Open AccessBinary data storage, retrieval and feature calculation on Netezza PureData system for Analytics
Author(s) -
Yann Do,
Rustam Paringer,
Alexander Kupriyanov
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/5/052016
Subject(s) - computer science , feature (linguistics) , database , computer data storage , architecture , information retrieval , fragmentation (computing) , data retrieval , data mining , programming language , operating system , art , philosophy , linguistics , visual arts
The storage of images in databases has long been a delicate matter but comes now more and more in use. This kind of data is in most DBMS limited in storage size to 64kb, making necessary to divide large objects into fragments; moreover, programming languages also present limitations in data retrieval. In this paper, we experimented the retrieval, reconstitution, feature calculation of pictures using different fragment size and determined the optimal one. In this work, the server used was a Netezza model from the N2001 line. In this work, we present the architecture of the database, our research and bring recommendation about the optimal fragmentation size to store images into a database.