translation_ja complete
colorful-board
parent
6e1f03e959
commit
689b404e97
180
README-jp.md
180
README-jp.md
|
|
@ -1497,7 +1497,7 @@ RESTはデータを公開することに焦点を当てています。クライ
|
|||
<i><a href=https://apihandyman.io/do-you-really-know-why-you-prefer-rest-over-rpc/>Source: Do you really know why you prefer REST over RPC</a></i>
|
||||
</p>
|
||||
|
||||
#### Source(s) and further reading: REST and RPC
|
||||
#### その他の参考資料、ページ: REST と RPC
|
||||
|
||||
* [Do you really know why you prefer REST over RPC](https://apihandyman.io/do-you-really-know-why-you-prefer-rest-over-rpc/)
|
||||
* [When are RPC-ish approaches more appropriate than REST?](http://programmers.stackexchange.com/a/181186)
|
||||
|
|
@ -1508,30 +1508,30 @@ RESTはデータを公開することに焦点を当てています。クライ
|
|||
* [Thrift](https://code.facebook.com/posts/1468950976659943/)
|
||||
* [Why REST for internal use and not RPC](http://arstechnica.com/civis/viewtopic.php?t=1190508)
|
||||
|
||||
## Security
|
||||
## セキュリティ
|
||||
|
||||
This section could use some updates. Consider [contributing](#contributing)!
|
||||
このセクションは更新が必要です。[contributing](#contributing)してください！
|
||||
|
||||
Security is a broad topic. Unless you have considerable experience, a security background, or are applying for a position that requires knowledge of security, you probably won't need to know more than the basics:
|
||||
セキュリティは幅広いトピックです。十分な経験、セキュリティ分野のバックグラウンドがなくても、セキュリティの知識を要する職に応募するのでない限り、基本以上のことを知る必要はないでしょう。
|
||||
|
||||
* Encrypt in transit and at rest.
|
||||
* Sanitize all user inputs or any input parameters exposed to user to prevent [XSS](https://en.wikipedia.org/wiki/Cross-site_scripting) and [SQL injection](https://en.wikipedia.org/wiki/SQL_injection).
|
||||
* Use parameterized queries to prevent SQL injection.
|
||||
* Use the principle of [least privilege](https://en.wikipedia.org/wiki/Principle_of_least_privilege).
|
||||
* 情報伝達、保存における暗号化
|
||||
* [XSS](https://en.wikipedia.org/wiki/Cross-site_scripting) や [SQL injection](https://en.wikipedia.org/wiki/SQL_injection)を防ぐために、全てのユーザー入力もしくはユーザーに露出される入力パラメーターをサニタイズする
|
||||
* SQL injectionを防ぐためにパラメータ化されたクエリを用いる。
|
||||
* [least privilege](https://en.wikipedia.org/wiki/Principle_of_least_privilege)の原理を用いる
|
||||
|
||||
### Source(s) and further reading
|
||||
### その他の参考資料、ページ:
|
||||
|
||||
* [Security guide for developers](https://github.com/FallibleInc/security-guide-for-developers)
|
||||
* [開発者のためのセキュリティガイド](https://github.com/FallibleInc/security-guide-for-developers)
|
||||
* [OWASP top ten](https://www.owasp.org/index.php/OWASP_Top_Ten_Cheat_Sheet)
|
||||
|
||||
## Appendix
|
||||
## 付録
|
||||
|
||||
You'll sometimes be asked to do 'back-of-the-envelope' estimates. For example, you might need to determine how long it will take to generate 100 image thumbnails from disk or how much memory a data structure will take. The **Powers of two table** and **Latency numbers every programmer should know** are handy references.
