Getting Started with Stream Processing Using Apache Flink

Size: 277 Mb | Duration: 2h 44m | Video: AVC (.mp4) 1280x720 15-30fps | Audio: AAC 48KHz 2ch

Genre: eLearning | Level: Beginner | Language: English

Apache Flink is a distributed computing engine used to process large scale data. Flink is built on the concept of stream-first architecture where the stream is the source of truth. This course, Getting Started with Stream Processing Using Apache Flink, walks the users through exploratory data analysis and data munging with Flink.

You’ll start off learning about simple data transformations on streams such as map(), filter(), flatMap(), reduce(), sum(), min(), and max() on simple DataStreams and KeyedStreams. You’ll then learn about window transformations in detail using tumbling, sliding, count, and session windows. You’ll wrap up the course explore operations on multiple streams such as union and joins. All of this with hands on demos using Flink’s Java API along with a real world project using Twitter’s streaming API. After you’ve watched this course you’ll have a strong foundation for stream processing concepts using Apache Flink.

What you get

:

- Understanding Streaming Data and Stream Processing

- Implementing Basic Operations on Streaming Data

- Windowing Operations on Streams

- Fault Tolerance with State and Checkpoints

- Working with Multiple Stream Sources

- Exercise files