Spark Structured Streaming 3.0 : All You Need to Know

Get to hands on from the first hour and travel through the concepts and details to emerge out master at the end

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Last Updated: 2022-05-03 10:05:11 English Course Type: Self Learning

In Depth exploration of Spark Structured Streaming 3.0 using Python API. We'll also introduce you to Apache Kafka on a high level in the process.

Getting faster action from the data is the need of many industries and Stream Processing helps doing just that. But it comes with its own set of theories, challenges and best practices.

Apache Spark has seen tremendous development being in stream processing. The rich features of Spark Structured Streaming introduces a learning curve and this course is aimed at bringing all those concepts in a friendly and easy to reflect manner.

You will learn the differences between batch & stream processing and the challenges specific to stream processing. Quickly we'll move to understand the concepts of stream processing with wide varieties of examples & hands-on, dealing with inner working and taking a use case towards the end. All of this activity will be on cloud using Spark 3.0.

Understanding of Spark SQL and Python (or pyspark) will be beneficial

Data Engineers looking to expand their skill set, Data Scientists who wish want hands on working with stream processing and Technical Architects who want to evaluate the Spark Structured Streaming for their use cases

Section 1 : First Steps with Spark Structured Streaming 4 Lectures 00:47:15
Lecture 1 :
Need and Challenges of Stream Processing Preview
Lecture 2 :
Concepts of Spark Structured Streaming
Lecture 3 :
Structure of Spark Structured Streaming Application
Lecture 4 :
Writing the first Structured Streaming Application
Section 2 : Resources 1 Lectures
Lecture 1 :
Links to resources
Section 3 : Deep dive into the structured streaming 4 Lectures 00:54:56
Lecture 1 :
Understanding output modes
Lecture 2 :
Windows in stream processing
Lecture 3 :
Watermarking in stream processing
Lecture 4 :
Quick Introduction to Kafka
Section 4 : Integrating Spark Structured Streaming with Kafka 2 Lectures 00:31:25
Lecture 1 :
Watermarking with Kafka Sourc
Lecture 2 :
Use Case: Get materialized advertisements by joining Kafka topics
Section 5 : Applying Structured Streaming in Production and Road to Expertise 3 Lectures 00:29:35
Lecture 1 :
Structured Streaming in Production
Lecture 2 :
System Designs involving Spark Structured Streaming
Lecture 3 :
Road to Expertise

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