|
||||
暗算で、推計値を求める必要があることも時にはあります。例えば、ディスクから100枚イメージ分のサムネイルを作る時間を求めたり、その時にどれだけディスクメモリーが消費されるかなどの値です。**2の乗数表** と **全てのプログラマーが知るべきレイテンシー値** は良い参考になるでしょう。
|
||||
|
||||
### Powers of two table
|
||||
### 2の乗数表
|
||||
|
||||
```
|
||||
Power Exact Value Approx Value Bytes
|
||||
乗数 厳密な値 約 Bytes
|
||||
---------------------------------------------------------------
|
||||
7 128
|
||||
8 256
|
||||
|
|
@ -1543,11 +1543,11 @@ Power Exact Value Approx Value Bytes
|
|||
40 1,099,511,627,776 1 trillion 1 TB
|
||||
```
|
||||
|
||||
#### Source(s) and further reading
|
||||
#### その他の参考資料、ページ:
|
||||
|
||||
* [Powers of two](https://en.wikipedia.org/wiki/Power_of_two)
|
||||
* [2の乗数表](https://en.wikipedia.org/wiki/Power_of_two)
|
||||
|
||||
### Latency numbers every programmer should know
|
||||
### 全てのプログラマーが知るべきレイテンシー値
|
||||
|
||||
```
|
||||
Latency Comparison Numbers
|
||||
|
|
@ -1575,58 +1575,58 @@ Notes
|
|||
1 ms = 10^-3 seconds = 1,000 us = 1,000,000 ns
|
||||
```
|
||||
|
||||
Handy metrics based on numbers above:
|
||||
上記表を参考にわかるわかりやすい数字は:
|
||||
|
||||
* Read sequentially from disk at 30 MB/s
|
||||
* Read sequentially from 1 Gbps Ethernet at 100 MB/s
|
||||
* Read sequentially from SSD at 1 GB/s
|
||||
* Read sequentially from main memory at 4 GB/s
|
||||
* 6-7 world-wide round trips per second
|
||||
* 2,000 round trips per second within a data center
|
||||
* ディスクからの連続読み取り速度 30 MB/s
|
||||
* 1 Gbps Ethernetからの連続読み取り速度 100 MB/s
|
||||
* SSDからの連続読み取り速度 1 GB/s
|
||||
* main memoryからの連続読み取り速度 4 GB/s
|
||||
* 一秒で地球6-7周できる
|
||||
* 一秒でデータセンターと2000周やりとりできる
|
||||
|
||||
#### Latency numbers visualized
|
||||
#### レイテンシーの視覚的表
|
||||
|
||||
|
||||
|
||||
#### Source(s) and further reading
|
||||
#### その他の参考資料、ページ:
|
||||
|
||||
* [Latency numbers every programmer should know - 1](https://gist.github.com/jboner/2841832)
|
||||
* [Latency numbers every programmer should know - 2](https://gist.github.com/hellerbarde/2843375)
|
||||
* [全てのプログラマーが知るべきレイテンシー値 - 1](https://gist.github.com/jboner/2841832)
|
||||
* [全てのプログラマーが知るべきレイテンシー値 - 2](https://gist.github.com/hellerbarde/2843375)
|
||||
* [Designs, lessons, and advice from building large distributed systems](http://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf)
|
||||
* [Software Engineering Advice from Building Large-Scale Distributed Systems](https://static.googleusercontent.com/media/research.google.com/en//people/jeff/stanford-295-talk.pdf)
|
||||
|
||||
### Additional system design interview questions
|
||||
### 他のシステム設計面接例題
|
||||
|
||||
> Common system design interview questions, with links to resources on how to solve each.
