Difference between revisions of "Course: Big Data 2014"
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* Required reading: | * Required reading: | ||
** Data-Intensive Text Processing with MapReduce, Chapters 1 and 2 | ** 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. | ** Mining of Massive Datasets (2nd Edition), Chapter 2 - 2.1 and 2.2 (Large-Scale File Systems and Map-Reduce). | ||
* Other useful reading: | * Other useful reading: | ||
| Line 82: | Line 82: | ||
* Homework Assignment -- Your first quiz is available on [http://www.newgradiance.com Gradiance]. It is ''due on March 17th at 5pm.'' | * Homework Assignment -- Your first quiz is available on [http://www.newgradiance.com Gradiance]. It is ''due on March 17th at 5pm.'' | ||
== Week 6 -- Mar 10: | == Week 6 -- Mar 10: Algorithm Design for MapReduce == | ||
== Week 7 -- Mar 24: No-SQL and NewSQL Systems == | * Lecture notes: | ||
** http://vgc.poly.edu/~juliana/courses/BigData2014/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 7 -- Mar 24: Data Management for Big Data, No-SQL and NewSQL Systems == | |||
== Week 8 -- Mar 31: Query Processing on Mapreduce and High-level Languages == | == Week 8 -- Mar 31: Query Processing on Mapreduce and High-level Languages == | ||
= Big Data Algorithms and Techniques (6 weeks) = | = Big Data Algorithms and Techniques (6 weeks) = | ||
Revision as of 22:06, 10 March 2014
DS-GA 1004/CSCI-GA 2568 Big Data: 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, 7:10pm-9:00pm at Cantor, room 101. Note new location!
- Cantor Film Center (CANTR), 36 E 8th St, New York, NY 10003
- Lab: Thursdays, 7:10pm-8:00pm at CIWW, room 109. Always bring your laptop.
- Warren Weaver Hall (CIWW), 251 Mercer St, New York, NY 10012
News
- Your first assignment has been posted and it is due on Feb 17, 2014 5:00 pm. Here are the instructions: http://vistrails.org/index.php/Assignment_1_-_Data_Exploration
- I have sent a test email to the class list. If you have not received the message, make sure to sign up: http://www.cs.nyu.edu/mailman/listinfo/csci_ga_2568_001_sp14
- Starting on Feb 10th, our class will meet at a new location: Cantor 101
- We will have lab on Thu at CIWW, room 109. Bring your laptop!
Background (4 weeks)
Week 1 -- Jan 27: Course Overview; the evolution of Data Management
- Lecture notes: http://vgc.poly.edu/~juliana/courses/BigData2014/Lectures/course-overview.pdf
- Reading: Chapter 1 of Mining of Massive Data Sets (version 1.1)
- Course survey: https://docs.google.com/spreadsheet/embeddedform?formkey=dDRoTVcyMnRQUXhFUjl0cFFuTEVER1E6MA
Week 2 -- Feb 3: Introduction to Databases
- Lecture notes: http://vgc.poly.edu/~juliana/courses/BigData2014/Lectures/intro-to-db.pdf
- Other useful reading:
- Feb 6: Lab: Data Exploration and Reproducibility ==
- Homework assignment: Assignment 1 - Data Exploration
Week 3 -- Feb 10: Overview: Relational Model and SQL
- Lecture notes:
- Other useful reading:
- Feb 13: Lab: Canceled -- University closed due to snow ==
Week 3.1 -- Feb 17
- No class, holiday
- Feb 20 Lab: hands-on SQL
Week 4 -- Feb 24: Overview: Advanced SQL and Query Optimization
- Lecture notes:
- Homework assignment: Assignment 2 - Data Exploration using SQL
Big Data Foundations and Infrastructure (4 weeks)
Week 5 -- Mar 3: Cloud computing, Map Reduce and Hadoop
- 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 6 -- Mar 10: Algorithm Design for MapReduce
- Required reading:
- Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
- Mining of Massive Datasets (2nd Edition), Chapter 2.