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Learn Big Data Analysis with PySpark
Learn Big Data Analysis in PySpark using the Apache Spark's Powerful Features and Easy Commands of Python and SQL
This Course Includes
udemy
4.6 (23 reviews )
1h 55m 
english
Online - Self Paced
professional certificate
Udemy
About Learn Big Data Analysis with PySpark
Apache Spark
is one of the most powerful tools used in big data analysis because:
It’s
Run programs up to
100x
faster than Hadoop MapReduce in memory, or
10x
faster on disk. · It can run
real
and
semi-real
time data analysis. · It can handle
large scale
of data. · It can be run using simple code in
Python
programming language. You can use the easy commands in Python and SQL languages, to run data analysis on big data that cannot or difficult to import inside relational database engines. This combination of Spark, Python and SQL create a powerful work environment to analyze big data easier and faster. In this course, you will learn: What is Spark, how does it run, and how data are stored in Spark work environment. You will learn how to configure Python programming environment to run Spark code. Also, you will learn performing data analysis using real
big data. In addition, y
ou will learn to import
big data files
inside Python. You will learn to
clean
and
transform
data for analysis purpose. You will learn conducting business analysis using several
Spark
functions. You will learn to create
SQL
queries inside PySpark to run data analysis. After that you will learn how to interpret the results from business perspective.
What You Will Learn?
- Learn Most Important PySpark Features .
- Understand Resilient Distributed Dataset .
- Learn Most Important Python Commands and Libraries used for Data Analysis .
- Import Big Data Files in PySpark Work Environment and Clean them .
- Perform Data Analysis in PySpark using SQL Queries.