Duration: 4h 17m | Video: .MP4 1280x720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | Size: 1.66 GB
Genre: eLearning | Language: English

I am creating Apache Spark 3 - Real- Stream Processing using the Scala course to help you understand the Real- Stream processing using Apache Spark and apply that knowledge to build real- stream processing solutions.

Learn to create Real- Stream Processing applications using Apache Spark

Real- Stream Processing Concepts

Spark Structured Streaming APIs and Architecture

Working with File Streams

Working With Kafka Source and Integrating Spark with Kafka

State-less and State-full Streaming Transformations

Windowing Aggregates using Spark Stream

Watermarking and State Cleanup

Streaming Joins and Aggregation

Handling Memory Problems with Streaming Joins

Creating Arbitrary Streaming Sinks

Spark Fundamentals and exposure to Spark Dataframe APIs

Kafka Fundamentals and working knowledge of Apache Kafka

Programming Knowledge Using Scala Programming Language

A Recent 64-bit Windows/Mac/Linux Machine with 8 GB RAM

About the Course

This course is example-driven and follows a working session like approach. We will be taking a live coding approach and explain all the needed concepts along the way.

Who should take this Course?

I designed this course for software eeers willing to develop a Real- Stream Processing Pipeline and application using the Apache Spark. I am also creating this course for data architects and data eeers who are responsible for designing and building the organization's data-centric infrastructure. Another group of people is the managers and architects who do not directly work with Spark implementation. Still, they work with the people who implement Apache Spark at the ground level.

Spark Version used in the Course

This Course is using the Apache Spark 3.x. I have tested all the source code and examples used in this Course on Apache Spark 3.0.0 open-source distribution.

Software Eeers and Architects who are willing to design and develop a Bigdata Eeering Projects using Apache Spark

Programmers and developers who are aspiring to grow and learn Data Eeering using Apache Spark




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