NETS 212: Scalable and Cloud Computing (Fall 2016)

Instructor Andreas Haeberlen
Location: 560 Levine Hall
Office hour: Fridays 1:00-2:00pm
Time and location Tuesdays/Thursdays 4:30-6:00pm
LRSM Auditorium
Teaching assistants Spencer Lake (
Office hour: Mondays 5:00-6:30pm (6th floor bump space)

Graham Mosley (
Office hour: Tuesdays 6:00-7:30pm (Levine 612)

Jeffrey Silver (
Office hour: Wednesdays 5:30-7:00pm (Levine 612)

Timothy Clancy (
Office hour: Thursdays 6:00-7:30pm (5th floor bump space)
Course description What is the "cloud"? How do we build software systems and components that scale to millions of users and petabytes of data, and are "always available"?

In the modern Internet, virtually all large Web services run atop multiple geographically distributed data centers: Google, Yahoo, Facebook, iTunes, Amazon, eBay, Bing, etc. Services must scale across thousands of machines, tolerate faults, and support thousands of concurrent requests. Increasingly, the major providers (including Amazon, Google, Microsoft, HP, and IBM) are looking at "hosting" third-party applications in their data centers - forming so-called "cloud computing" services. A significant number of these services also process "streaming" data: geocoding information from cell phones, tweets, streaming video, etc.

This course, aimed at a sophomore with exposure to basic programming within the context of a single machine, focuses on the issues and programming models related to such cloud and distributed data processing technologies: data partitioning, storage schemes, stream processing, and "mostly shared-nothing" parallel algorithms.

Topics covered Datacenter architectures, the MapReduce programming model, Hadoop, cloud algorithms (PageRank, adsorption, friend recommendation, TF/IDF), web programming basics (servlets, AJAX, Node.js/Express, Bootstrap), higher-level programming (Hive, Pig Latin), ...
Format The format will be two 1.5-hour lectures per week, plus assigned readings. There will be regular homework assignments and a term project, plus a midterm and a final exam.
Prerequisites CIS 120, Introduction to Programming
CIS 160, Discrete Mathematics
Co-requisite: CIS 121, Data Structures
Texts and readings Hadoop: The Definitive Guide, Fourth Edition, by Tom White (O'Reilly) (ISBN 978-1-4919-0163-2; read online)
Data-Intensive Text Processing with MapReduce, by Jimmy Lin and Chris Dyer (Morgan & Claypool) (ISBN 978-1608453429; read online)
Additional materials will be provided as handouts or in the form of light technical papers.

Grading Homework 30%, Term project 30%, Exams 35%, Participation 5%
Policies You are encouraged to discuss your homework assignments with your classmates; however, any code you submit must be your own work. You may not share code with others or copy code from outside sources, except where the assignment specifically allows it. Plagiarism can have serious consequences.
Resources We will be using Piazza for course-related discussions.
Term project In two-person teams, build a small Facebook-like application using Node.js and Amazon's SimpleDB. Based on network analysis, the application should make friend recommendations; it should also visualize the social network.
Facebook award As in previous years, Facebook is sponsoring an award for the best term project. You can learn more about the winners from previous years in the Hall of Fame.
Assignments Homework assignments will be available for download; you can submit your solution here. If necessary, you can request an extension.
Lab sessions The TAs may occasionally hold lab sessions to provide additional help with topics related to the class.
Schedule Below is the tentative schedule for the course:

Date Topic Details Reading Remarks
Aug 30 Introduction Course overview    
Sep 1 The Cloud Kinds of clouds; cloud applications
Datacenters; utility computing
Web vs. cloud vs. cluster
Armbrust et al.: A View of Cloud Computing HW0
Sep 6 Concurrency Parallel architectures; consistency models
Synchronization; locking
Deadlock and livelock; solutions
Vogels: Eventually consistent  
Sep 8 Faults and failures Internet basics; TCP and IP
Types of faults; challenges
CAP theorem; eventual consistency
Tseitlin: The Antifragile Organization HW0 due; HW1
Sep 13  
Sep 15 Cloud basics Introduction to Amazon Web Services
EC2 and EBS
Other services
Handout: Getting Started with AWS  
Sep 19
Course selection period ends
Sep 20 Cloud storage Key-value stores; concurrency control
  HW1 MS1 due
Sep 22 MapReduce Core concepts
Programming model
Examples of MapReduce algorithms
Dean and Ghemawat: MapReduce: Simplified Data Processing on Large Clusters
Lin & Dyer, Chapter 2: MapReduce Design
Sep 27 Programming in MapReduce Using keys to group
Different kinds of reduce functions
Shuffle implementations
White, Chapter 7: How MapReduce Works
Lin & Dyer, Chapter 3: MapReduce Algorithm Design
HW1 MS2 due
Sep 29 First midterm exam (covers topics through September 27)    
Oct 4 Cloud case studies
Netflix; Google Apps
Data Warehousing at Facebook
White, Chapter 16: Case Studies
NY Times article
Oct 6–9
Fall break
Oct 10
Last day to drop
Oct 11 Hadoop Basics: Data types, drivers, mappers, reducers
HDFS; dataflow in Hadoop
Fault tolerance in Hadoop
White, Chapter 3: HDFS
White, Chapter 6: Developing a MapReduce Application
Oct 13 Graph algorithms Iterative MapReduce
Graph representations; SSSP
k-means; Naive Bayes; link analysis
Lin & Dyer, Chapter 5: Graph Algorithms  
Oct 18 Random-walk algorithms PageRank
Baluja et al.: Video suggestion and discovery for YouTube  
Oct 20 Iterative processing RDDs
White, Chapter 19 HW2 due; HW3
Oct 25 Web programming Client/server versus P2P
Web protocols: DNS, HTTP, ...
How to build a web server; threads vs events
Berners-Lee: Information Management: A Proposal
Google: SPDY white paper
Oct 27 Web services, XML, JSON Web services
Data interchange
XML; DTDs; DOM; XML schema; JSON
  HW3 MS1 due
Nov 01 Node.js Node.js; Express; EJS
Managing state; cookies
Web security
Getting Started with Express Form project teams
Nov 03
No class — Andreas in Savannah for OSDI
HW3 MS2 due; HW4
Nov 08 Dynamic content JavaScript
Google Maps
Nov 10
No class — Andreas in Atlanta for HotNets
Nov 11
Last day to withdraw
Nov 11 Beyond MapReduce SQL
White, Chapter 12: Hive
Stonebraker et al.: MapReduce and parallel DBMSs: friends or foes?
Nov 15 Security Crypto essentials
Web security
Nov 17 Peer-to-peer P2P applications; swarming; incentives
Structured and unstructured overlays; Pastry
P2P security
Rodrigues and Druschel: Peer-to-Peer systems  
Nov 18 Hierarchical data Beyond relations
Pig Latin
White, Chapter 11: Pig HW4 MS1 due
(on 11/20)
Nov 22 Case Study: Facebook Storage at Facebook
Nov 24
Thanksgiving break — no class
Nov 29
Class moved to Nov 11
Dec 01
Class moved to Nov 18
HW4 MS2 due
Dec 06 Special topics Accountability
Differential privacy
Dec 08 Second midterm exam (covers all topics since the first midterm)    
Dec 13–14
Reading days
Dec 15
Finals begin; project demos
Dec 22
Finals end