Description
Big Data Best Practices with PySpark & Spark Tuning is a PySpark Big Data training course published by the online academy Udemy. In this hands-on training course, you will become familiar with PySpark and learn how to work on various big data projects and exercises. You will also encounter many different types of distributed processing problems. This course is designed for people who want to learn PySpark through hands-on exercises and expand their knowledge and skills in big data analytics. In this course, you will work with Spark RDD, DF and SQL to process large volumes of data in the form of semi-structured, structured and unstructured data.
By identifying the most important skills needed in the industry, this course will teach you the content that will help you make a big impact and achieve great success in this great industry. This training course will not only introduce you to PySpark, but also introduce you to the challenges that exist when working with huge data, allowing you to be more successful in your work. After completing this training course, you will be proficient in PySpark and can use it to manage and analyze huge data.
What you’ll learn in Big Data Best Practices with PySpark and Spark Tuning:
- Understanding of Apache Spark structure, implementation model and programming.
- PySpark Practices
- Using RDD, DataFrame and SQL
- How to work with a free cloud system
- AND…
Course characteristics
Publisher: Udemy
Instructors: Amin Karami
English language
Level: from introductory to advanced
Number of lessons: 22
Duration: 10 hours 16 minutes
course topics
Best practices for working with big data with PySpark and prerequisites for setting up Spark
Very simple Python and SQL
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Images
Big Data Best Practices with PySpark and Spark Tuning Introductory Video
installation instructions
Once extracted, watch on your favorite player.
English subtitles
Quality: 720p
Download link
File password(s): free download software
size
5.3 GB