Udemy – Master Apache Spark using Spark SQL and PySpark 3 2022-8 – Downloadly

Description

Master Apache Spark using Spark SQL and PySpark 3 is an Apache Spark software training course published by Udemy Online Academy. In this training course, you will learn about Apache Spark using Spark SQL and PySpark 3. Apache Spark is an open-source distributed computing system that provides a fast and general-purpose cluster computing framework for large-scale data processing. It was developed to overcome the limitations of the MapReduce model and is designed for ease of use, speed, and versatility. Apache Spark has gained popularity due to its performance, ease of use, and flexibility in processing large data sets. Apache Spark software has evolved as a leading technology for taking care of large-scale data engineering.

This training course has a variety of exercises that help you learn the topics. In this training course, you will get to know Spark SQL and PySpark 3 and understand their basic concepts and principles. Knowledge of working with Python is required for this training course. For this reason, a section has been included in this training course for this purpose so that those of you who have no knowledge of Python can use it and acquire the necessary skills. After becoming fully familiar with Spark SQL, PySpark 3, and Python, you will be familiar with the Apache Spark software, and with it you will be able to manage a large set of data.

What you will learn in Master Apache Spark using Spark SQL and PySpark 3:

Setting up Single Node Hadoop and Spark using Docker
Basic concepts and principles of Python
Processing data in a DataFrame using Spark SQL
Apache Spark Application Development Life Cycle
And…

Course Specifications

Publisher: Udemy
coach: Durga Vishwanath Raju Gadiraju And Naga Bhuvaneshwar
language English
Level: Introductory to advanced
Number of lessons: 346
Duration: 32 hours and 11 minutes

Course Subjects

Master Apache Spark using Spark SQL and PySpark 3 Stuff

Master Apache Spark using Spark SQL and PySpark 3 Prerequisites

Basic programming skills using any programming language
Self-help lab (instructions provided) or ITversity lab at additional cost for suitable environment.
Minimum memory requirement depending on the environment you are using with 64 bit operating system
4 GB RAM with access to a proper cluster or 16 GB RAM to setup environment using Docker