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Spark with Python

What you will learn

PySpark Foundation

PySpark Core Programming – RDD Programming

PySpark SQL – DataFrames, DSL and Native SQL

PySpark Streaming Programming

PySpark Integrations

Description

Learn the latest Big Data Technology – Spark! And learn to use it with one of the most popular programming languages, Python!

One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!

Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!

This course will teach the basics with a crash course in Python, continuing on to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! Once we’ve done that we’ll go through how to use the MLlib Machine Library with the DataFrame syntax and Spark. All along the way you’ll have exercises and Mock Consulting Projects that put you right into a real world situation where you need to use your new skills to solve a real problem!


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We also cover the latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees! After you complete this course you will feel comfortable putting Spark and PySpark on your resume! This course also has a full 30 day money back guarantee and comes with a LinkedIn Certificate of Completion!

If you’re ready to jump into the world of Python, Spark, and Big Data, this is the course for you!

Who this course is for:

  • Someone who knows Python and would like to learn how to use it for Big Data
  • Someone who is very familiar with another programming language and needs to learn Spark
English
language

Content

PySpark Foundation

1 What is Spark
2 Spark vs MapReduce part 1
3 Spark vs MapReduce part 2
4 Spark vs MapReduce part 3
5 Spark vs MapReduce part 4
6 Spark Components
7 Spark Job Roles or Opportunities
8 PySpark Developer Content
9 PySpark Development Environment
10 PySpark Runtime Environment
11 PySpark Development Environment Setup
12 Java Installation
13 Scala Installation
14 Python Installation
15 Spark Installation part 1
16 Spark Installation part 2
17 PySpark Programming Introduction part 1
18 PySpark Programming Introduction part 2
19 First PySpark Program using pyspark shell
20 First PySpark Program using jupyter notebook part 1
21 First PySpark Program using jupyter notebook part 2
22 First PySpark Program using jupyter notebook part 3
23 First PySpark Application in Script Mode using PyCharm part 1
24 First PySpark Application in Script Mode using PyCharm part 2
25 Interactive Mode vs Script Mode
26 Spark Architecture part 1
27 Spark Architecture part 1
28 Spark Architecture — Local Mode part 1
29 Spark Architecture — Local Mode part 2

Spark Installation and Configuration on Windows

1 Spark Installation Introduction
2 Java 8 Installation
3 Scala 2.13 Installation
4 Python 3.10 Installation
5 Spark Installation
6 How to Become Spark Developer