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Kafka Streams API For Developers using Java/SpringBoot 3.X

سرفصل های دوره

Master the Kafka Streams API to build advanced real time Kafka Streaming applications using Java and SpringBoot 3.x.


1. Getting Started With the Course
  • 1. Course Introduction
  • 2. Pre-requestites

  • 2. Getting Started to Kafka Streams
  • 1. Introduction to Kafka Streams
  • 2. Kafka Streams Terminologies - Topology & Processor
  • 3. Introduction to KStreams API

  • 3. Greetings Kafka Streams App using KStreams API
  • 1. Overview of the Greetings App
  • 2.1 2.2-greetings-app-setup.zip
  • 2.2 Github Link.html
  • 2. Setup the Greetings App
  • 3.1 2.3-greetings-app-topology.zip
  • 3. Topology of the Greetings App
  • 4.1 2.4-greetings-launcher-app.zip
  • 4. Build the Kafka Streams Launcher Application
  • 5.1 2.5-kafka-setup-test.zip
  • 5. Setting Up Kafka Environment and Test our Greeting App

  • 4. Operators in Kafka Streams using KStream API
  • 1.1 3.1-filter-filternot.zip
  • 1. Filter & FilterNot
  • 2.1 3.2-map.zip
  • 2. MapMapValues
  • 3.1 3.3-flatMap-flatmapValues.zip
  • 3. FlatMapValuesFlatMap
  • 4.1 3.4-peek.zip
  • 4. peek
  • 5.1 3.5-merge.zip
  • 5. merge

  • 5. Serialization and Deserialization in Kafka Streams
  • 1. How KeyValue serialization and deserialization works in Kafka Streams
  • 2.1 4.1.1-serdes-config.zip
  • 2. Providing Default SerializerDeserializer using Application Configuration
  • 3.1 4.2-custom-serdes.zip
  • 3. Build a Custom Serdes for Enhanced Greeting Messages
  • 4.1 4.3-integrate-custom-serdes.zip
  • 4. Usage of CustomSerde in the Greeting App

  • 6. Reusable Generic SerializerDeserializer (Recommended Approach)
  • 1.1 4.4-build-generic-serdes.zip
  • 1. Build a Generic SerializerDeserializer
  • 2.1 4.5-integrate-generic-serdes.zip
  • 2. Integrate Generic SerializerDeserializer into the Greeting App

  • 7. Order Management Kafka Streams application - A real time use case
  • 1.1 5.1-overview-of-retail-app.zip
  • 1. Overview of the Retail App
  • 2.1 5.2-orders-topology.zip
  • 2. Build the Topology for the Orders Management App
  • 3.1 5.3-branch-split-retail-app.zip
  • 3. Split the RestaurantRetail Shopping Orders - Using split and branch operator
  • 4.1 5.4-transform-order-revenue.zip
  • 4. Transform the Order Domain to a Revenue Domain Type

  • 8. Topology, Stream and Tasks - Under the Hood
  • 1. Internals of Topology, Stream and Tasks
  • 2.1 6.2-streams-modify-property.zip
  • 2. Explore the behavior of streams by modifying the stream threads

  • 9. ErrorException Handling in Kafka Streams
  • 1. Failures in Kafka Streams
  • 2.1 6.4-default-deserialization-error-handler.zip
  • 2. Default Deserialization Error Behavior
  • 3.1 6.5-custom-deserialization-error-handler.zip
  • 3. Custom Deserialization Error Handler
  • 4.1 6.6-default-custom-processor-error-handler.zip
  • 4. Default & Custom Processor Error Handler
  • 5.1 6.7-default-custom-production-handler.zip
  • 5. Custom Production Error Handler
  • 6. Error handling when Kafka Cluster is down

  • 10. KTable & Global KTable
  • 1. Introduction to KTable API
  • 2.1 7.2-ktable-handson.zip
  • 2. Build a topology for KTable
  • 3. KTable - Under the Hood
  • 4. Assignment - Implement the mapValues operator in KTable.html
  • 5.1 7.4-global-k-table.zip
  • 5. GlobalKTable

  • 11. StateFul Operations in Kafka Streams - Aggregate, Join and Windowing Events
  • 1. StateFul Operations in Kafka Streams
  • 2.1 8.2-aggregation-count.zip
  • 2. What is Aggregation & How it works
  • 3.1 8.2.1-aggregation-count-groupby.zip
  • 3. Aggregation using count operator
  • 4.1 8.3-aggregation-reduce.zip
  • 4. Aggregation using reduce operator
  • 5.1 8.4-aggregation-aggregate.zip
  • 5. Aggregation using aggregate operator
  • 6.1 8.5-count-reduce-materialized-views.zip
  • 6. Using Materialized Store for count & reduce operator

