Large-scale Graph Analysis: System, Algorithm and Optimization

di Yingxia Shao (Autore)

Bin Cui (Autore)

Lei Chen (Autore)

Springer Verlag, Singapore, 2020

This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms – the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology fordesigning efficient large-scale graph algorithms.

• Autore: Yingxia Shao, Bin Cui, Lei Chen
• Editore: Springer Verlag, Singapore
• Collana: Big Data Management
• Anno: 2020
• Rilegatura: Hardback
• Pagine: 146 p.
• Dimensioni: 235 x 155 mm
• EAN: 9789811539275

Testo in English