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. Oeiras onsite live Apache Flink trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Hotel Real Oeiras
nº5, R. Álvaro Rodrigues de Azevedo nº 5, 2770-197 Paço de Arcos, Paço de Arcos, Portugal, 2770-197 Paço de Arcos
With a privileged location near the business hubs of Oeiras, such as Lagoas Park, Tagus Park, and Quinta da Fonte, the Hotel ...
With a privileged location near the business hubs of Oeiras, such as Lagoas Park, Tagus Park, and Quinta da Fonte, the Hotel Real Oeiras is a 4-star hotel that offers all the conditions to organize all types of meetings and social events.
Whether it’s a business meeting, a congress, a business event, a social event, a dinner or a private lunch, a marriage, a baptism, an anniversary party or even if it’s an amusing child anniversary, the 8 multipurpose rooms are the ideal option.
With every room having natural light and direct access to the outdoor swimming pool and to the surrounding green areas, this hotel is the perfect choice to make your event memorable.
This instructor-led, live training in Oeiras (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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