|
||||
> 頻出のシステム設計面接課題とその解答へのリンク
|
||||
|
||||
| Question | Reference(s) |
|
||||
| 質問 | 解答 |
|
||||
|---|---|
|
||||
| Design a file sync service like Dropbox | [youtube.com](https://www.youtube.com/watch?v=PE4gwstWhmc) |
|
||||
| Design a search engine like Google | [queue.acm.org](http://queue.acm.org/detail.cfm?id=988407)<br/>[stackexchange.com](http://programmers.stackexchange.com/questions/38324/interview-question-how-would-you-implement-google-search)<br/>[ardendertat.com](http://www.ardendertat.com/2012/01/11/implementing-search-engines/)<br>[stanford.edu](http://infolab.stanford.edu/~backrub/google.html) |
|
||||
| Design a scalable web crawler like Google | [quora.com](https://www.quora.com/How-can-I-build-a-web-crawler-from-scratch) |
|
||||
| Design Google docs | [code.google.com](https://code.google.com/p/google-mobwrite/)<br/>[neil.fraser.name](https://neil.fraser.name/writing/sync/) |
|
||||
| Design a key-value store like Redis | [slideshare.net](http://www.slideshare.net/dvirsky/introduction-to-redis) |
|
||||
| Design a cache system like Memcached | [slideshare.net](http://www.slideshare.net/oemebamo/introduction-to-memcached) |
|
||||
| Design a recommendation system like Amazon's | [hulu.com](http://tech.hulu.com/blog/2011/09/19/recommendation-system.html)<br/>[ijcai13.org](http://ijcai13.org/files/tutorial_slides/td3.pdf) |
|
||||
| Design a tinyurl system like Bitly | [n00tc0d3r.blogspot.com](http://n00tc0d3r.blogspot.com/) |
|
||||
| Design a chat app like WhatsApp | [highscalability.com](http://highscalability.com/blog/2014/2/26/the-whatsapp-architecture-facebook-bought-for-19-billion.html)
|
||||
| Design a picture sharing system like Instagram | [highscalability.com](http://highscalability.com/flickr-architecture)<br/>[highscalability.com](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html) |
|
||||
| Design the Facebook news feed function | [quora.com](http://www.quora.com/What-are-best-practices-for-building-something-like-a-News-Feed)<br/>[quora.com](http://www.quora.com/Activity-Streams/What-are-the-scaling-issues-to-keep-in-mind-while-developing-a-social-network-feed)<br/>[slideshare.net](http://www.slideshare.net/danmckinley/etsy-activity-feeds-architecture) |
|
||||
| Design the Facebook timeline function | [facebook.com](https://www.facebook.com/note.php?note_id=10150468255628920)<br/>[highscalability.com](http://highscalability.com/blog/2012/1/23/facebook-timeline-brought-to-you-by-the-power-of-denormaliza.html) |
|
||||
| Design the Facebook chat function | [erlang-factory.com](http://www.erlang-factory.com/upload/presentations/31/EugeneLetuchy-ErlangatFacebook.pdf)<br/>[facebook.com](https://www.facebook.com/note.php?note_id=14218138919&id=9445547199&index=0) |
|
||||
| Design a graph search function like Facebook's | [facebook.com](https://www.facebook.com/notes/facebook-engineering/under-the-hood-building-out-the-infrastructure-for-graph-search/10151347573598920)<br/>[facebook.com](https://www.facebook.com/notes/facebook-engineering/under-the-hood-indexing-and-ranking-in-graph-search/10151361720763920)<br/>[facebook.com](https://www.facebook.com/notes/facebook-engineering/under-the-hood-the-natural-language-interface-of-graph-search/10151432733048920) |
|
||||
| Design a content delivery network like CloudFlare | [cmu.edu](http://repository.cmu.edu/cgi/viewcontent.cgi?article=2112&context=compsci) |
|
||||
| Design a trending topic system like Twitter's | [michael-noll.com](http://www.michael-noll.com/blog/2013/01/18/implementing-real-time-trending-topics-in-storm/)<br/>[snikolov .wordpress.com](http://snikolov.wordpress.com/2012/11/14/early-detection-of-twitter-trends/) |
|
||||
| Design a random ID generation system | [blog.twitter.com](https://blog.twitter.com/2010/announcing-snowflake)<br/>[github.com](https://github.com/twitter/snowflake/) |
|
||||
| Return the top k requests during a time interval | [ucsb.edu](https://icmi.cs.ucsb.edu/research/tech_reports/reports/2005-23.pdf)<br/>[wpi.edu](http://davis.wpi.edu/xmdv/docs/EDBT11-diyang.pdf) |
|
||||
| Design a system that serves data from multiple data centers | [highscalability.com](http://highscalability.com/blog/2009/8/24/how-google-serves-data-from-multiple-datacenters.html) |
|
||||
| Design an online multiplayer card game | [indieflashblog.com](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html)<br/>[buildnewgames.com](http://buildnewgames.com/real-time-multiplayer/) |
