Spark Programming in Python for Beginners - Apache Spark 3
Unlock the Power of Apache Spark 3
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What You Will Learn!
- Basic knowledge of Apache Spark
- Apache Spark installation and configuration on local machine as well as on cloud
- How to use Spar-shell
- Installation of multi-node cluster on Google Cloud Platform
- Using clusters in notebooks
- Creating and configuring spark session
- Creating Spark project Build Configuration
- Configuring spark application logs
- How to load different file formats in Dataframe
- Dataframe and Data sets transformations
- Aggregations in spark
- Spark Dataframe Joins
Description
Get ready for the Apache Spark with Python complete course. Gain familiarity with the course details and topics designed to help you succeed.
Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. This course is designed for students, professionals, and people in non-technical roles who are willing to develop a Data Engineering pipeline and application using Apache Spark. The managers and architects, who are not directly involved in the Spark implementation process, are another group of people. Still, they collaborate with those who really put Apache Spark into practice.
Learn Apache Spark with Hands-On Labs
The Spark Programming in Python course is a hands-on practice course designed to teach you the basic and intermediate concepts of spark via practical demonstration through hands-on labs. The course comprises approximately 22 labs starting from the basics and moving to high levels in terms of complexity.
Who should take this course?
The course is intended for software developers who want to build an Apache Spark-based data engineering pipeline and application. The data architects and data engineers who are in charge of creating the data-centric architecture for the company can also benefit from it. The managers and architects, who are not directly involved in the Spark implementation process, are another group of people. Still, they collaborate with those who really put Apache Spark into practice.
Requirements
● Basic Programming Knowledge Using Python Language
● A Recent 64-bit Windows/Mac/Linux Machine with 8 GB RAM
Who this course is for:
● Software Engineers and Architects who are willing to design and develop Big data Engineering Projects using Apache Spark
● Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark
What you’ll learn
● Basic knowledge of Apache Spark
● Apache Spark installation and configuration on the local machine as well as on the cloud
● How to use Spar-shell
● Installation of the multi-node cluster on the Google Cloud Platform
● Using clusters in notebooks
● Creating and configuring spark session
● Creating Spark project Build Configuration
● Configuring spark application logs
● How to load different file formats in a dataframe
● Dataframe and Data set transformations
● Aggregations in spark
● Spark dataframe Joins
Are there any course requirements or prerequisites?
● Basic Programming Knowledge Using Python Language
● A Recent 64-bit Windows/Mac/Linux Machine with 8 GB RAM
Who this course is for:
● Software Engineers and Architects who are willing to design and develop Big data Engineering Projects using Apache Spark
● Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark
Who Should Attend!
- Software Engineers and Architects who are willing to design and develop a Big data Engineering Projects using Apache Spark
- Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark