Big scale analytics 2018-19

MSc in Computer science

Academic year

This course introduces the principal techniques related to the analysis of large amounts of data.


Date Info
07/04/2019 The Big scale analytics oral tests of April will take place in prof. Malchiodi's office on 9/4 at 14:30.
07/02/2019 The Big scale analytics oral tests of February will take place in the meeting room at the fifth floor of the Computer science department, on 12/2 at 14:30 (last name starting from A to M), and on 13/2 at 9:30 (last name starting from N to Z).
24/01/2019 Starting Monday 28/01, office hour will be handled via e-mail.
10/01/2019 The Big scale analytics oral tests of January will take place in the meeting room at the fifth floor of the Computer science department, on 16/1 at 15:00 (last name starting from A to H), and on 17/1 at 15:00 (last name starting from L to Z).
13/12/2018 The office hours of December, 18th are canceled.
29/11/2018 The Big scale analytics lectures of 4/12, 11/12, and 8/1 will take place in aula Tau; the lecture of 18/12 will take place in aula 207.
13/11/2018 Starting from 20/11, the Tuesday classes will take place in aula 207.
05/11/2018 The classes of November, 6th and 7th are canceled, as well as the office hours of November 6th.
30/10/2018 Reminder: the class of Big scale analytics of 28/11 will take place in aula V5.
08/10/2018 The class of Big scale analytics of 17/10 will take place in aula 305.
05/10/2018 Office hours for the fall semester will be on Tuesday from 16:30 in the teacher's office, starting from 09/10.
05/10/2018 Starting from 09/10, classes will take place on Tuesday from 14:30 till 16:30 in aula Alfa and on Wednesday from 13:30 till 15:30 in aula Magna.

Course schedule

Lectures will take place at the educational sector of Città Studi, according to the following tentative schedule:

Day Hour Place
Tuesday 16:30 - 18:30 14:30 - 16:30 aula V8 aula Alfa Aula 207
Wednesday 13:30 - 15:30 aula 402 aula Magna

Any change to the schedule will be announced in class and published in paragraph News of this page.

Office hours

Via e-mail. It is possible contact the teacher by e-mail, taking care to read in advance the guide prepared by Prof. Sebastiano Vigna and clearly specifying in the message the course name and the academic year. In particular, students are encouraged to always use their academic address (i.e. based on the domain signing with name and student ID number and recalling that the response time may vary depending on the teacher commitments.

Course material

The theoric part of the course is based on the following textbook: Anand Rajaraman and Jeff Ullman, Mining of Massive Datasets (marked by RU in the lectures calendar)., available both as a freely downloadable PDF and published in hardcopy by Cambridge University Press (ISBN:9781107015357). The suggested readings for the practical part are Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia, Learning Spark. Lightning-Fast Big Data Analysis, O'Reilly, 2015 (ISBN:978-1-449-35862-4) and Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills, Advanced Analytics with Spark. Patterns for Learning from Data at Scale, O'Reilly, 2015 (ISBN:978-1-491-91276-8)

The part on distributed file systems and MapReduce is based on the adopted textbook and on the Hadoop tutorial published by Yahoo!

Some labs refer to the Data Science and Engineering with Spark edX program.


The course explains the topics listed in the lecture calendar, covering the textbook contents as well as the contents of the remaining documents listed in Course material.

Lectures calendar


The lectures calendar is based on Google calendar and is accessible also through feed, iCal and Web.

Exam modalities

The exam consists in an oral test.

Exam sessions

Session Date
January 16/01/2019
February 11/02/2019
June 11/06/2019
July 02/07/2019
September 17/09/2019
January 16/01/2020