|
||||
| Design a garbage collection system | [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) |
|
||||
| Add a system design question | [Contribute](#contributing) |
|
||||
| Dropboxのようなファイル同期サービスを設計する | [youtube.com](https://www.youtube.com/watch?v=PE4gwstWhmc) |
|
||||
| Googleのような検索エンジンの設計 | [queue.acm.org](http://queue.acm.org/detail.cfm?id=988407)<br/>[stackexchange.com](http://programmers.stackexchange.com/questions/38324/interview-question-how-would-you-implement-google-search)<br/>[ardendertat.com](http://www.ardendertat.com/2012/01/11/implementing-search-engines/)<br>[stanford.edu](http://infolab.stanford.edu/~backrub/google.html) |
|
||||
| Googleのようなスケーラブルなwebクローラーの設計 | [quora.com](https://www.quora.com/How-can-I-build-a-web-crawler-from-scratch) |
|
||||
| Google docsの設計 | [code.google.com](https://code.google.com/p/google-mobwrite/)<br/>[neil.fraser.name](https://neil.fraser.name/writing/sync/) |
|
||||
| Redisのようなキーバリューストアの設計 | [slideshare.net](http://www.slideshare.net/dvirsky/introduction-to-redis) |
|
||||
| Memcachedのようなキャッシュシステムの設計 | [slideshare.net](http://www.slideshare.net/oemebamo/introduction-to-memcached) |
|
||||
| Amazonにおけるようなレコメンデーションシステムの設計 | [hulu.com](http://tech.hulu.com/blog/2011/09/19/recommendation-system.html)<br/>[ijcai13.org](http://ijcai13.org/files/tutorial_slides/td3.pdf) |
|
||||
| BitlyのようなURL短縮サービスの設計 | [n00tc0d3r.blogspot.com](http://n00tc0d3r.blogspot.com/) |
|
||||
| WhatsAppのようなチャットアプリの設計 | [highscalability.com](http://highscalability.com/blog/2014/2/26/the-whatsapp-architecture-facebook-bought-for-19-billion.html)
|
||||
| Instagramのような写真共有サービスの設計 | [highscalability.com](http://highscalability.com/flickr-architecture)<br/>[highscalability.com](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html) |
|
||||
| Facebookニュースフィードの設計 | [quora.com](http://www.quora.com/What-are-best-practices-for-building-something-like-a-News-Feed)<br/>[quora.com](http://www.quora.com/Activity-Streams/What-are-the-scaling-issues-to-keep-in-mind-while-developing-a-social-network-feed)<br/>[slideshare.net](http://www.slideshare.net/danmckinley/etsy-activity-feeds-architecture) |
|
||||
| Facebookタイムラインの設計 | [facebook.com](https://www.facebook.com/note.php?note_id=10150468255628920)<br/>[highscalability.com](http://highscalability.com/blog/2012/1/23/facebook-timeline-brought-to-you-by-the-power-of-denormaliza.html) |
|
||||
| Facebookチャットの設計 | [erlang-factory.com](http://www.erlang-factory.com/upload/presentations/31/EugeneLetuchy-ErlangatFacebook.pdf)<br/>[facebook.com](https://www.facebook.com/note.php?note_id=14218138919&id=9445547199&index=0) |
|
||||
| Facebookにおけるようなgraph検索の設計 | [facebook.com](https://www.facebook.com/notes/facebook-engineering/under-the-hood-building-out-the-infrastructure-for-graph-search/10151347573598920)<br/>[facebook.com](https://www.facebook.com/notes/facebook-engineering/under-the-hood-indexing-and-ranking-in-graph-search/10151361720763920)<br/>[facebook.com](https://www.facebook.com/notes/facebook-engineering/under-the-hood-the-natural-language-interface-of-graph-search/10151432733048920) |
|
||||
| CloudFlareのようなCDNの設計 | [cmu.edu](http://repository.cmu.edu/cgi/viewcontent.cgi?article=2112&context=compsci) |
|
||||
| Twitterのトレンド機能の設計 | [michael-noll.com](http://www.michael-noll.com/blog/2013/01/18/implementing-real-time-trending-topics-in-storm/)<br/>[snikolov .wordpress.com](http://snikolov.wordpress.com/2012/11/14/early-detection-of-twitter-trends/) |
|
||||
| ランダムID発行システムの設計 | [blog.twitter.com](https://blog.twitter.com/2010/announcing-snowflake)<br/>[github.com](https://github.com/twitter/snowflake/) |
|
||||
| 一定のインターバル時間での上位k件を返す | [ucsb.edu](https://icmi.cs.ucsb.edu/research/tech_reports/reports/2005-23.pdf)<br/>[wpi.edu](http://davis.wpi.edu/xmdv/docs/EDBT11-diyang.pdf) |
|
||||
| 複数のデータセンターからデータを配信するサービスの設計 | [highscalability.com](http://highscalability.com/blog/2009/8/24/how-google-serves-data-from-multiple-datacenters.html) |
|
||||
| オンラインの複数プレイヤーカードゲームの設計 | [indieflashblog.com](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html)<br/>[buildnewgames.com](http://buildnewgames.com/real-time-multiplayer/) |
|
||||
| ごみ収集システムの設計 | [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) |
|
||||
| システム設計例題を追加する | [Contribute](#contributing) |
|
||||
|
||||
### Real world architectures
|
||||
### 実世界のアーキテクチャ
|
||||
|
||||
> Articles on how real world systems are designed.
