Moved system design to additional info.
This commit is contained in:
John Washam
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README.md
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README.md
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@ -165,7 +165,6 @@ software development/engineering roles.
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- [Unicode](#unicode)
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- [Endianness](#endianness)
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- [Networking](#networking)
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- [System Design, Scalability, Data Handling](#system-design-scalability-data-handling) (if you have 4+ years experience)
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- [Final Review](#final-review)
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- [Coding Question Practice](#coding-question-practice)
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- [Coding exercises/challenges](#coding-exerciseschallenges)
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@ -182,6 +181,7 @@ software development/engineering roles.
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## Additional Resources
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- [Additional Books](#additional-books)
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- [System Design, Scalability, Data Handling](#system-design-scalability-data-handling) (if you have 4+ years experience)
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- [Additional Learning](#additional-learning)
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- [Compilers](#compilers)
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- [Emacs and vi(m)](#emacs-and-vim)
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@ -1113,118 +1113,6 @@ Graphs can be used to represent many problems in computer science, so this secti
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- [ ] [Java - Sockets - Introduction (video)](https://www.youtube.com/watch?v=6G_W54zuadg&t=6s)
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- [ ] [Socket Programming (video)](https://www.youtube.com/watch?v=G75vN2mnJeQ)
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## System Design, Scalability, Data Handling
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**You can expect system design questions if you have 4+ years of experience.**
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- Scalability and System Design are very large topics with many topics and resources, since
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there is a lot to consider when designing a software/hardware system that can scale.
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Expect to spend quite a bit of time on this
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- Considerations:
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- Scalability
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- Distill large data sets to single values
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- Transform one data set to another
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- Handling obscenely large amounts of data
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- System design
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- features sets
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- interfaces
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- class hierarchies
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- designing a system under certain constraints
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- simplicity and robustness
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- tradeoffs
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- performance analysis and optimization
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- [ ] **START HERE**: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
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- [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
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- [ ] [How Do I Prepare To Answer Design Questions In A Technical Interview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023)
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- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
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- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (video)](https://www.youtube.com/watch?v=UrYLYV7WSHM)
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- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below
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- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
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- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/)
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- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html)
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- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk)
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- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem)
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- [ ] [MIT 6.824: Distributed Systems, Spring 2020 (20 videos)](https://www.youtube.com/watch?v=cQP8WApzIQQ&list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB)
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- [ ] Consensus Algorithms:
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- [ ] Paxos - [Paxos Agreement - Computerphile (video)](https://www.youtube.com/watch?v=s8JqcZtvnsM)
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- [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (video)](https://www.youtube.com/watch?v=P9Ydif5_qvE)
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- [ ] [Easy-to-read paper](https://raft.github.io/)
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- [ ] [Infographic](http://thesecretlivesofdata.com/raft/)
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- [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html)
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- [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html)
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- [ ] Scalability:
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- You don't need all of these. Just pick a few that interest you.
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- [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4)
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- [ ] Short series:
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- [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones)
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- [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database)
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- [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache)
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- [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism)
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- [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html)
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- [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf)
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- [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI)
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- [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/)
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- [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc)
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- [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0)
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- [ ] [The Importance of Algorithms](https://www.topcoder.com/community/competitive-programming/tutorials/the-importance-of-algorithms/)
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- [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html)
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- [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4)
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- [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html)
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- [video](https://www.youtube.com/watch?v=G-lGCC4KKok)
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- [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html)
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- [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/)
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- [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o)
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- [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/)
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- [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/)
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- [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html)
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- [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html)
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- [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html)
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- [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html)
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- [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html)
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- [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
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- [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html)
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- [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html)
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- [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html)
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- [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it)
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- [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances)
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- [ ] [Salesforce Architecture - 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)
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- [ ] [ESPN's Architecture At Scale - 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)
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- [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together
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- [ ] Twitter:
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- [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI)
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- [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)
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- For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section
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- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world:
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- review: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
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- [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
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- [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/main/extras/cheat%20sheets/system-design.pdf)
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- flow:
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1. Understand the problem and scope:
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- Define the use cases, with interviewer's help
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- Suggest additional features
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- Remove items that interviewer deems out of scope
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- Assume high availability is required, add as a use case
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2. Think about constraints:
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- Ask how many requests per month
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- Ask how many requests per second (they may volunteer it or make you do the math)
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- Estimate reads vs. writes percentage
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- Keep 80/20 rule in mind when estimating
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- How much data written per second
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- Total storage required over 5 years
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- How much data read per second
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3. Abstract design:
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- Layers (service, data, caching)
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- Infrastructure: load balancing, messaging
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- Rough overview of any key algorithm that drives the service
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- Consider bottlenecks and determine solutions
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- Exercises:
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- [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake)
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- [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis)
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- [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)
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- [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf)
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- [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/)
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- [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/)
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---
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## Final Review
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@ -1482,6 +1370,118 @@ You're never really done.
