Apache Kafka Crash Course for Java and Python Developers
What you’ll learn
Kafka Basics: Key Architecture Components and Data Flow
Kafka Admin Client API (Java in Spring for Kafka and Python kafka-python)
Kafka Producer Client API (Java in Spring for Kafka and Python kafka-python)
Kafka Consumer Client API (Java in Spring for Kafka and Python kafka-python)
Schema Registry (Java in Spring for Kafka and Python confluent-kafka)
Kafka Connect for Data Pipelining into and out of Kafka
Overview of Stream Processing with Kafka
Kafka Streams in Java and Spring for Kafka
Faust Stream Processing with Python
Requirements
Basic understanding of Docker along with comfortability using the CLI and familiarity with either Java or Python programming languages.
Description
A fast track to gain the skills needed to work with Apache Kafka as a Java or Python Software Engineer by taking the Kafka Crash Course developed and presented by a 2X Confluent Kafka Certified Engineer!In this course students, Java or Python Software Developers, will be taken on a fast track journey to attaining skills required to harness the amazing power of Apache Kafka. Students gain the practical knowledge to build loosely coupled distributed systems that scale to insane levels of throughput while maintaining unprecedented resiliency. Topics covered include:Kafka Basics of Key Architecture Components and Data FlowKafka Admin API (In Java with Spring for Kafka as well as in Python)Kafka Producer API (In Java with Spring for Kafka as well as in Python)Kafka Consumer API(In Java with Spring for Kafka as well as in Python)Confluent Schema Registry (In Java with Spring for Kafka as well as in Python)Kafka Connect to Import and Export Data to/from Kafka from Common Source/Sink SystemsOverview of Stream Processing Basics with Kafka (Kafka Streams in Java and Faust Streams Python Framework)The Apache Kafka Crash Course for Java and Python Developers is specifically designed for quickly getting Developers up to speed using Apache Kafka to be prepared for upcoming interviews or make timely yet significant contributions implementing Apache Kafka pub/sub messaging or event streaming in their current roles. The course provides a balance of fundamental theory on the inner workings of Apache Kafka’s storage mechanism along with the know how to tune producer and consumer applications for performance and resiliency. This course is packed full of practical examples with code samples for putting the theoretical content into practice in two of the most popular languages used in industry, Java and Python.
Overview
Section 1: Introduction
Lecture 1 Course Introduction
Lecture 2 Overview
Lecture 3 Format
Lecture 4 Outline
Lecture 5 About Course Instructor
Section 2: Kafka Architecture Foundations and Data Flow
Lecture 6 Introduction
Lecture 7 Why Apache Kafka?
Lecture 8 50K Foot View of Kafka
Lecture 9 10K Foot View of Kafka
Lecture 10 1K Foot View of Kafka
Lecture 11 Anatomy of a Message
Lecture 12 Kafka Default Topic Storage
Lecture 13 Kafka Compacted Topics
Lecture 14 Kafka APIs
Lecture 15 Kafka API Implementation Languages
Lecture 16 Dockerized Dev Environment Setup
Section 3: Kafka Admin API
Lecture 17 Admin API Introduction
Lecture 18 CLI to Manage Topics
Lecture 19 CLI to Manage Topics Continued (Advanced Configurations)
Lecture 20 Python to Create Topics
Lecture 21 Python Create and Alter Topics with Advanced Configurations
Lecture 22 Java (Spring for Kafka) to Create Topics
Lecture 23 Java (Spring for Kafka) to Create and Alter Topics with Advanced Configurations
Section 4: Kafka Producer API
Lecture 24 Producer API Introduction
Lecture 25 Producers at a High Level
Lecture 26 Producers and their Influence on Message Partition Assignment
Lecture 27 CLI Tools for Producing Messages to Kafka
Lecture 28 Basic Producer in Python
Lecture 29 Basic Producer in Java (Spring for Kafka)
