Optimizing query execution in large differential factbase

Optimizing query execution in large differential factbase

The aim of this project is to evaluate the effectiveness of a factbase that employs a graph database for storing program facts. Specifically, the project focuses on understanding the nature of relationships within the factbase, assessing the scalability of Neo4j for handling large amounts of data, a...

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Bibliographic Details
Main Author: Kartikeya, Vedula
Other Authors: Li Yi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Engineering::Computer science and engineering::Data::Data storage representations
Engineering::Computer science and engineering::Information systems::Information interfaces and presentation
Online Access:https://hdl.handle.net/10356/166115
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Institution: Nanyang Technological University
Language: English
Description
Summary:The aim of this project is to evaluate the effectiveness of a factbase that employs a graph database for storing program facts. Specifically, the project focuses on understanding the nature of relationships within the factbase, assessing the scalability of Neo4j for handling large amounts of data, and testing the performance of complex queries along with their execution times. To assess the system's efficiency, benchmarking will be performed by modifying some of the existing parameters in the benchmark.sh file and comparing the query execution times on new data. Overall, this project aims to contribute to the ongoing effort of improving the efficiency and scalability of program fact storage systems.

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