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- [Computer Architecture, Sixth Edition: A Quantitative Approach](https://www.amazon.com/dp/0128119055)
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- For a richer, more up-to-date (2017), but longer treatment
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## System Design, Scalability, Data Handling
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|
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**You can expect system design questions if you have 4+ years of experience.**
|
||||
|
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- Scalability and System Design are very large topics with many topics and resources, since
|
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there is a lot to consider when designing a software/hardware system that can scale.
|
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Expect to spend quite a bit of time on this
|
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- Considerations:
|
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- Scalability
|
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- Distill large data sets to single values
|
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- Transform one data set to another
|
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- Handling obscenely large amounts of data
|
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- System design
|
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- features sets
|
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- interfaces
|
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- class hierarchies
|
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- designing a system under certain constraints
|
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- simplicity and robustness
|
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- tradeoffs
|
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- performance analysis and optimization
|
||||
- [ ] **START HERE**: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
|
||||
- [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
|
||||
- [ ] [How Do I Prepare To Answer Design Questions In A Technical Interview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023)
|
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- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
|
||||
- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (video)](https://www.youtube.com/watch?v=UrYLYV7WSHM)
|
||||
- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below
|
||||
- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
|
||||
- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/)
|
||||
- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html)
|
||||
- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk)
|
||||
- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem)
|
||||
- [ ] [MIT 6.824: Distributed Systems, Spring 2020 (20 videos)](https://www.youtube.com/watch?v=cQP8WApzIQQ&list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB)
|
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- [ ] Consensus Algorithms:
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- [ ] Paxos - [Paxos Agreement - Computerphile (video)](https://www.youtube.com/watch?v=s8JqcZtvnsM)
|
||||
- [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (video)](https://www.youtube.com/watch?v=P9Ydif5_qvE)
|
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- [ ] [Easy-to-read paper](https://raft.github.io/)
|
||||
- [ ] [Infographic](http://thesecretlivesofdata.com/raft/)
|
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- [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html)
|
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- [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html)
|
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- [ ] Scalability:
|
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- You don't need all of these. Just pick a few that interest you.
|
||||
- [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4)
|
||||
- [ ] Short series:
|
||||
- [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones)
|
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- [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database)
|
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- [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache)
|
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- [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism)
|
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- [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html)
|
||||
- [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf)
|
||||
- [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI)
|
||||
- [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/)
|
||||
- [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc)
|
||||
- [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0)
|
||||
- [ ] [The Importance of Algorithms](https://www.topcoder.com/community/competitive-programming/tutorials/the-importance-of-algorithms/)
|
||||
- [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html)
|
||||
- [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4)
|
||||
- [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html)
|
||||
- [video](https://www.youtube.com/watch?v=G-lGCC4KKok)
|
||||
- [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html)
|
||||
- [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/)
|
||||
- [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o)
|
||||
- [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/)
|
||||
- [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/)
|
||||
- [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html)
|
||||
- [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html)
|
||||
- [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html)
|
||||
- [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html)
|
||||
- [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html)
|
||||
- [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
|
||||
- [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html)
|
||||
- [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html)
|
||||
- [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html)
|
||||
- [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it)
|
||||
- [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances)
|
||||
- [ ] [Salesforce Architecture - 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)
|
||||
- [ ] [ESPN's Architecture At Scale - 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)
|
||||
- [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together
|
||||
- [ ] Twitter:
|
||||
- [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI)
|
||||
- [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)
|
||||
- For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section
|
||||
- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world:
|
||||
- review: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
|
||||
- [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
|
||||
- [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/main/extras/cheat%20sheets/system-design.pdf)
|
||||
- flow:
|
||||
1. Understand the problem and scope:
|
||||
- Define the use cases, with interviewer's help
|
||||
- Suggest additional features
|
||||
- Remove items that interviewer deems out of scope
|
||||
- Assume high availability is required, add as a use case
|
||||
2. Think about constraints:
|
||||
- Ask how many requests per month
|
||||
- Ask how many requests per second (they may volunteer it or make you do the math)
|
||||
- Estimate reads vs. writes percentage
|
||||
- Keep 80/20 rule in mind when estimating
|
||||
- How much data written per second
|
||||
- Total storage required over 5 years
|
||||
- How much data read per second
|
||||
3. Abstract design:
|
||||
- Layers (service, data, caching)
|
||||
- Infrastructure: load balancing, messaging
|
||||
- Rough overview of any key algorithm that drives the service
|
||||
- Consider bottlenecks and determine solutions
|
||||
- Exercises:
|
||||
- [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake)
|
||||
- [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis)
|
||||
- [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)
|
||||
- [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf)
|
||||
- [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/)
|
||||
- [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/)
|
||||
|
||||
## Additional Learning
|
||||
|
||||
I added them to help you become a well-rounded software engineer, and to be aware of certain
|
||||
|
|
|
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Loading…
Reference in New Issue