https://github.com/learningjournal/spark-streaming-in-python

Apache Spark 3 - Structured Streaming Course Material
https://github.com/learningjournal/spark-streaming-in-python

apache-spark big-data bigdata data-lake pyspark python spark-sql spark-streaming

Last synced: 5 days ago
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Apache Spark 3 - Structured Streaming Course Material

• Host: GitHub
• URL: https://github.com/learningjournal/spark-streaming-in-python
• Owner: LearningJournal
• License: mit
• Created: 2020-07-21T15:04:21.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2023-08-19T11:44:44.000Z (about 1 year ago)
• Last Synced: 2024-09-28T07:03:53.701Z (5 days ago)
• Topics: apache-spark, big-data, bigdata, data-lake, pyspark, python, spark-sql, spark-streaming
• Language: Python
• Homepage: https://www.learningjournal.guru
• Size: 19.4 MB
• Stars: 120
• Watchers: 8
• Forks: 152
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Apache Spark 3 - Real-time Stream Processing using Python

This is the central repository for all the materials related to Apache Spark 3 -Real-time Stream Processing using Python 
Course by Prashant Pandey.


 You can get the full course at  

  Apache Spark Course @ Udemy.







 



 Description 



  I am creating Apache Spark 3 - Real-time Stream Processing using Python course to help you understand the Stream Processing using Apache Spark and apply that knowledge to build 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 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 and source code version



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.