Mining of Massive Datasets
by Anand Rajaraman, Jeffrey D. Ullman
Publisher: Stanford University 2010
Number of pages: 340
Description:
At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web.
Download or read it online for free here:
Download link
(2MB, PDF)
Similar books

by J. M. Hellerstein, M. Stonebraker - UC Berkeley
These lecture notes provide students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area.
(13247 views)

by Julio Ponce, Adem Karahoca - InTech
This book presents different ways of theoretical and practical advances and applications of data mining in different promising areas. The book will serve as a Data Mining bible to show a right way for the students, researchers and practitioners.
(12425 views)

by C.J. Date, Hugh Darwen - Addison Wesley
This is a book on database management based on an earlier book by the same authors. It can be seen as an abstract blueprint for the design of a DBMS and the language interface to such a DBMS. It serves as a basis for a model of type inheritance.
(3284 views)

by P. A. Bernstein, V. Hadzilacos, N. Goodman - Addison Wesley
This book is about techniques for concurrency control and recovery. It covers techniques for centralized and distributed computer systems, and for single copy, multiversion, and replicated databases. Example applications are included.
(17371 views)