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    The Ultimate Kafka Streams (3.x) : Real-time Data Processing

    Posted By: lucky_aut
    The Ultimate Kafka Streams (3.x) : Real-time Data Processing

    The Ultimate Kafka Streams (3.x) : Real-time Data Processing
    Duration: 7h 31m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 3.9 GB
    Genre: eLearning | Language: English

    Apache Kafka Streams: Stateless Streams, Stateful Streams, KTable, Window, Statestore, RocksDB,Real-Time data analysis

    What you'll learn:
    Fullly understand Real-Time data process model of Kafka Streams
    In Depth understand Kafka Streams stateless operation
    In Depth understand Kafka Streams stateful operation
    In Depth understand Kafka Streams KTable & GlobalKTable
    Build Complex Event Process Application
    Rocksdb and statestore in Kafka Streams

    Requirements:
    Java(1.8+) Development Experiences
    Apache Kafka Fundamental Knowledge
    Big Data Development Experiences
    Apache Maven project build tools

    Description:
    **** Please enable the vedio cc function (captions ) *****
    First of all, welcome to enroll this course. This is a course about Kafka Streams. In this course, every knowledge detail of the Kafka Streams framework is introduced in great detail. Secondly, I sincerely hope that you can enable the vedio cc function (captions ) , because my native language is not English, the spoken language is not very standard, but I assure you that the course content is absolutely detailed and step by step,From shallow to deep.

    Kafka Streams is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.

    [Pre-Requisites]
    You should have the Java development experiences(***this is mandatory requirement***)
    You should have the Kafka foundation knowledge(***this is mandatory requirement***)
    It's better have another streaming develop experiences such as Spark Streaming, Storm, Flink

    【Course Characteristics】
    Driven by source code
    Lots of practices
    From shallow to deep
    Absolutely detailed and step by step
    Covers all knowledge points of Kafka Streams framework
    Rich comprehensive cases

    [Course Agenda]
    Introduce the Kafka Streams
    Tutorial the Kafka Streams key terms and concepts
    Kafka Streams Parallel Mode
    Stateless operation of map transform
    Stateless operation of mapValues transform
    Stateless operation of flatMap transform
    Stateless operation of flatMapValues transform
    Stateless operation of selectKey transform
    Stateless operation of foreach
    Stateless operation of Print&Peek
    Stateless operation split & merge & BranchedKStream
    How to custom Serdes
    XMall Transaction data real-time analysis practise
    Tutorial the kafka stateful operation and statestore
    Explain in details of internal data redistribution and stateful transform
    Stateful operation of Joining(inner join/left join/outer join)
    Stateful operation of grouping
    Stateful operation of aggregation(count,reduce,aggregate)
    Build Real-time analysis the sales champion application
    Build Real-time analysis the sales stats application
    Stateful KStream Queryable Storestore
    Stateful TimeWindowedKStream Queryable state store for interactive
    KGroupedStream windowing operation
    Time Semantics and custom TimestampExtractor
    Tumbling time window for analysis of Potential Cyber Attacks
    Hopping time window for Site Visit real-time statistics
    Heartbeat sensor data real-time analysis for patient health monitoring
    What is KTable and how to create the KTable
    KTable basis operation such as map values, filtering
    KTable basis stateful operation transformValues implement the shooting game
    KStream inner&left join the KTable enrichment/enhancement the orginal records
    KTable inner join, inner foreign key with other KTable
    KTable left join, left foreign join, outer join KTable
    KTable & KGroupedTable aggregating operation such as count/reduce/aggregate

    [Course Objectives]
    Fully understand the kafka Streams concepts and key terms
    Fully understand the kafak Streams parallel mode
    Master the stateless streams application building and in depth understand every stateless operation
    Master the stateful streams application building and in depth understand every stateful operation
    Master the internal data distribution underlying mechanism
    Master the statestore, can base on the statestore build complex event process real-time application
    Fully understand the KTable and Windowing operation

    Hope you will enjoy this course, After learning this course, you will become an expert in Kafka Streams, and ability to build complex event process(CEP) real-time application based on Kafka Streams framework.

    Who this course is for:
    Big Data Developer
    Senior Java/Scala/Groovy/Clojure Developer
    Kafka Engineer
    Big Data Engineer

    More Info

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