|
||||
> 世の中のシステムがどのように設計されているかについての記事
|
||||
|
||||
<p align="center">
|
||||
<img src="http://i.imgur.com/TcUo2fw.png">
|
||||
|
|
@ -1634,39 +1634,39 @@ Handy metrics based on numbers above:
|
|||
<i><a href=https://www.infoq.com/presentations/Twitter-Timeline-Scalability>Source: Twitter timelines at scale</a></i>
|
||||
</p>
|
||||
|
||||
**Don't focus on nitty gritty details for the following articles, instead:**
|
||||
**以下の記事の重箱の隅をつつくような細かい詳細にこだわらないこと。むしろ**
|
||||
|
||||
* Identify shared principles, common technologies, and patterns within these articles
|
||||
* Study what problems are solved by each component, where it works, where it doesn't
|
||||
* Review the lessons learned
|
||||
* 共通の原理、技術、パターンを探ること
|
||||
* それぞれのコンポーネントでどんな問題が解決され、コンポーネントはどこでうまく使えもしくは使えないかを知ること
|
||||
* 学んだことを復習すること
|
||||
|
||||
|Type | System | Reference(s) |
|
||||
|種類 | システム | 参考ページ |
|
||||
|---|---|---|
|
||||
| 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 | **Spark** - Distributed data processing from Databricks | [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) |
|
||||
| データ処理 | **MapReduce** - Googleの分散データ処理システム | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/mapreduce-osdi04.pdf) |
|
||||
| データ処理 | **Spark** - Databricksの分散データ処理システム | [slideshare.net](http://www.slideshare.net/AGrishchenko/apache-spark-architecture) |
|
||||
| データ処理 | **Storm** - Twitterの分散データ処理システム | [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 | **HBase** - Open source implementation of Bigtable | [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 | **DynamoDB** - Document-oriented database from Amazon | [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 | **Spanner** - Globally-distributed database from Google | [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 | **Redis** - Distributed memory caching system with persistence and value types | [slideshare.net](http://www.slideshare.net/dvirsky/introduction-to-redis) |
|
||||
| データストア | **Bigtable** - Googleのカラム指向分散データベース | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/chang06bigtable.pdf) |
|
||||
| データストア | **HBase** - Bigtableのオープンソース実装 | [slideshare.net](http://www.slideshare.net/alexbaranau/intro-to-hbase) |
|
||||
| データストア | **Cassandra** - Facebookのカラム指向分散データベース | [slideshare.net](http://www.slideshare.net/planetcassandra/cassandra-introduction-features-30103666)
|
||||
| データストア | **DynamoDB** - Amazonのドキュメント指向分散データベース | [harvard.edu](http://www.read.seas.harvard.edu/~kohler/class/cs239-w08/decandia07dynamo.pdf) |
|
||||
| データストア | **MongoDB** - ドキュメント指向分散データベース | [slideshare.net](http://www.slideshare.net/mdirolf/introduction-to-mongodb) |
|
||||
| データストア | **Spanner** - Googleのグローバル分散データベース | [research.google.com](http://research.google.com/archive/spanner-osdi2012.pdf) |
|
||||
| データストア | **Memcached** - 分散メモリーキャッシングシステム | [slideshare.net](http://www.slideshare.net/oemebamo/introduction-to-memcached) |
|
||||
| データストア | **Redis** - 永続性とバリュータイプを兼ね備えた分散メモリーキャッシングシステム | [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 | **Hadoop File System (HDFS)** - Open source implementation of GFS | [apache.org](https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html) |
|
||||
| ファイルシステム | **Google File System (GFS)** - 分散ファイルシステム | [research.google.com](http://static.googleusercontent.com/media/research.google.com/zh-CN/us/archive/gfs-sosp2003.pdf) |
|
||||
