Processing

Linkedin Learning – Stream Processing Patterns in Apache Flink

Linkedin Learning – Stream Processing Patterns in Apache Flink-QUiD
English | Size: 211.71 MB
Category: Tutorial


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.

PluralSight – Modeling Streaming Data for Processing with Apache Beam

PluralSight – Modeling Streaming Data for Processing with Apache Beam Bookware-KNiSO
English | Size: 237.94 MB
Category: Tutorial


Streaming data usually needs to be processed real-time or near real-time which means stream processing systems need to have capabilities that allow them to process data with low latency, high performance and fault-tolerance. In this course, Modeling Streaming Data for Processing with Apache Beam, you will gain the ability to work with streams and use the Beam unified model to build data parallel pipelines