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. Csongrád onsite live Apache Flink trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Szeged
NobleProg Szeged, Maros utca 1., Szeged, hungary, 6721
The NobleProg conference rooms are located in the city center, right next to the garden of the beautiful castle of Szeged and...
The NobleProg conference rooms are located in the city center, right next to the garden of the beautiful castle of Szeged and close to the Tisza river. These conference rooms can be hired as lecture, seminar, teaching or meeting rooms. With natural lighting from two large windows, a variety of artificial lighting options and great technical equipments, such as projector, computers, full sound system with speakers, and internet, this meeting room has great possibilities for successful presentations or trainings. Our professional staff is taking care of the preparation and implementation of the high quality conferences.
This instructor-led, live training in Csongrád (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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