यह मेरा वेब डेवलपर से गूगल सॉफ्टवेर इंजिनियर बनाने की अद्ययन योजना हैं.
यह लम्बी सूचि **गूगल कोचिंग नोट्स** से छाती एव विस्तारित की गयी हैं, ताकि इन बातो को आपको पता चल सके. मैंने आपके इंटरव्यू में मदत कर सकने वाले कुछ अतिरिक्त विषय सूचि के आखिर में डाले हे.
मैं यह योजना का अनुपालन गूगल इनेर्विएव के तयारी के लिए कर रहा हूँ. मैं १९९७ से वेब, सर्विसेज और स्टार्टअप का निर्माण कर रहा हूँ. मेरे पास संगणक शात्र की पदवी ना होक अर्थशात्र की पदवी हैं. मैं अपने कैरियर में बहुत सफल रहा हूँ, पर मुजे गूगल में काम करने की इच्छा हें. मैं एक बड़े सिस्टम में प्रगति और कंप्यूटर प्रणालियों की एक असली समझ प्राप्त करना चाहते हु, अल्गोरिथम की निपुणता, डाटा स्ट्रक्चर का निष्पादन,
लो-लेवल भाषाए, और वो कैसे काम करती हें. और अगर आपको एनमेंसे किसी की जानकारी नहीं हे तो गूगल आपको नियुन्क्त नहीं करेगा.
मैंने जब ये परियोजना शुरू की, तब मैं स्टैक और हीप में फरक नहीं जनता था, मुजे नहीं पता था की Big-O क्या हे, ट्रीज क्या हे, या ग्राफ को पार कैसे करते हैं. अगर मुजे छाटने का अल्गोरिथम लिखना पड़ता तो मैं आपको ये बता सकता हु के वो इतना ख़ास नहीं होगा. जो भी डाटा स्ट्रक्चर का मैंने उपयोग किया वो भाषा में समाविष्ट था, और वो कैसे काम करता हे उसकी कोई जानकारी मुजे नहीं थी. मुजे कभी मेमोरी का संचालन नहीं करता पड़ा, जबतक मेरी चलाई कोई प्रोसेस "out of
memory" का एरर न दे, और तब मुजे कोई वैकल्पिक हल धुन्दाना पड़ता था. मैंने मेरी जिन्दगी में बहोत कम मुल्ती-डायमेंशनल ऐरे और बहोत सारे अस्सोसिअतिव् ऐरे का उपयोग किया हे, पर मैंने कोई भी डाटा स्ट्रक्चर शुरू से नहीं लिखा था.
पर इस अध्ययन योजना का उपयोग करने बाद मेरा नौकरी लगाने का आत्मविश्वास बहोत बढ़ा हें. यह एक लम्बी योजना हें. यह मेरे लिए बहोत महीनोतक चलेगी. अगर आपको ईंमैसे कुछ पता हैं तो आपको कम वक्त लगेगा.
"[फ्यूचर गूगलर](https://github.com/jwasham/google-interview-university/blob/master/extras/future-googler.pdf)" साइन की एक (या दो) प्रिंट निकाले और अपने पुरस्कार को आपने नजरो के सामने रखे.
मुजे अभीभी कुछ दींन हे ये सूचि समाप्त करने के लिए, और आगे पुरे हफ्ते से में पूरा दिनप्रोग्रामिंग प्रश्न करने वाला हु. ये कुछ हफ्ते तक चलेगा और फिर मैं मेरे रेफेरेल जो की मैं फेब्रुअरी से रखा हे उससे नौकरी का अर्ज दूंगा.
- [ ] छात्रों के लिए - [Google Careers: Technical Development Guide](https://www.google.com/about/careers/students/guide-to-technical-development.html)
- [ ] सर्च कैसे काम करता हे:
- [ ] [सर्च का विकास (विडियो)](https://www.youtube.com/watch?v=mTBShTwCnD4)
- [ ] [सर्च कैसे काम करता हैं - एक कहानी](https://www.google.com/insidesearch/howsearchworks/thestory/)
- [ ] [सर्च कैसे काम करता हैं](https://www.google.com/insidesearch/howsearchworks/)
- [ ] [सर्च कैसे काम करता हैं - मैट कट्ट्स (विडियो)](https://www.youtube.com/watch?v=BNHR6IQJGZs)
- [ ] [कैसे गूगल अपने सर्च एल्गोरिथ्म में सुधार करता है (विडियो)](https://www.youtube.com/watch?v=J5RZOU6vK4Q)
- [ ] शृंखला:
- [ ] [How Google Search Dealt With Mobile](https://backchannel.com/how-google-search-dealt-with-mobile-33bc09852dc9)
- [ ] [हमारी जरूरत पता लगाने के लिए गूगल का गुप्त अध्ययन ](https://backchannel.com/googles-secret-study-to-find-out-our-needs-eba8700263bf)
It is free to do so, but sometimes the classes are not in session so you have to wait a couple of months, so you have no access.