Lecture 30 Basic Producer in Java Alt Configuration (Spring for Kafka)
Lecture 31 Detailed Overview of Kafka Producer
Lecture 32 Changing Partitions Change Ordering
Lecture 33 Advanced Producer in Python
Lecture 34 Advanced Producer in Java (Spring for Kafka)
Section 5: Kafka Consumer API
Lecture 35 Consumer API Introduction
Lecture 36 Consumer Group Offsets and Progress Tracking
Lecture 37 Consumer Group Rebalances
Lecture 38 Basic Consumer in Python
Lecture 39 Basic Consumer in Java (Spring for Kafka)
Lecture 40 Auto Offset Commits and At Least Once Processing
Lecture 41 Manual Offset Commits and At Least Once Processing
Lecture 42 Manual Offset Commits and At Most Once Processing
Lecture 43 Manual Offset Commits and Exactly Once Processing
Lecture 44 Advanced Consumer in Python
Lecture 45 Advanced Consumer in Java (Spring for Kafka)
Lecture 46 Viewing Consumer Group Offsets
Lecture 47 Updating Consumer Group Offsets
Section 6: Schema Registry
Lecture 48 Schema Registry Introduction
Lecture 49 What is Confluent Schema Registry
Lecture 50 Why use Confluent Schema Registry
Lecture 51 How Schema Registry Fits into Kafka Architecture
Lecture 52 Quick Overview of Apache Avro
Lecture 53 Schema Registry Compatibility Settings and Schema Evolution Checks
Lecture 54 Java Demo Part 1: Avro Library Project Setup
Lecture 55 Java Demo Part 2: Integrating Avro and Schema Registry in a Producer Application
Lecture 56 Java Demo Part 3: Integrating Avro and Schema Registry on a Consumer Application
Lecture 57 Java Demo Part 4: Evolving the Schema
Lecture 58 Python Demo Part 1: Integrating Avro and Schema Registry in a Producer
Lecture 59 Python Demo Part 2: Integrating Avro and Schema Registry in a Consumer
Lecture 60 Python Demo Part 3: Evolving the Schema
Lecture 61 Overview of Schema Registry REST API
Section 7: Kafka Connect
Lecture 62 Kafka Connect Introduction
Lecture 63 What is Kafka Connect
Lecture 64 Why use Kafka Connect
Lecture 65 How Kafka Connect Fits into Systems and Data Architecture
Lecture 66 Conceptual Overview of a Connect Cluster and Starting a Connector Plugin
Lecture 67 Setting Up Datagen Connector in Docker
Lecture 68 Configuring and Starting a Datagen Connector via REST API
Lecture 69 Using REST API to Manage Datagen Connector
Lecture 70 Kafka Connect Sink Demo with MongoDB
Section 8: Stream Processing with Kafka Streams in Java
Lecture 71 Stream Processing Introduction
Lecture 72 What is Kafka Streams
Lecture 73 Streams and Tables
Lecture 74 Stateless and Stateful Transformations
Lecture 75 Processing Topologies
Lecture 76 Input Partitions Still Drive Parallelism and Throughput
Lecture 77 Java Stream Processing Demo Setup
Lecture 78 Java Stream Demo: Order Validation Service
Lecture 79 Java Streams Demo: Customer Revenue Service
Lecture 80 Tumbling Windows
Lecture 81 Sliding Windows
Lecture 82 Session Windows
Section 9: Stream Processing with Faust in Python
Lecture 83 Section Introduction
Lecture 84 What is Faust
Lecture 85 Key Data Constructs of Faust Library
Lecture 86 Types of Streaming Computations
Lecture 87 Faust Channels, Topics, Streams and Agents
Lecture 88 Demo: Install and Setup Faust & Agents and Topics
Lecture 89 Faust Tasks and Timers
Lecture 90 Demo: Faust Tasks and Timers
Lecture 91 Producing to Topics and Processing Streams in Faust
Lecture 92 Demo: Simple Faust Producer Consumer
Lecture 93 Processing Complex Types in Faust
Lecture 94 Demo: Producing and Consuming Complex Types
Lecture 95 Working with Tables in Faust
Lecture 96 Demo: Calculating Aggregates using Faust Tables
Lecture 97 Understanding that Kafka Topic Partitions Still Drive Parallelism in Faust
Software Developers and Software Architects with experience programming in Java or Python interested in using Kafka for building robust, scalable, decoupled systems.
Course Information:
Udemy | English | 12h 3m | 5.60 GB
Created by: Adam McQuistan
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