Introduction to Spark SQL and DataFrames
With Dan Sullivan
Liked by 1,697 users
Duration: 1h 54m
Skill level: Intermediate
Released: 5/30/2019
Course details
Explore DataFrames, a widely used data structure in Apache Spark. DataFrames allow Spark developers to perform common data operations, such as filtering and aggregation, as well as advanced data analysis on large collections of distributed data. With the addition of Spark SQL, developers have access to an even more popular and powerful query language than the built-in DataFrames API. In this course, instructor Dan Sullivan shows how to perform basic operations—loading, filtering, and aggregating data in DataFrames—with the API and SQL, as well as more advanced techniques that are easily performed in SQL. In this section of the course, Dan explains how to join data, eliminate duplicates, and deal with null or NA values. The lessons conclude with three in-depth examples of using DataFrames for data science: exploratory data analysis, time series analysis, and machine learning.
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Meet the instructor
Learner reviews
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Arvind Kumar
Arvind Kumar
GT Combustor Design/Analysis @Siemens Energy| Ex Quest-Rolls Royce| Ex GE Aviation | Ex ISRO l IITB l NIT A
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Karl-Heinz Hoffmann
Karl-Heinz Hoffmann
Head of Tech Ecosystem | Technology Strategist Specialized in Developing & Executing Go-To-Market Strategies
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Alejandro Cespedes
Alejandro Cespedes
Technology Specialist @TELUS & B.A. Peer tutor @UCW | MSc. Cyber Security | MBA | Electronic Eng.
Contents
What’s included
- Practice while you learn 1 exercise file
- Test your knowledge 4 quizzes
- Learn on the go Access on tablet and phone
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