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 Montpellier or in NobleProg corporate training centers in Montpellier.
NobleProg -- Your Local Training Provider
Montpellier, Garosud
NobleProg Montpellier, 48, rue Claude Balbastre, Montpellier, france, 34070
– Access Tram stop Victoire 2 Line 2 direction Saint Jean de Védas.
-Tram access then Bus take tram line 2 Sabine stop to...
– Access Tram stop Victoire 2 Line 2 direction Saint Jean de Védas.
-Tram access then Bus take tram line 2 Sabine stop towards Saint Jean de Védas then the “La Ronde” bus stop Patrice Lumumba.
- Access by car from the A9 exit 31 “Saint Jean de Védas” Montpellier Ouest, silver cross MOSSON.
-Access by train from Saint Roch station, Tram line 2 towards Saint Jean de Védas, Victory 2 stop.
– Access by plane from Montpellier airport 10 minutes by car, exit 31 of the A9 towards Barcelona or by bus from the airport line 120 to Place de l'Europe then Tram line 2 towards Saint Jean de Védas stop Victory 2
This instructor-led, live training in Montpellier (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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