* Cantinho Satkeys

Refresh History
  • FELISCUNHA: Votosde um santo domingo para todo o auditório  4tj97u<z
    24 de Novembro de 2024, 11:06
  • j.s.: bom fim de semana  49E09B4F
    23 de Novembro de 2024, 21:01
  • j.s.: try65hytr a todos
    23 de Novembro de 2024, 21:01
  • FELISCUNHA: dgtgtr   49E09B4F  e bom fim de semana
    23 de Novembro de 2024, 12:27
  • JPratas: try65hytr A Todos  101yd91 k7y8j0
    22 de Novembro de 2024, 02:46
  • j.s.: try65hytr a todos  4tj97u<z 4tj97u<z
    21 de Novembro de 2024, 18:43
  • FELISCUNHA: dgtgtr  pessoal   49E09B4F
    20 de Novembro de 2024, 12:26
  • JPratas: try65hytr Pessoal  4tj97u<z classic k7y8j0
    19 de Novembro de 2024, 02:06
  • FELISCUNHA: ghyt74   49E09B4F  e bom fim de semana  4tj97u<z
    16 de Novembro de 2024, 11:11
  • j.s.: bom fim de semana  49E09B4F
    15 de Novembro de 2024, 17:29
  • j.s.: try65hytr a todos  4tj97u<z
    15 de Novembro de 2024, 17:29
  • FELISCUNHA: ghyt74  pessoal   49E09B4F
    15 de Novembro de 2024, 10:07
  • JPratas: try65hytr A Todos  4tj97u<z classic k7y8j0
    15 de Novembro de 2024, 03:53
  • FELISCUNHA: dgtgtr   49E09B4F
    12 de Novembro de 2024, 12:25
  • JPratas: try65hytr Pessoal  classic k7y8j0 yu7gh8
    12 de Novembro de 2024, 01:59
  • j.s.: try65hytr a todos  4tj97u<z
    11 de Novembro de 2024, 19:31
  • cereal killa: try65hytr pessoal  2dgh8i
    11 de Novembro de 2024, 18:16
  • FELISCUNHA: ghyt74   49E09B4F  e bom fim de semana  4tj97u<z
    09 de Novembro de 2024, 11:43
  • JPratas: try65hytr Pessoal  classic k7y8j0
    08 de Novembro de 2024, 01:42
  • j.s.: try65hytr a todos  49E09B4F
    07 de Novembro de 2024, 18:10

Autor Tópico: Apache Spark 3 - Real-time Stream Processing using Scala  (Lida 121 vezes)

0 Membros e 1 Visitante estão a ver este tópico.

Online mitsumi

  • Moderador Global
  • ***
  • Mensagens: 117535
  • Karma: +0/-0
Apache Spark 3 - Real-time Stream Processing using Scala
« em: 23 de Dezembro de 2020, 10:14 »

Apache Spark 3 - Real-time Stream Processing using Scala
Duration: 4h17m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 1.66 GB
Genre: eLearning | Language: English
Learn to create Real-time Stream Processing applications using Apache Spark

What you'll learn
Real-time 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

Requirements
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

Description
About the Course

I am creating Apache Spark 3 - Real-time Stream Processing using the Scala course to help you understand the Real-time Stream processing using Apache Spark and apply that knowledge to build real-time stream processing solutions. 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 engineers willing to develop a Real-time Stream Processing Pipeline and application using the Apache Spark. I am also creating this course for data architects and data engineers 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.

Who this course is for:
Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark
Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark
Download link:
Só visivel para registados e com resposta ao tópico.

Only visible to registered and with a reply to the topic.

Links are Interchangeable - No Password - Single Extraction