java餐厅智能推荐系统源码-Random-topics:随机主题

[](http://awesome-scalability.com/) An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users. #### If your system goes slow > Understand your problems: scalability problem (fast for a single user but slow under heavy load) or performance problem (slow for a single user) by reviewing some [design principles](#principle) and checking how [scalability](#scalability) and [performance](#performance) problems are solved at tech companies. The section of [intelligence](#intelligence) are created for those who work with data and machine learning at big (data) and deep (learning) scale. #### If your system goes down > "Even if you lose all one day, you can build all over again if you retain your calm!" - Thuan Pham, CTO of Uber. So, keep calm and mind the [availability](#availability) and [stability](#stability) matters! #### If you are having a system design interview > Look at some [interview notes](#interview) and [real-world architectures with completed diagrams](#architecture) to get a comprehensive view before designing your system on whiteboard. You can check some [talks](#talk) of engineers from tech giants to know how they build, scale, and optimize their systems. There are some selected [books](#book) for you (most of them are free)! Good luck! #### If you are building your dream team > The goal of scaling team is not growing team size but increasing team output and value. You can find out how tech companies reach that goal in various aspects: hiring, management, organization, culture, and communication in the [organization](#organization) section. #### Community power > Contributions are greatly welcome! You may want to take a look at the [contribution guidelines](CONTRIBUTING.md). If you see a link here that is no longer maintained or is not a good fit, please submit a pull request! > Many long hours of hard work have gone into this project. If you find it helpful, please share on Facebook, [on Twitter](https://ctt.ec/V8B2p), [on Weibo](http://t.cn/RnjFLCB), or on your chat groups! Knowledge is power, knowledge shared is power multiplied. Thank you! ## Content - [Principle](#principle) - [Scalability](#scalability) - [Availability](#availability) - [Stability](#stability) - [Performance](#performance) - [Intelligence](#intelligence) - [Architecture](#architecture) - [Interview](#interview) - [Organization](#organization) - [Talk](#talk) - [Book](#book) ## Principle * [Lessons from Giant-Scale Services - Eric Brewer, UC Berkeley & Google](https://people.eecs.berkeley.edu/~brewer/papers/GiantScale-IEEE.pdf) * [Designs, Lessons and Advice from Building Large Distributed Systems - Jeff Dean, Google](https://www.cs.cornell.edu/projects/ladis2009/talks/dean-keynote-ladis2009.pdf) * [How to Design a Good API & Why it Matters - Joshua Bloch, CMU & Google](https://www.infoq.com/presentations/effective-api-design) * [On Efficiency, Reliability, Scaling - James Hamilton, VP at AWS](http://mvdirona.com/jrh/work/) * [Things to Keep in Mind When Building a Platform for the Enterprise - Heidi Williams, VP Platform at Box](https://blog.box.com/blog/4-things-to-keep-in-mind-when-building-a-platform-for-the-enterprise/) * [Principles of Chaos Engineering](https://www.usenix.org/conference/srecon17americas/program/presentation/rosenthal) * [Finding the Order in Chaos](https://www.usenix.org/conference/srecon16/program/presentation/lueder) * [The Twelve-Factor App](https://12factor.net/) * [Clean Architecture](https://8thlight.com/blog/uncle-bob/2012/08/13/the-clean-architecture.html) * [High Cohesion and Low Coupling](http://www.math-cs.gordon.edu/courses/cs211/lectures-2009/Cohesion,Coupling,MVC.pdf) * [Monoliths and Microservices](https://medium.com/@SkyscannerEng/monoliths-and-microservices-8c65708c3dbf) * [CAP Theorem and