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Processing Streaming Data Using Apache Flink

by Janani Ravi

Apache Flink is built on the concept of stream-first architecture where the stream is the source of truth.

What you'll learn

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.

Table of contents

Course Overview

About the author

Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing ... more

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