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19 Understand and Optimize Shuffle in Spark 

Ease With Data
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Video explains - How Shuffle works in Spark ? How to optimize Shuffle in Spark ?
Chapters
00:00 - Introduction
00:20 - Understand Pipelining in Spark
02:18 - Demonstration
11:40 - Performance with Partitioned Data
14:19 - Few More Tips
Local PySpark Jupyter Lab setup - • 03 Data Lakehouse | Da...
Python Basics - www.learnpython.org/
GitHub URL for code - github.com/subhamkharwal/pysp...
The series provides a step-by-step guide to learning PySpark, a popular open-source distributed computing framework that is used for big data processing.
New video in every 3 days ❤️
#spark #pyspark #python #dataengineering

Опубликовано:

 

15 июл 2024

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Комментарии : 5   
@anveshkonda8334
@anveshkonda8334 День назад
Thanks a lot for sharing. It will be very helpful if you add data directory in git hub repo
@at-cv9ky
@at-cv9ky 5 месяцев назад
great, explanation ! and the article in the comments section is too good.
@sarthaks
@sarthaks 6 месяцев назад
To your statement "to avoid un-necessary shuffle wherever necessary", can you give some example or scenarios..
@easewithdata
@easewithdata 6 месяцев назад
Checkout this article - blog.devgenius.io/pyspark-worst-use-of-window-functions-f646754255d2 An example of un-necessary use of shuffle
@sarthaks
@sarthaks 6 месяцев назад
@@easewithdata very very useful.. thanks for sharing the details
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