Trade-offs](http://robertgreiner.com/2014/08/cap-theorem-revisited/) * [CP Databases and AP Databases](https://blog.andyet.com/2014/10/01/right-database) * [Stateless vs Stateful Scalability](http://ithare.com/scaling-stateful-objects/) * [Scale Up vs Scale Out](https://www.brianjgraf.com/2013/05/17/scalability-scale-up-scale-out-care/) * [Scale Up vs Scale Out: Hidden Costs](https://blog.codinghorror.com/scaling-up-vs-scaling-out-hidden-costs/) * [Best Practices for Scaling Out](https://blog.openshift.com/best-practices-for-horizontal-application-scaling/) * [Best Practices for Continuous Delivery](https://techblog.rakuten.co.jp/2018/02/06/cd-the-best-practice/) * [ACID and BASE](https://neo4j.com/blog/acid-vs-base-consistency-models-explained/) * [Blocking/Non-Blocking and Sync/Async](https://blogs.msdn.microsoft.com/csliu/2009/08/27/io-concept-blockingnon-blocking-vs-syncasync/) * [Performance and Scalability of Databases](https://use-the-index-luke.com/sql/testing-scalability) * [Database Isolation Levels and Effects on Performance and Scalability](http://highscalability.com/blog/2011/2/10/database-isolation-levels-and-their-effects-on-performance-a.html) * [The Probability of Data Loss in Large Clusters](https://martin.kleppmann.com/2017/01/26/data-loss-in-large-clusters.html) * [Data Access for Highly-Scalable Solutions: Using SQL, NoSQL, and Polyglot Persistence](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/dn271399(v=pandp.10)) * [SQL vs NoSQL](https://www.upwork.com/hiring/data/sql-vs-nosql-databases-whats-the-difference/) * [SQL vs NoSQL - Lesson Learned at Salesforce](https://engineering.salesforce.com/sql-or-nosql-9eaf1d92545b) * [NoSQL Databases: Survey and Decision Guidance](https://medium.baqend.com/nosql-databases-a-survey-and-decision-guidance-ea7823a822d) * [How Sharding Works](https://medium.com/@jeeyoungk/how-sharding-works-b4dec46b3f6) * [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html) * [Consistent Hashing: Algorithmic Tradeoffs](https://medium.com/@dgryski/consistent-hashing-algorithmic-tradeoffs-ef6b8e2fcae8) * [Don’t be tricked by the Hashing Trick](https://booking.ai/dont-be-tricked-by-the-hashing-trick-192a6aae3087) * [Uniform Consistent Hashing at Netflix](https://medium.com/netflix-techblog/distributing-content-to-open-connect-3e3e391d4dc9) * [Eventually Consistent - Werner Vogels, CTO at Amazon](https://www.allthingsdistributed.com/2008/12/eventually_consistent.html) * [Cache is King](https://www.stevesouders.com/blog/2012/10/11/cache-is-king/) * [Anti-Caching](https://www.the-paper-trail.org/post/2014-06-06-paper-notes-anti-caching/) * [Understand Latency](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it) * [Latency Numbers Every Programmer Should Know](http://norvig.com/21-days.html#answers) * [The Calculus of Service Availability](https://queue.acm.org/detail.cfm?id=3096459&__s=dnkxuaws9pogqdnxmx8i) * [Architecture Issues When Scaling Web Applications: Bottlenecks, Database, CPU, IO](http://highscalability.com/blog/2014/5/12/4-architecture-issues-when-scaling-web-applications-bottlene.html) * [Common Bottlenecks](http://highscalability.com/blog/2012/5/16/big-list-of-20-common-bottlenecks.html) * [Life Beyond Distributed Transactions](https://queue.acm.org/detail.cfm?id=3025012) * [Relying on Software to Redirect Traffic Reliably at Various Layers](https://www.usenix.org/conference/srecon15/program/presentation/taveira) * [Breaking Things on Purpose](https://www.usenix.org/conference/srecon17americas/program/presentation/andrus) * [Avoid Over Engineering](https://medium.com/@rdsubhas/10-modern-software-engineering-mistakes-bc67fbef4fc8) * [Scalability Worst Practices](https://www.infoq.com/articles/scalability-worst-practices) * [Use Solid Technologies - Don’t Re-invent the Wheel - Keep It Simple!](https://medium.com/@DataStax/instagram-engineerings-3-rules