I'd appreciate your help converting the MOOC video links to public sources to replace the online course videos over time. I like using university lectures.
- [ ] [How Google Thinks About Hiring, Management And Culture](http://www.kpcb.com/blog/lessons-learned-how-google-thinks-about-hiring-management-and-culture)
- [ ] [Effective Whiteboarding during Programming Interviews](http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/)
- [ ] Cracking The Coding Interview Set 1:
- [ ] [Gayle L McDowell - Cracking The Coding Interview (video)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ)
- [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (video)](https://www.youtube.com/watch?v=aClxtDcdpsQ)
मैं इसके बारे में इस छोटे से लेख लिखा था: [महत्वपूर्ण: गूगल इंटरव्यू के लिए एक भाषा चुनें](https://googleyasheck.com/important-pick-one-language-for-the-google-interview/)
मैंने घंटो वीडिय के विडियो देखे और टिप्पणिया लिखी, और महीनो बाद मुजे कुछ याद नहीं रहा. सबकी समीक्षा करने के लिए मैंने 3 दिन मेरी तिप्पनिओयो और flashcards बनाने में बितायें (नीचे देखें).
To solve the problem, I made a little flashcards site where I could add flashcards of 2 types: general and code.
Each card has different formatting.
I made a mobile-first website so I could review on my phone and tablet, whereever I am.
Make your own for free:
- [Flashcards site repo](https://github.com/jwasham/computer-science-flash-cards)
- [My flash cards database](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham.db): Keep in mind I went overboard and have cards covering everything from assembly language and Python trivia to machine learning and statistics. It's way too much for what's required by Google.
**Note on flashcards:** The first time you recognize you know the answer, don't mark it as known. You have to see the
same card and answer it several times correctly before you really know it. Repetition will put that knowledge deeper in
your brain.
### 3. Review, review, review
I keep a set of cheatsheets on ASCII, OSI stack, Big-O notations, and more. I study them when I have some spare time.
Take a break from programming problems for a half hour and go through your flashcards.
### 4. Focus
There are a lot of distractions that can take up valuable time. Focus and concentration is hard.
## What you won't see covered
This big list all started as a personal to-do list made from Google interview coaching notes. These are prevalent
technologies but were not mentioned in those notes:
- SQL
- Javascript
- HTML, CSS, and other front-end technologies
## The Daily Plan
Some subjects take one day, and some will take multiple days. Some are just learning with nothing to implement.
Each day I take one subject from the list below, watch videos about that subject, and write an implementation in:
C - using structs and functions that take a struct * and something else as args.
C++ - without using built-in types
C++ - using built-in types, like STL's std::list for a linked list
Python - using built-in types (to keep practicing Python)
and write tests to ensure I'm doing it right, sometimes just using simple assert() statements
You may do Java or something else, this is just my thing.
Why code in all of these?
Practice, practice, practice, until I'm sick of it, and can do it with no problem (some have many edge cases and bookkeeping details to remember)
Work within the raw constraints (allocating/freeing memory without help of garbage collection (except Python))
Make use of built-in types so I have experience using the built-in tools for real-world use (not going to write my own linked list implementation in production)
I may not have time to do all of these for every subject, but I'll try.
(first video only - interesting but not required) [Introduction and Basics - Carnegie Mellon - Computer Architecture](https://www.youtube.com/watch?v=zLP_X4wyHbY&list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq&index=1)
- [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU)
- [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- not the whole video, just portions about Node struct and memory allocation.
- [ ] Linked List vs Arrays:
- [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays)
- [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays)
- [ ] [why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo)
- [ ] Gotcha: you need pointer to pointer knowledge:
(for when you pass a pointer to a function that may change the address where that pointer points)
This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness.
