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Data Engineering, PySpark, Coding exercise

What you will learn

Fundamentals of PySpark

Hands on experience in PySpark

Understanding of data using PySpark

Performing various operations on DataFrame

Description

This course will prepare you for a real world Data Engineer role !

Learn to code PySpark like a real world developer. Here our major focus will be on Practical applications of PySpark and bridge the gap between academic knowledge and practical skill.

In this course we will get to know and apply few of the most essential and basic functions in PySpark, that are used frequently in scripting for any project based on PySpark.

About PySpark:

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


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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!

What you will learn :

  • SparkSession and imports
  • Spark DataFrame and its characteristics
  • Syntax and example
  • Print results
  • Understanding the data
  • Number of records
  • Columns in dataFrame
  • Describe a DataFrame
  • Schema of a DataFrame
  • Create a new column
  • Arithmetic operations on Data
  • Change column data type
  • Create a column with integer as constant
  • Apply what we know
  • Rounding of digits
  • Sorting operation
  • Drop columns
  • Rename columns
  • Create a column with string as constant
  • Conditional Statements
  • Changing case of a column
  • Filter operations
  • Grouping and aggregations

Prerequisites :

  • Some basic programming skills (Not Mandatory)
  • Will to implement theoretical knowledge in pratical.

Who this course is for:

  • Beginners who want to learn Big Data or experienced people who want to transition to a Big Data role
  • Big data beginners who want to learn how to code in the real world
  • Aspiring candidates for data engineering role
English
language

Content

Introduction

Introduction
SparkSession and Imports
Spark DataFrame and its characteristics
Syntax and example
Print operation
Understanding the data
Number of records in DataFrame
Columns present in DataFrame
Summary of a DataFrame
Get schema of a DataFrame
Create a new column in a dataframe
Arithmetic operations on columns
Change column Data Types by casting
Create a column with integer constant
Application of the learnings
Rounding operations using bround
Sorting operation
Drop columns of a dataframe
Rename a column
Create a column with String constant
Conditional Statements
Changing Case of a column
Filter operations
Grouping and Aggegrations