Linkedin.Learning.Stream.Processing.Patterns.in.Apache.Flink-QUiD

Section

Appz

Group

QUiD

Size

211,71 MB

Files

17

Date

2021-01-06

NFO

Release Name : Linkedin.Learning.Stream.Processing.Patterns.in.Apache.Flink-QUiD

Publisher    : Linkedin
Release Date : 2021-01-06
Size         : 15 x 15MB
Url          : https://www.lynda.com/Flink-tutorials/Stream-Processing-Patterns-Apache-Flink/2833060-2.html


Release Info: 
Frameworks such as Apache Flink can help you build fast, scalable stream processing 
applications, but big data engineers still need to design smart use cases to achieve 
maximum efficiency. In this course, instructor Kumaran Ponnambalam demonstrates how to 
use Apache Flink and associated technologies to build stream-processing use cases 
leveraging popular patterns. Kumaran begins by highlighting the opportunities and 
challenges that stream processing brings to big data. He then goes over four popular 
patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, 
and real-time predictions. Along the way, he reviews example use cases and explains how 
to leverage Flink, as well as key technologies like MariaDB and Redis, to implement key 
examples.


- Unpack
- Open the tutorial
- Enjoy

Files