Online or onsite, instructor-led live Apache Flink training courses demonstrate through interactive hands-on practice the principles and approaches behind distributed stream and batch data processing.
Apache Flink 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 Apache Flink 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.
This instructor-led, live training in York (online or onsite) introduces the principles and approaches behind distributed stream and batch data processing, and walks participants through the creation of a real-time, data streaming application in Apache Flink.
By the end of this training, participants will be able to:
Set up an environment for developing data analysis applications.
Understand how Apache Flink's graph-processing library (Gelly) works.
Package, execute, and monitor Flink-based, fault-tolerant, data streaming applications.
Manage diverse workloads.
Perform advanced analytics.
Set up a multi-node Flink cluster.
Measure and optimize performance.
Integrate Flink with different Big Data systems.
Compare Flink capabilities with those of other big data processing frameworks.
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