  • 12. StateFul Operation Results - How to access them
  • 1. How to access the results of Aggregation

  • 13. Aggregation in Order Management Application - A Real Time Use Case
  • 1.1 9.1-order-management-count.zip
  • 1. Total number of orders by each store using count operator
  • 2.1 9.2-order-management-aggregate.zip
  • 2. Total Revenue by each store using aggregate operator

  • 14. Re-Keying Kafka Records for Stateful operations
  • 1.1 10.1-null-keys-in-stateful-operations.zip
  • 1. Effect of null Key in Stateful Operations & Repartition of Kafka Records
  • 2.1 10.2-rekey-selectkey.zip
  • 2. Re-Keying using the selectKey operator

  • 15. StateFul Operations in Kafka Streams - Join
  • 1. Introduction to Joins & Types of Joins in Kafka Streams
  • 2.1 11.2-join-kstream-ktable.zip
  • 2. Explore innerJoin using join operator - Joining KStream and KTable
  • 3.1 11.3-join-kstream-globalktable.zip
  • 3. Explore innerJoin using join operator - Joining KStream and GlobalKTable
  • 4.1 11.4-join-ktable-ktable.zip
  • 4. Explore innerJoin using join operator - Joining KTable and KTable
  • 5.1 11.5-join-kstream-kstream.zip
  • 5. Explore innerJoin using join operator - Joining KStream and KStream
  • 6.1 11.6-leftjoin.zip
  • 6. Joining Kafka Streams using leftJoin operator
  • 7.1 11.7-outerjoin.zip
  • 7. Joining Kafka Streams using outerJoin operator
  • 8.1 11.8-under-the-hood.zip
  • 8.2 Kafka Commands Link.html
  • 8. Join - Under the hood
  • 9.1 11.9-co-partioning.zip
  • 9. CoPartitioning Requirements in Joins

  • 16. Join in Order Management Application - A Real Time Use Case
  • 1. Join Aggregate Revenue with StoreDetails KTable
  • 2. Join Aggregate Count with Stores KTable.html

  • 17. StateFul Operations in Kafka Streams - Windowing
  • 1. Introduction to Windowing and time concepts
  • 2.1 13.2-tumbling-windows.zip
  • 2. Windowing in Kafka Streams - Tumbling Windows
  • 3.1 13.3-supress.zip
  • 3. Control emission of windowed results using supress operartor
  • 4.1 13.4-hopping-windows.zip
  • 4. Windowing in Kafka Streams - Hopping Windows
  • 5.1 13.5-sliding-windows.zip
  • 5. Windowing in Kafka Streams - Sliding Windows

  • 18. Widowing in Order Management Application - A Real Time Use Case
  • 1. New Requirements for the Order Management Application
  • 2.1 14.2-custom-timestamp-extractor.zip
  • 2. Implementing a CustomTimeStamp Extractor
  • 3.1 14.3-aggregate-orders-by-windows.zip
  • 3. Aggregate Number of Orders by Windows
  • 4.1 14.4-aggregate-orders-by-windows.zip
  • 4. Aggregate Revenue by Windows
  • 5.1 14.5-joins-inwindowed-data.zip
  • 5. Joins on the Windowed Data

  • 19. Behavior of Records with Future & Older Timestamp in Windowing
  • 1.1 16.1-timestamp-behavior.zip
  • 1. Records with timestamps before & after the CurrentTimestamp.

  • 20. Build Kafka Streams Application using SpringBoot
  • 1. Introduction to SpringBoot and Kafka Streams
  • 2.1 17.2-set-up-springboot-kafka-streams.zip
  • 2. Setup the Project - Greeting Streams app using Spring Kafka Streams
  • 3.1 17.3-configure-spring-kafka-streams.zip
  • 3. Configuring the Kafka Stream using application.yml
  • 4.1 17.4-spring-kafka-streams-topology.zip
  • 4. Build the Greeting Topology
  • 5.1 17.5-test-spring-kafka-streams.zip.zip
  • 5. Test Greeting App in Local

  • 21. SpringBoot AutoConfiguration of Kafka Streams
  • 1. Internals of AutoConfiguring Kafka Streams in SpringBoot

  • 22. JSON SerializationDeserialization in Spring Kafka Streams
  • 1.1 18.1-custom-serialization-deserialization.zip
  • 1. JSON SerializationDeserialization using JsonSerde
  • 2.1 18.2-jackson-custom-objectmapper.zip
  • 2. JsonSerde using custom ObjectMapper

