polito.it
Politecnico di Torino (logo)
Webthesis
Libraries

Reengineering of a Big Data architecture for real-time ingestion and data analysis

Roberto Fortino

Reengineering of a Big Data architecture for real-time ingestion and data analysis.

Rel. Elena Maria Baralis. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2018

[img]
Preview
 PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.
Download (5MB) | Preview
Abstract:

The thesis work has the aim to analyze the role covered by Big Data solutions in modern architectures and to provide a solution to a reengineering problem. All the work is focused on: - Reengineering of the Real Time Ingestion Layer, based on Kafka Stream and StreamSets - Realization of an Analytic Layer, CRUD compliant, based on Apache Kudu - Study and comparison of the Hadoop Query Layer: Hive vs Impala vs Kudu
Relators: Elena Maria Baralis
Academic year: 2017/18
Publication type: Electronic
Number of Pages: 83
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Aziende collaboratrici: DATA Reply S.r.l. con Unico Socio
URI: http://webthesis.biblio.polito.it/id/eprint/7568
Modify record (reserved for operators) Modify record (reserved for operators)