Apache Flink is built on the concept of stream-first architecture where the stream is the source of truth.
Flink is a stateful, tolerant, and large scale system which works with bounded and unbounded datasets using the same underlying stream-first architecture. In this course, Processing Streaming Data Using Apache Flink, you will integrate your Flink applications with real-time Twitter feeds to perform analysis on high-velocity streams. First, you’ll see how you can set up a standalone Flink cluster using virtual machines on a cloud platform. Next, you will install and work with the Apache Kafka reliable messaging service. Finally, you will perform a number of transformation operations on Twitter streams, including windowing and join operations. When you are finished with this course you will have the skills and knowledge to work with high volume and velocity data using Flink and integrate with Apache Kafka to process streaming data.
Flink is a stateful, tolerant, and large scale system which works with bounded and unbounded datasets using the same underlying stream-first architecture. In this course, Processing Streaming Data Using Apache Flink, you will integrate your Flink applications with real-time Twitter feeds to perform analysis on high-velocity streams. First, you’ll see how you can set up a standalone Flink cluster using virtual machines on a cloud platform. Next, you will install and work with the Apache Kafka reliable messaging service. Finally, you will perform a number of transformation operations on Twitter streams, including windowing and join operations. When you are finished with this course you will have the skills and knowledge to work with high volume and velocity data using Flink and integrate with Apache Kafka to process streaming data.