- [Pointers to Pointers](https://www.eskimo.com/~scs/cclass/int/sx8.html)
- [ ] implement (I did with tail pointer & without):
- [ ] size() - returns number of data elements in list
- [ ] empty() - bool returns true if empty
- [ ] value_at(index) - returns the value of the nth item (starting at 0 for first)
- [ ] push_front(value) - adds an item to the front of the list
- [ ] pop_front() - remove front item and return its value
- [ ] push_back(value) - adds an item at the end
- [ ] pop_back() - removes end item and returns its value
- [ ] front() - get value of front item
- [ ] back() - get value of end item
- [ ] insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index
- [ ] erase(index) - removes node at given index
- [ ] value_n_from_end(n) - returns the value of the node at nth position from the end of the list
- [ ] reverse() - reverses the list
- [ ] remove_value(value) - removes the first item in the list with this value
- [ ] [Phone Book Problem (video)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem)
- [ ] distributed hash tables:
- [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox)
- [ ] [Bits cheat sheet](https://github.com/jwasham/google-interview-university/blob/master/extras/cheat%20sheets/bits-cheat-cheet.pdf) - you should know many of the powers of 2 from (2^1 to 2^16 and 2^32)
- [ ] Get a really good understanding of manipulating bits with: &, |, ^, ~, >>, <<
- [How To Count The Number Of Set Bits In a 32 Bit Integer](http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit-integer)
- [ ] round to next power of 2:
- [Round Up To Next Power Of Two](http://bits.stephan-brumme.com/roundUpToNextPowerOfTwo.html)
- [ ] [Binary search tree - Implementation in C/C++ (video)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28)
- [ ] [BST implementation - memory allocation in stack and heap (video)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29)
- [ ] [Find min and max element in a binary search tree (video)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Find height of a binary tree (video)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31)
- [ ] [Binary tree traversal - breadth-first and depth-first strategies (video)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32)
- [ ] [Binary tree: Level Order Traversal (video)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Binary tree traversal: Preorder, Inorder, Postorder (video)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Check if a binary tree is binary search tree or not (video)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36)
- [ ] [Inorder Successor in a binary search tree (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] Implement:
- [ ] insert // insert value into tree
- [ ] get_node_count // get count of values stored
- [ ] print_values // prints the values in the tree, from min to max
- [ ] delete_tree
- [ ] is_in_tree // returns true if given value exists in the tree
- [ ] get_height // returns the height in nodes (single node's height is 1)
- [ ] get_min // returns the minimum value stored in the tree
- [ ] get_max // returns the maximum value stored in the tree
- [ ] is_binary_search_tree
- [ ] delete_value
- [ ] get_successor // returns next-highest value in tree after given value, -1 if none
- ### Heap / Priority Queue / Binary Heap
- visualized as a tree, but is usually linear in storage (array, linked list)
- [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw)
- [ ] Implement a max-heap:
- [ ] insert
- [ ] sift_up - needed for insert
- [ ] get_max - returns the max item, without removing it
- [ ] get_size() - return number of elements stored
- [ ] is_empty() - returns true if heap contains no elements
- [ ] extract_max - returns the max item, removing it
- [ ] sift_down - needed for extract_max
- [ ] remove(i) - removes item at index x
- [ ] heapify - create a heap from an array of elements, needed for heap_sort
- [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap
- note: using a min heap instead would save operations, but double the space needed (cannot do in-place).
- ### Tries
- Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits
to track the path.
- I read through code, but will not implement.
- [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries)
- [ ] Short course videos:
- [ ] [Introduction To Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries)
- [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries)
- [ ] [Implementing A Trie (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie)
- [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure)
- [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/data-science/data-science-tutorials/using-tries/)
- [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU)
- [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
- ### Balanced search trees
- Know least one type of balanced binary tree (and know how it's implemented):
- "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular.
A particularly interesting self-organizing data structure is the splay tree, which uses rotations
to move any accessed key to the root." - Skiena
- Of these, I chose to implement a splay tree. From what I've read, you won't implement a
balanced search tree in your interview. But I wanted exposure to coding one up
and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code.
- splay tree: insert, search, delete functions
If you end up implementing red/black tree try just these:
- search and insertion functions, skipping delete
- I want to learn more about B-Tree since it's used so widely with very large data sets.
