Google | [Google 的架构](http://highscalability.com/google-architecture) |
| Instagram | [14 million users, terabytes of photos](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)<br/>[What powers Instagram](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) | | Instagram | [1400 万用户，达到兆级别的照片存储](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)<br/>[是什么在驱动 Instagram](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances) |
| Justin.tv | [Justin.Tv's live video broadcasting architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html) | | Justin.tv | [Justin.Tv 的直播广播架构](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html) |
| Facebook | [Scaling memcached at Facebook](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/key-value/fb-memcached-nsdi-2013.pdf)<br/>[TAO: Facebook’s distributed data store for the social graph](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/data-store/tao-facebook-distributed-datastore-atc-2013.pdf)<br/>[Facebook’s photo storage](https://www.usenix.org/legacy/event/osdi10/tech/full_papers/Beaver.pdf) | | Facebook | [Facebook 的可扩展 memcached](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/key-value/fb-memcached-nsdi-2013.pdf)<br/>[TAO: Facebook 社交图的分布式数据存储](https://cs.uwaterloo.ca/~brecht/courses/854-Emerging-2014/readings/data-store/tao-facebook-distributed-datastore-atc-2013.pdf)<br/>[Facebook 的图片存储](https://www.usenix.org/legacy/event/osdi10/tech/full_papers/Beaver.pdf) |
| Flickr | [Flickr architecture](http://highscalability.com/flickr-architecture) | | Flickr | [Flickr 的架构](http://highscalability.com/flickr-architecture) |
| Mailbox | [From 0 to one million users in 6 weeks](http://highscalability.com/blog/2013/6/18/scaling-mailbox-from-0-to-one-million-users-in-6-weeks-and-1.html) | | Mailbox | [在 6 周内从 0 到 100 万用户](http://highscalability.com/blog/2013/6/18/scaling-mailbox-from-0-to-one-million-users-in-6-weeks-and-1.html) |
| Pinterest | [From 0 To 10s of billions of page views a month](http://highscalability.com/blog/2013/4/15/scaling-pinterest-from-0-to-10s-of-billions-of-page-views-a.html)<br/>[18 million visitors, 10x growth, 12 employees](http://highscalability.com/blog/2012/5/21/pinterest-architecture-update-18-million-visitors-10x-growth.html) | | Pinterest | [从零到每月数十亿的浏览量](http://highscalability.com/blog/2013/4/15/scaling-pinterest-from-0-to-10s-of-billions-of-page-views-a.html)<br/>[1800 万访问用户，10 倍增长，12 名员工](http://highscalability.com/blog/2012/5/21/pinterest-architecture-update-18-million-visitors-10x-growth.html) |
| Playfish | [50 million monthly users and growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html) | | Playfish | [月用户量 5000 万并在不断增长](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html) |
| PlentyOfFish | [PlentyOfFish architecture](http://highscalability.com/plentyoffish-architecture) | | PlentyOfFish | [PlentyOfFish 的架构](http://highscalability.com/plentyoffish-architecture) |
| Salesforce | [How they handle 1.3 billion transactions a day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) | | Salesforce | [他们每天如何处理 13 亿笔交易](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html) |
| Stack Overflow | [Stack Overflow architecture](http://highscalability.com/blog/2009/8/5/stack-overflow-architecture.html) | | Stack Overflow | [Stack Overflow 的架构](http://highscalability.com/blog/2009/8/5/stack-overflow-architecture.html) |
| TripAdvisor | [40M visitors, 200M dynamic page views, 30TB data](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html) | | TripAdvisor | [40M 访问者，200M 页面浏览量，30TB 数据](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html) |
| Tumblr | [15 billion page views a month](http://highscalability.com/blog/2012/2/13/tumblr-architecture-15-billion-page-views-a-month-and-harder.html) | | Tumblr | [每月 150 亿的浏览量](http://highscalability.com/blog/2012/2/13/tumblr-architecture-15-billion-page-views-a-month-and-harder.html) |
| Twitter | [Making Twitter 10000 percent faster](http://highscalability.com/scaling-twitter-making-twitter-10000-percent-faster)<br/>[Storing 250 million tweets a day using MySQL](http://highscalability.com/blog/2011/12/19/how-twitter-stores-250-million-tweets-a-day-using-mysql.html)<br/>[150M active users, 300K QPS, a 22 MB/S firehose](http://highscalability.com/blog/2013/7/8/the-architecture-twitter-uses-to-deal-with-150m-active-users.html)<br/>[Timelines at scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)<br/>[Big and small data at Twitter](https://www.youtube.com/watch?v=5cKTP36HVgI)<br/>[Operations at Twitter: scaling beyond 100 million users](https://www.youtube.com/watch?v=z8LU0Cj6BOU) | | Twitter | [Making Twitter 10000 percent faster](http://highscalability.com/scaling-twitter-making-twitter-10000-percent-faster)<br/>[每天使用 MySQL 存储2.5亿条 tweet](http://highscalability.com/blog/2011/12/19/how-twitter-stores-250-million-tweets-a-day-using-mysql.html)<br/>[150M 活跃用户，300K QPS，22 MB/S 的防火墙](http://highscalability.com/blog/2013/7/8/the-architecture-twitter-uses-to-deal-with-150m-active-users.html)<br/>[可扩展时间表](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)<br/>[Twitter 的大小数据](https://www.youtube.com/watch?v=5cKTP36HVgI)<br/>[Twitter 的行为：规模超过 1 亿用户](https://www.youtube.com/watch?v=z8LU0Cj6BOU) |
| Uber | [How Uber scales their real-time market platform](http://highscalability.com/blog/2015/9/14/how-uber-scales-their-real-time-market-platform.html) | | Uber | [Uber 如何扩展自己的实时化市场](http://highscalability.com/blog/2015/9/14/how-uber-scales-their-real-time-market-platform.html) |
| WhatsApp | [The WhatsApp architecture Facebook bought for $19 billion](http://highscalability.com/blog/2014/2/26/the-whatsapp-architecture-facebook-bought-for-19-billion.html) | | WhatsApp | [Facebook 用 190 亿美元购买 WhatsApp 的架构](http://highscalability.com/blog/2014/2/26/the-whatsapp-architecture-facebook-bought-for-19-billion.html) |
| YouTube | [YouTube scalability](https://www.youtube.com/watch?v=w5WVu624fY8)<br/>[YouTube architecture](http://highscalability.com/youtube-architecture) | | YouTube | [YouTube 的可扩展性](https://www.youtube.com/watch?v=w5WVu624fY8)<br/>[YouTube 的架构](http://highscalability.com/youtube-architecture) |
### 公司工程博客 ### 公司工程博客
@ -1769,7 +1769,7 @@ Notes
* 直接存储器访问（DMA）控制器 * 直接存储器访问（DMA）控制器
* [Contribute](#contributing) * [Contribute](#contributing)
## Credits ## 致谢
整个仓库都提供了证书和源 整个仓库都提供了证书和源
@ -1791,7 +1791,7 @@ Notes
可以在我的 [GitHub 主页](https://github.com/donnemartin)上找到我的联系方式 可以在我的 [GitHub 主页](https://github.com/donnemartin)上找到我的联系方式
## License ## 许可
Creative Commons Attribution 4.0 International License (CC BY 4.0) Creative Commons Attribution 4.0 International License (CC BY 4.0)