Exploring parallelisms on large-scale graph processing frameworks
Large-scale graph-structured computation is becoming increasingly important for various data analysis applications, and has driven the development of various distributed graph processing frameworks. However, existing framework abstractions do not directly support efficient implementation for complex...
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project (FYP) |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/66648 |