- [ ] [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/data-science/data-science-tutorials/an-introduction-to-binary-search-and-red-black-trees/)
- ### N-ary (K-ary, M-ary) trees
- note: the N or K is the branching factor (max branches)
- binary trees are a 2-ary tree, with branching factor = 2
- [ ] [Understanding the Python GIL (2010)](https://www.youtube.com/watch?v=Obt-vMVdM8s)
- [reference](http://www.dabeaz.com/GIL)
- [ ] [David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015](https://www.youtube.com/watch?v=MCs5OvhV9S4)
- [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU)
- [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY)
Scalability and System Design are very large topics with many topics and resources, since there is a lot to consider
when designing a software/hardware system that can scale. Expect to spend quite a bit of time on this.
- ### System Design, Scalability, Data Handling
- Considerations from Yegge:
- scalability
- Distill large data sets to single values
- Transform one data set to another
- Handling obscenely large amounts of data
- system design
- features sets
- interfaces
- class hierarchies
- designing a system under certain constraints
- simplicity and robustness
- tradeoffs
- performance analysis and optimization
- [ ]**START HERE**: [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- [ ] [How Do I Prepare To Answer Design Questions In A Technical Inverview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023)
- [ ] [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/)
- [ ] [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/)
- [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html)
- [ ] O - [Open/Closed Principal](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension for not for modification](https://en.wikipedia.org/wiki/Open/closed_principle)
- [ ] L - [Liskov Substitution Principal](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ principal](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle)
- [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use
- [Interface Segregation Principle in 5 minutes (video)](https://www.youtube.com/watch?v=3CtAfl7aXAQ)
- [ ] D -[Dependency Inversion principle](http://www.oodesign.com/dependency-inversion-principle.html) | Reduce the dependency In composition of objects.
- [Why Is The Dependency Inversion Principle And Why Is It Important](http://stackoverflow.com/questions/62539/what-is-the-dependency-inversion-principle-and-why-is-it-important)
- [ ] [Scale at Facebook (2009)](https://www.infoq.com/presentations/Scale-at-Facebook)
- [ ] [Scale at Facebook (2012), "Building for a Billion Users" (video)](https://www.youtube.com/watch?v=oodS71YtkGU)
- [ ] [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)
- [ ] [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/)
- [ ] [Asyncio Tarantool Queue, Get In The Queue](http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html)
- [ ] [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)
- [ ] [Egnyte Architecture: Lessons Learned In Building And Scaling A Multi Petabyte Distributed System](http://highscalability.com/blog/2016/2/15/egnyte-architecture-lessons-learned-in-building-and-scaling.html)
- [ ] [Machine Learning Driven Programming: A New Programming For A New World](http://highscalability.com/blog/2016/7/6/machine-learning-driven-programming-a-new-programming-for-a.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)
- [ ] [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)
- [ ] [How Does The Use Of Docker Effect Latency?](http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html)
- [ ] [Does AMP Counter An Existential Threat To Google?](http://highscalability.com/blog/2015/12/14/does-amp-counter-an-existential-threat-to-google.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)
- [ ] [Serverless (very long, just need the gist)](http://martinfowler.com/articles/serverless.html)
- [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances)
- [ ] [Cinchcast Architecture - 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)
- [ ] [Justin.Tv's Live Video Broadcasting Architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html)
- [ ] [Playfish's Social Gaming Architecture - 50 Million Monthly Users And Growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html)
- [ ] [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 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: [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- 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 CDN network: old article](http://repository.cmu.edu/cgi/viewcontent.cgi?article=2112&context=compsci)
- [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake)
- [Design an online multiplayer card game](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html)
- [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis)
- [Design a function to return the top k requests during past time interval]( https://icmi.cs.ucsb.edu/research/tech_reports/reports/2005-23.pdf)
- [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/)
- ### Papers
- These are Google papers and well-known papers.
- Reading all from end to end with full comprehension will likely take more time than you have. I recommend being selective on papers and their sections.
- [ ] [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
- replaced by Colossus in 2012
- [ ] [2004: MapReduce: Simplified Data Processing on Large Clusters]( http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)
- mostly replaced by Cloud Dataflow?
