Online or onsite, instructor-led live GraphX training courses demonstrate through hands-on practice how to implement GraphX to carry out graph computing across many machines in parallel.
GraphX training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live GraphX training can be carried out locally on customer premises in Malaga or in NobleProg corporate training centers in Malaga.
NobleProg -- Your Local Training Provider
Malaga City Center
NobleProg Málaga, Street Cortina del Muelle, 1, Malaga, spain, 29015
Malaga, Andalusian city with more than 3,000 years of history, from its Phoenician origins to the beautiful and cosmopolitan ...
Malaga, Andalusian city with more than 3,000 years of history, from its Phoenician origins to the beautiful and cosmopolitan city that loves citizens from all over the world. Located in the south of the Iberian Peninsula, it is characterized by having multiple geographical sectors, such as Its abundant beaches or its high mountains.
The airport is connected to the city center and with the Málaga-María Zambrano Station by the Cercanías railway line and by the A Express of the EMT, which also has a stop inside the Bus Station, where you can link to the destination To other Spanish cities and the Costa del Sol.
In this instructor-led, live training in Malaga, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a Graph Computing (also known as Graph Analytics) approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments.
By the end of this training, participants will be able to:
Understand how graph data is persisted and traversed.
Select the best framework for a given task (from graph databases to batch processing frameworks.)
Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
View real-world big data problems in terms of graphs, processes and traversals.
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