In this assignment we will learn how to use DataBrick's GraphFrames library for graph-parallel computation in the Spark ecosystem. GraphFrames is a package for Apache Spark which provides ...

Enterprise knowledge graphs typically store a vast array of disconnected entities. When applications require contextualized data, such as calendar events with their attendees and attachments or ...

As of version 0.8.4 there is no distinction between types of node in GraphFrames. There is support for different edge types using the relationship field. While it is possible to use any property of a ...

Abstract: In the era of big data, the number of network users has exploded, the number of network nodes has increased, and the association relationships between nodes have become more intricate.

USENIX ATC '21 Wednesday Paper Archive (50 MB ZIP, includes Proceedings front matter and attendee list) USENIX ATC '21 Thursday Paper Archive (25 MB ZIP) USENIX ATC '21 Friday Paper Archive (37 MB ZIP ...

Graph data is prevalent in many domains, but it has usually required specialized engines to analyze. This design is onerous for users and precludes optimization across complete workflows. We present ...

Community detection is a topic that can be applied to datasets that have an inherent order among themselves. For example, redwood, birch and oak are types of trees. Fish, algae and octopus are types ...

I have a simple PySpark structured streaming app that transforms incoming messages into a graph (using GraphFrames). A simplified example of the code is given below. The code will run for ~50 batches ...