News Trends Processing Using Open Linked Data

2013 ◽  
pp. 192-198 ◽  
Author(s):  
Antonio Garrote ◽  
María N. Moreno García
Keyword(s):  
Big Data ◽  
Linked Data ◽  
Detection System ◽  
Data Systems ◽  
Front End ◽  
It Systems ◽  
Big Data Technologies ◽  
Big Data Systems ◽  
Convenient Interface ◽  
The Web

In this chapter we describe a news trends detection system built with the aim of detecting daily trends in a big collection of news articles extracted from the web and expose the computed trends data as open linked data that can be consumed by other components of the IT infrastructure. Due to the sheer amount of data being processed, the system relies on big data technologies to process raw news data and compute the trends that will be later exposed as open linked data. Thanks to the open linked data interface, data can be easily consumed by other components of the application, like a JavaScript front-end, or re-used by different IT systems. The case is a good example of how open linked data can be used to provide a convenient interface to big data systems.

News Trends Processing Using Open Linked Data

2015 ◽  
pp. 1633-1637
Author(s):  
Antonio Garrote ◽  
María N. Moreno García
Keyword(s):  
Big Data ◽  
Linked Data ◽  
Detection System ◽  
Data Systems ◽  
Front End ◽  
It Systems ◽  
Big Data Technologies ◽  
Big Data Systems ◽  
Convenient Interface ◽  
The Web

In this chapter we describe a news trends detection system built with the aim of detecting daily trends in a big collection of news articles extracted from the web and expose the computed trends data as open linked data that can be consumed by other components of the IT infrastructure. Due to the sheer amount of data being processed, the system relies on big data technologies to process raw news data and compute the trends that will be later exposed as open linked data. Thanks to the open linked data interface, data can be easily consumed by other components of the application, like a JavaScript front-end, or re-used by different IT systems. The case is a good example of how open linked data can be used to provide a convenient interface to big data systems.

scholarly journals Performance Analysis of Two Big Data Technologies on a Cloud Distributed Architecture. Results for Non-Aggregate Queries on Medium-Sized Data

2016 ◽  
Vol 63 (s1) ◽  
pp. 21-50 ◽  
Author(s):  
Marin Fotache ◽  
Ionuț Hrubaru
Keyword(s):  
Big Data ◽  
Performance Analysis ◽  
Management Systems ◽  
Data Systems ◽  
Two Systems ◽  
Aggregate Queries ◽  
Big Data Technologies ◽  
Base Management ◽  
Overall Performance ◽  
Big Data Systems

Abstract Big Data systems manage and process huge volumes of data constantly generated by various technologies in a myriad of formats. Big Data advocates (and preachers) have claimed that, relative to classical, relational/SQL Data Base Management Systems, Big Data technologies such as NoSQL, Hadoop and in-memory data stores perform better. This paper compares data processing performance of two systems belonging to SQL (PostgreSQL/Postgres XL) and Big Data (Hadoop/Hive) camps on a distributed five-node cluster deployed in cloud. Unlike benchmarks in use (YCSB, TPC), a series of R modules were devised for generating random non-aggregate queries on different subschema (with increasing data size) of TPC-H database. Overall performance of the two systems was compared. Subsequently a number of models were developed for relating performance on the system and also on various query parameters such as the number of attributes in SELECT and WHERE clause, number of joins, number of processing rows etc.

Sign in / Sign up

Export Citation Format

Share Document