| ファイルシステム | **Hadoop File System (HDFS)** - GFSのオープンソース実装 | [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 | **Dapper** - Distributed systems tracing infrastructure | [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 | **Zookeeper** - Centralized infrastructure and services enabling synchronization | [slideshare.net](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper) |
|
||||
| | Add an architecture | [Contribute](#contributing) |
|
||||
| Misc | **Chubby** - 疎結合の分散システムをロックするGoogleのサービス | [research.google.com](http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/archive/chubby-osdi06.pdf) |
|
||||
| Misc | **Dapper** - 分散システムを追跡するインフラ | [research.google.com](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36356.pdf)
|
||||
| Misc | **Kafka** - LinkedInによるPub/subメッセージキュー | [slideshare.net](http://www.slideshare.net/mumrah/kafka-talk-tri-hug) |
|
||||
| Misc | **Zookeeper** - 同期を可能にする中央集権インフラとサービス | [slideshare.net](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper) |
|
||||
| | アーキテクチャを追加する | [Contribute](#contributing) |
|
||||
|
||||
### Company architectures
|
||||
### 各企業のアーキテクチャ
|
||||
|
||||
| Company | Reference(s) |
|
||||
| 企業 | 参考ページ |
|
||||
|---|---|
|
||||
| Amazon | [Amazon architecture](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) |
|
||||
|
|
@ -1691,11 +1691,11 @@ Handy metrics based on numbers above:
|
|||
| 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) |
|
||||
| YouTube | [YouTube scalability](https://www.youtube.com/watch?v=w5WVu624fY8)<br/>[YouTube architecture](http://highscalability.com/youtube-architecture) |
|
||||
|
||||
### Company engineering blogs
|
||||
### 企業のエンジニアブログ
|
||||
|
||||
> Architectures for companies you are interviewing with.
|
||||
> 面接を受ける企業のアーキテクチャ
|
||||
>
|
||||
> Questions you encounter might be from the same domain.
|
||||
> 投げられる質問は同じ分野から来ることもあるでしょう
|
||||
|
||||
* [Airbnb Engineering](http://nerds.airbnb.com/)
|
||||
* [Atlassian Developers](https://developer.atlassian.com/blog/)
|
||||
|
|
@ -1739,24 +1739,24 @@ Handy metrics based on numbers above:
|
|||
* [Yelp Engineering Blog](http://engineeringblog.yelp.com/)
|
||||
* [Zynga Engineering Blog](https://www.zynga.com/blogs/engineering)
|
||||
|
||||
#### Source(s) and further reading
|
||||
#### その他の参考資料、ページ:
|
||||
|
||||
* [kilimchoi/engineering-blogs](https://github.com/kilimchoi/engineering-blogs)
|
||||
|
||||
The list of blogs here will be kept relatively small and [kilimchoi/engineering-blogs](https://github.com/kilimchoi/engineering-blogs) will contain the larger list to avoid duplicating work. Do consider adding your company blog to the engineering-blogs repo instead.
|
||||
ここにあるリストは比較的小規模なものにとどめ、[kilimchoi/engineering-blogs](https://github.com/kilimchoi/engineering-blogs)により詳細に記すことで重複しないようにしておくことにする。エンジニアブログへのリンクを追加する場合はここではなく、engineering-blogsレボジトリに追加することを検討してください。
|
||||
|
||||
## Under development
|
||||
## 進行中の作業
|
||||
|
||||
Interested in adding a section or helping complete one in-progress? [Contribute](#contributing)!
|
||||
セクションの追加や、進行中の作業を手伝っていただけますか場合は[こちら](#contributing)!
|
||||
|
||||
* Distributed computing with MapReduce
|
||||
* MapReduceによる分散コンピューティング
|
||||
* Consistent hashing
|
||||
* Scatter gather
|
||||
* [Contribute](#contributing)
|
||||
|
||||
## Credits
|
||||
## クレジット
|
||||
|
||||
Credits and sources are provided throughout this repo.
|
||||
クレジット及び、参照ページは適時このレポジトリ内に記載してあります
|
||||
|
||||
Special thanks to:
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue