Course: Massive Data Analysis 2014

CS-GY 6333 Massive Data Analysis: Tentative Schedule -- subject to change

• Course Web page: http://cs.nyu.edu/courses/spring14/CSCI-GA.2568-001/index.html

• Instructor: Professor Juliana Freire (http://vgc.poly.edu/~juliana/)

• Lecture: Mondays, 1:00pm-3:25pm at 2MTC, room 9.011.

News

• Welcome!

Background (4 weeks)

Week 1 -- Sept 8: Course Overview; the evolution of Data Management

• Lecture notes: http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/course-overview.pdf (http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/course-overview-6p.pdf)
• Reading: Chapter 1 of Mining of Massive Data Sets (version 1.1)
• Course survey: https://docs.google.com/spreadsheet/embeddedform?formkey=dFpwTjROVzhLUWY2NVNXb0xvNTVLMnc6MA

Week 2 -- Sept 15: Introduction to Databases

• Lecture notes: http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/intro-to-db.pdf
• Other useful reading:
  • Greenspun's SQL for Web Nerds Intro
  • SQL/Nerds Modeling (parts)

• Homework assignment: Assignment 1 - Data Exploration

Week 3 -- Sept 22: Overview: Relational Model and SQL

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/relational-algebra.pdf
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/sql-intro.pdf
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/sql-more.pdf
• Other useful reading:
  • Greenspun's SQL for Web Nerds Intro
  • SQL/Nerds Modeling (parts)

Week 4 -- Sept 29: Overview: Advanced SQL and Query Optimization

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/xml_schema_query.pdf
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/query-opt.pdf

• Homework assignment: Assignment 2 - Data Exploration using SQL

Big Data Foundations and Infrastructure (3 weeks)

Week 5 -- Oct 6: Cloud computing, Map Reduce and Hadoop

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/mapreduce-intro.pdf

• Required reading:
  • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
  • Mining of Massive Datasets (2nd Edition), Chapter 2 - 2.1 and 2.2 (Large-Scale File Systems and Map-Reduce).

• Other useful reading:
  • Hadoop: The Definitive Guide. http://www.amazon.com/Hadoop-Definitive-Guide-Tom-White/dp/1449311520

• Homework Assignment -- Your first quiz is available on Gradiance. It is due on March 17th at 5pm.

Week 7 -- Oct 20: Algorithm Design for MapReduce

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/mapreduce-algo-design.pdf

• Required reading:
  • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
  • Mining of Massive Datasets (2nd Edition), Chapter 2.

Week 8 -- Oct 27: Parallel Databases vs MapReduce, Query Processing on Mapreduce and High-level Languages

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/paralleldb-vs-hadoop-2014.pdf
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/hive-pig.pdf
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/data-analysis-mapreduce.pdf

• Required reading:
  • Data-Intensive Text Processing with MapReduce (Jan 27, 2013), Chapter 6 -- Processing Relational Data (this chapter appears in the 2013 version of the textbook -- I have placed this version in http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Textbooks/MapReduce-algorithms-Jan2013-draft.pdf)
  • Benchmark DBMS vs MapReduce (2009): http://database.cs.brown.edu/sigmod09/benchmarks-sigmod09.pdf
  • MapReduce: A Flexible Data Processing Tool: http://cacm.acm.org/magazines/2010/1/55744-mapreduce-a-flexible-data-processing-tool/fulltext

• Additional reading:
  • Pig Latin: A Not-So-Foreign Language for Data Processing: http://pages.cs.brandeis.edu/~olga/cs228/Reading%20List_files/piglatin.pdf
  • Hive - A Warehousing Solution Over a Map-Reduce Framework: http://www.vldb.org/pvldb/2/vldb09-938.pdf

Big Data Algorithms and Techniques (3 weeks)

Week 9 -- Nov 3: Association Rules

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/association-rules.pdf

• Reading: Chapter 6 Mining of Massive Datasets

• Homework Assignment -- Your quiz is available on Gradiance. It is due on April 28th.

Week 10 -- Nov 10: Finding similar items

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/similarity.pdf

• Reading: Chapter 3 Mining of Massive Datasets

• Homework Assignment
  • There are two new quizes on Gradiance -- Distance measures and document similarity. They due on May 5th.
  • Your final assignment is available at http://www.vistrails.org/index.php/Assignment_4_-_Querying_with_Pig_and_Mapreduce. This is an optional assignment and will count towards extra credit

Week 11 -- Nov 17: Graph Analysis

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/graph-algos.pdf

Week 12 -- Nov 25: Large-Scale Visualization -- Invited lecture by Dr. Lauro Lins (AT&T Research)

• Lecture notes:
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/intro-to-visualization.pdf
  • http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/nanocubes.pdf

• Reading:

The Value of Visualization, Jarke Van Wijk http://www.win.tue.nl/~vanwijk/vov.pdf

Tamara Munzner's Book draft 2 available online http://www.cs.ubc.ca/~tmm/courses/533/book/

Nanocubes Paper http://nanocubes.net http://nanocubes.net/assets/pdf/nanocubes_paper_preprint.pdf

== Week 13 -- Dec 1:

Week 14 -- Dec 8: Final Exam

== Week 15 -- Dec 15: