What is Google Pregel?

Pregel (a portmanteu of the words Parallel, Graph, and Google) is a data flow paradigm and system for large-scale graph processing created at Google to solve problems that are hard or expensive to solve using only the MapReduce framework.

What is Pregel in big data?

The basic idea of Pregel is that we implement an algorithm that is executed on every vertex of a graph. It receives all messages from neighbor vertices and can optionally send messages to other vertices or update vertex value. Messages sent by this function will be received on the next iteration.

Is Pregel open source?

Pregel+ is not just another open-source Pregel implementation, but a substantially improved distributed graph computing system with effective message reduction. Compared with existing Pregel-like systems, Pregel+ provides simpler programming interface and yet achieves higher computational efficiency.

What does it mean that edges are not first class citizens in the Pregel model?

Edges are not first-class citizens in this model, having no associated computation. A Pregel program terminates when every vertex votes to halt. A vertex starts in the active state.

What is a Superstep?

A superstep consists of a unit of generic programming, which through a global communication component, makes thousands of parallel processing on a mass of data and sends it to a “meeting” called synchronization barrier. At this point, the data are grouped, and passed on to the next superstep chain.

Which programming languages can be used for using GraphX the Apachespark graph processing engine select all that apply?

It provides some advantages as shown below compared to the RDD based graph data processing: Support for Python and Java in addition to Scala APIs. Now we can use GraphX algorithms in all three languages.

What is GraphX spark?

GraphX is a new component in Spark for graphs and graph-parallel computation. At a high level, GraphX extends the Spark RDD by introducing a new Graph abstraction: a directed multigraph with properties attached to each vertex and edge.