Distributed Graph Processing

Distributed graph processing involves analyzing large network-like data (graphs) across multiple computer systems working together. Each system handles a portion of the graph, allowing for faster processing of complex relationships, such as social networks or transportation maps. By dividing the workload, it overcomes the limitations of a single computer’s memory and computing power, enabling efficient analysis of massive datasets. This approach is essential for tasks like finding shortest paths, community detection, or recommendation systems at scale.