- [ ] [2007: What Every Programmer Should Know About Memory (very long, and the author encourages skipping of some sections)](https://www.akkadia.org/drepper/cpumemory.pdf)
- [ ] [2014: Machine Learning: The High-Interest Credit Card of Technical Debt](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf)
- [ ] [2015: Continuous Pipelines at Google](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf)
- [ ] [2015: High-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44686.pdf)
- [ ] [2015: How Developers Search for Code: A Case Study](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf)
- [ ] [2016: Borg, Omega, and Kubernetes](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf)
- ### Unicode
- [ ] [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets]( http://www.joelonsoftware.com/articles/Unicode.html)
- [ ] [What Every Programmer Absolutely, Positively Needs To Know About Encodings And Character Sets To Work With Text](http://kunststube.net/encoding/)
- ### Emacs and vi(m)
- suggested by Yegge, from an old Amazon recruiting post: Familiarize yourself with a unix-based code editor
Once you've understood everything in the daily plan, and read and done exercises from the the books above,
read and do exercises from the books below. Then move to coding challenges (further down below)
**Read first:**
- [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html)
**Read second (recommended by many, but not in Google coaching docs):**
- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/)
- If you see people reference "The Google Resume", it was a book replaced by "Cracking the Coding Interview".
### Additional books
These were not suggested by Google but I added because I needed the background knowledge
- [ ] C Programming Language, Vol 2
- [answers to questions](https://github.com/lekkas/c-algorithms)
- [ ] [Algorithms and Programming: Problems and Solutions](http://www.amazon.com/Algorithms-Programming-Solutions-Alexander-Shen/dp/0817638474)
### If you have time
- [ ] [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844)
- Half.com is a great resource for textbooks at good prices.
- [ ] [Elements of Programming Interviews](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836)
- all code is in C++, if you're looking to use C++ in your interview
- good book on problem solving in general.
## Coding exercises/challenges
Once you've learned your brains out, put those brains to work.
Take coding challenges every day, as many as you can.
- [ ] [Great intro (copied from System Design section): Algorithm design:](http://www.hiredintech.com/algorithm-design/)
- [ ] [How to Find a Solution](https://www.topcoder.com/community/data-science/data-science-tutorials/how-to-find-a-solution/)
- [ ] [How to Dissect a Topcoder Problem Statement](https://www.topcoder.com/community/data-science/data-science-tutorials/how-to-dissect-a-topcoder-problem-statement/)
- [ ] [Mathematics for Topcoders](https://www.topcoder.com/community/data-science/data-science-tutorials/mathematics-for-topcoders/)
- [ ] [Dynamic Programming – From Novice to Advanced](https://www.topcoder.com/community/data-science/data-science-tutorials/dynamic-programming-from-novice-to-advanced/)
- [ ] [Core Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation)
- [ ] [Core Implementing Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation)
- [ ] [Project = Markov Text Generation Walk Through](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through)
- See more in MIT 6.050J Information and Entropy series below.
- [ ] [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2)
- ### Discrete math
- see videos below
- ### Machine Learning
- [ ] Why ML?
- [ ] [How Google Is Remaking Itself As A Machine Learning First Company](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70)
- [ ] [Large-Scale Deep Learning for Intelligent Computer Systems (video)](https://www.youtube.com/watch?v=QSaZGT4-6EY)
- [ ] [Deep Learning and Understandability versus Software Engineering and Verification by Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw)
- [ ] [A Tour of Go](https://www.youtube.com/watch?v=ytEkHepK08c)
- [ ] Books:
- [ ] [An Introduction to Programming in Go (read free online)](https://www.golang-book.com/books/intro)
- [ ] [The Go Programming Language (Donovan & Kernighan)](https://www.amazon.com/Programming-Language-Addison-Wesley-Professional-Computing/dp/0134190440)
- [ ] [MIT 6.042J: Mathematics for Computer Science, Fall 2010 (25 videos)](https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B)
- [ ] [MIT 6.046: Design and Analysis of Algorithms (34 videos)](https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- [ ] [MIT 6.050J: Information and Entropy, Spring 2008 (19 videos)](https://www.youtube.com/watch?v=phxsQrZQupo&list=PL_2Bwul6T-A7OldmhGODImZL8KEVE38X7)
- [ ] [MIT 6.851: Advanced Data Structures (22 videos)](https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=1)
http://www.gainlo.co/ - Mock interviewers from big companies
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## Once You've Got The Job
Congratulations!
- [10 things I wish I knew on my first day at Google](https://medium.com/@moonstorming/10-things-i-wish-i-knew-on-my-first-day-at-google-107581d87286#.livxn7clw)
