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. Federal District onsite live Apache Flink trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Mexico City - Mariano Escobedo
Mariano Escobedo 510, Ciudad de Mexico, mexico, 11590
The Mexico City Mariano Escobedo Center is on the 12th floor and penthouse of a tall, slimline commercial building with bold ...
The Mexico City Mariano Escobedo Center is on the 12th floor and penthouse of a tall, slimline commercial building with bold vertical detailing giving it instant kerb-appeal.
Mexico City - Cygni Santa Fe
Alfonso Nápoles Gandara 50, Mexico City, mexico, 1210
The Mexico City Cygni Santa Fé Center is on the top floor of a four-story building that is one of Mexico City's foremost bus...
The Mexico City Cygni Santa Fé Center is on the top floor of a four-story building that is one of Mexico City's foremost business addresses. It has landscaped grounds and an imposing entrance, and the center enjoys incredible views across to the high-rise skyline of Santa Fé, a leading district for financial services businesses.
This instructor-led, live training in Federal District (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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