02282 Algorithms for Massive Data Sets

General Info | Mandatory Exercises | Weekplan | FAQ

General Info


When and where Monday 8.15-12, Bldg. 324, room 040. The course runs in the DTU spring semester (Feb. 2 to May 15). There is no teaching in the Easter break (March 30 and April 6).

Piazza The course uses Piazza as onlineforum discussion of material. Sign up here

Mandatory Exercises

Use the template.tex file to prepare your hand in exercises. Do not repeat the problem statement in your hand in. Compile using LaTeX. Upload the resulting pdf file (and only this file) via Campusnet. The maximum size of the finished pdf must be at most 2 pages. An exercise from week x must be handed in no later than Sunday in week x before 20.00.

Collaboration policy for mandatory exercises

Violations of the collaboration policy will be reported.


The weekplan is preliminary It will be updated during the course. Under each week there is a number of suggestions for reading material regarding that weeks lecture. It is not the intention that you read ALL of the papers. It is a list of papers and notes where you can read about the subject discussed at the lecture.

Week Topics Slides Weekplan Mandatory Material
Approximation Algorithms I: Scheduling, k-center. 1x1 · 4x1 Approximation Algorithms I Week 1
Integer Data Structures I: Dictionaries, Universal and Perfect Hashing. 1x1 · 4x1 Hashing Mandatory
Integer Data Structures II: Predecessor Problem, van Emde Boas, x-Fast and y-Fast Tries 1x1 · 4x1 Predecessor Mandatory
Trees I: Nearest Common Ancestor, Range Minimum Query NCA+RMQ Mandatory
Trees II: Level Ancestor, Path Decompositions, Tree Decompositions 1x1 · 4x1 Level Ancestor Mandatory
Trees III: Range Reporting, Range Trees, Fractional Cascading, kD Trees 1x1 · 4x1 Range Reporting Mandatory
Strings I: Dictionaries, Tries, Suffix trees, Suffix Sorting 1x1 · 4x1 Suffix Trees Mandatory
Strings II: Approximate String Matching Part 1, Part 2 Approximate String Matching Mandatory
Strings III: Compression, Lempel-Ziv, Grammar-compression, and Burrows-Wheeler Transform 1x1 Compression Mandatory
Strings IV: Compressed Pattern Matching 1x1 Compressed Pattern Matching Mandatory
External Memory I: I/O Model, Cache-Oblivious Model, External Dynamic Programming 1x1 · 4x1 External Memory Mandatory
External Memory II: B-trees 1x1 External Memory II Mandatory
Course Roundup, Questions, Future Perspectives

Frequently Asked Questions

How should I write my mandatory exercises? The ideal writing format for mandatory exercises is classical scientific writing, such as the writing found in the peer-reviewed articles listed as reading material for this course (not textbooks and other pedagogical material). One of the objectives of this course is to practice and learn this kind of writing. A few tips:

How much do the mandatory exercises count in the final grade? The final grade is an overall evaluation of your mandatory exercise and the oral exam combined. Thus, there is no precise division of these part in the final grade. However, expect that (in most cases, and under normal circumstances) the mandatory exercises account for a large fraction of the final grade.

Can I write my assignments in Danish? Ja. Du er meget velkommen til at aflevere på dansk.

What do I do if I want to do a MSc/BSc thesis or project in Algorithms? Great! Algorithms is an excellent topic to work on :-) and Algorithms for Massive Data Sets is designed to prepare you to write a strong thesis. Some basic tips and points.