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 Indiana or in NobleProg corporate training centers in Indiana.
NobleProg -- Your Local Training Provider
IN, Indianapolis - Lockerbie Marketplace
333 N. Alabama Street Suite 350, Indianapolis, united states, 46204
With its closeness to interstates and a dynamic global transportation infrastructure, as well as downtown amenities, the L...
With its closeness to interstates and a dynamic global transportation infrastructure, as well as downtown amenities, the Lockerbie Marketplace office on N. Alabama Street offers great accessibility. The office occupies the third floor of the smart Sears Building in the heart of Indianapolis’s historic district. Lockerbie Square is where many immigrants settled in the United States. Indianpolis (Indy) is an international city in Marion County that’s home to more than 500 overseas companies. It also has many vibrant sporting events including motoring mainstay, the Indy 500. Indianapolis lays claim to being one of the least expensive large cities in the US. The property is located near Lockerbie Chatham Arch and the main commercial hub of Massachusetts Avenue.
This instructor-led, live training in Indiana (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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