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 York or in NobleProg corporate training centers in York.
NobleProg -- Your Local Training Provider
York
15 Priory Street, York, united kingdom, YO1 6ET
Accessible conference space centrally located in the heart of York,within easy walking distance from York railway station.
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Accessible conference space centrally located in the heart of York,within easy walking distance from York railway station.
Standard lunch is a mixture of vegetarian and non-vegetarian food, which can be tailored to individual requirements and we can offer catering for a wide range of specialist dietary, cultural or religious needs. Where possible, we ask our suppliers to source fair trade or local produce that is organic, free range and GM free.
Address: 15 Priory Street, York, YO1 6ET
Telephone: 01904 621133
Web: http://www.priorystreetcentre.org.uk/
York is a walled city in northeast England that was founded by the ancient Romans. The city offers a wealth of historic attractions, of which York Minster is the most prominent, and a variety of cultural and sporting activities making it a popular tourist destination for millions.
In this instructor-led, live training in York, 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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