  • 23. Error Handling in Spring Kafka Streams
  • 1.1 19.1-spring-deserialization-approach1.zip
  • 1. Handle DeSerialization Error - Approach 1
  • 2.1 19.2-spring-deserialization-approach2.zip
  • 2. Handle DeSerialization Error using Custom Error Handler - Approach 2
  • 3.1 19.3-spring-deserialization-approach3.zip
  • 3.2 Spring for Kafka Reference Link.html
  • 3. Handle DeSerialization Errors using Spring Specific Approach- Approach 3
  • 4.1 19.4-spring-uncaught-exception.zip
  • 4. Handle UncaughtExceptions in the Topology
  • 5.1 19.5-spring-production-errors.zip
  • 5. Handle Production Errors

  • 24. Build Orders Kafka Streams Application using SpringBoot
  • 1. Set up the base project for Orders Kafka Streams App
  • 2.1 20.2-orders-streams-setup-topology.zip
  • 2. Create the OrdersTopology

  • 25. Interactive Queries - Querying State Stores using RESTFUL APIs
  • 1.1 21.1-get-endpoint-orderCount-part1.zip
  • 1. Build a GET Endpoint to retrieve the OrderCount by OrderType - Part 1
  • 2.1 21.1-get-endpoint-orderCount-part2.zip
  • 2. Build a GET Endpoint to retrieve the OrderCount by OrderType - Part 2
  • 3.1 21.2-get-endpoint-orderCount.zip
  • 3. Retrieve OrderCount by OrderType & LocationId
  • 4.1 21.3-get-endpoint-all-ordercount.zip
  • 4. Build a GET Endpoint to retrieve the OrderCount for All OrderTypes
  • 5.1 21.4-get-endpoint-orderRevenue.zip
  • 5. Build a GET Endpoint to retrieve the Revenue by OrderType
  • 6.1 21.5-global-error-handler.zip
  • 6. Global Error Handling for useful Client Error Messages
  • 7. Assignment Retrieve Revenue by OrderType & LocationId.html

  • 26. Interactive Queries - Querying Window State Stores using RESTFUL APIs
  • 1.1 22.1-get-windows-order-count-bytype.zip
  • 1. Build a GET Endpoint to Retrieve OrderCount by OrderType
  • 2.1 22.2-get-windows-order-count-all-types.zip
  • 2. Build a GET Endpoint to Retrieve the windowed OrderCount for All OrderTypes
  • 3.1 22.3-get-windows-order-count-within-range.zip
  • 3. Build a GET endpoint to retrieve the windowed OrderCount within a Time Range
  • 4. Build a GET Endpoint to retrieve the Revenue by OrderType

  • 27. Testing Kafka Streams Using TopologyTestDriver & JUnit5
  • 1.1 Testing Streams Code.html
  • 1. Testing Kafka Streams using TopologyTestDriver
  • 2.1 23.2-unit-testing-greetings-app.zip
  • 2. Unit Testing Greetings App - Writing Data to a Output Topic
  • 3.1 23.3-unit-testing-greetings-app-multiple-messages.zip
  • 3. Unit Testing Greetings App - Testing Multiple Messages
  • 4.1 23.4-unit-testing-greetings-app-error.zip
  • 4. Unit Testing Greetings App - Error Scenario
  • 5.1 23.5-unit-testing-orders-count.zip
  • 5. Unit Testing OrdersCount - Writing Data to a State Store
  • 6.1 23.6-unit-testing-orders-Revenue.zip
  • 6. Unit Testing OrdersRevenue - Writing Data to a State Store
  • 7.1 23.7-unit-testing-orders-Revenue-by-windows.zip
  • 7. Unit Testing OrdersRevenue By Windows - Writing Data to a State Store
  • 8.1 23.8-topology-test-driver-limitations.zip
  • 8. Limitations of TopologyTestDriver

  • 28. Testing Kafka Streams in SpringBoot Using TopologyTestDriver & JUnit5
  • 1.1 24.1-topologyTestdriver-springboot.zip
  • 1. UnitTest Using TopologyTestDriver in SpringBoot

  • 29. Integration Testing Spring KafkaStreams App using @EmbeddedKafka
  • 1.1 25.1-intg-test.zip
  • 1. Introduction & SetUp Integration Test
  • 2.1 25.2-intg-test-orders-count.zip
  • 2. Integration Test for OrdersCount
  • 3.1 25.3-intg-test-orders-revenue.zip
  • 3. Integration Test for OrdersRevenue
  • 4.1 25.4-intg-test-orders-revenue-by-windows.zip
  • 4. Integration Test for OrdersRevenue By Windows

  • 30. Grace Period in Kafka Streams
  • 1.1 26.1-grace-period.zip
  • 1. Grace Period in Windowing

  • 31. Build and Package the SpringBoot App as an Executable
  • 1.1 27.1-kafka-streams-jar.zip
  • 1. Package the SpringBoot app and execute it as a Jar File
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