graph computation model articles

Articles tagged with graph computation model. There are 4 article(s) corresponding to the tag graph computation model. If you don't find what you're looking for, please check related tags: Apache Spark 2.4.0 features, Apache Spark data sources, AWS EC2, Big Data patterns implemented, completable future, data patterns, graph partitioning, horizontal scalability, idempotent consumer, Kubernetes.

Chaos in streaming graph processing

Some time ago I wrote a post about the graph data processing with streams. That article was based on X-Stream framework proposed by the searchers of EPFL research institute. At this occasion, I also mentioned the existence of newer alternative for X-Stream, adapted for distributed workloads, called Chaos. I voluntary omitted the explanation of Chaos in the previous post. Putting it aside of X-Stream would introduce too many new concepts. But now, after some weeks of graph processing discoveries, I would like to return to the successor of X-Stream and present it more in details. Continue Reading →

Streaming and graph processing

Use cases of streaming surprise me more and more. In my recent research about graph processing in Big Data era I found a paper presenting the graph framework working on vertices and edges directly from a stream. In case you've missed that paper I'll try to present this idea to you. Continue Reading →

Vertex-centric graph processing

Graph data processing, even though seems to be less popular than streaming or files processing, is an important member of data-oriented systems. And as its "colleagues", it also has some different processing logics. The first described in this blog is called vertex-centric. Continue Reading →