Introduction to Apache Spark

Categories: BIG DATA

About Course

Introduction to Apache Spark is a beginner-friendly course that helps you understand the architecture, components, and core programming model of Apache Spark one of the most powerful and widely-used Big Data tools today.

You’ll learn how Spark works under the hood, how it differs from Hadoop MapReduce, and how to build basic programs using Resilient Distributed Datasets (RDDs), DataFrames, and Spark SQL. Perfect for data enthusiasts, developers, and aspiring data engineers.

This course uses clear explanations, diagrams, and examples to help you get hands-on with Spark without needing prior Big Data experience.

What is Apache Spark and where is it used?
Spark architecture, components, and workflow
Difference between Spark and Hadoop MapReduce
Introduction to RDDs (Resilient Distributed Datasets)
Using Spark DataFrames and performing SQL queries
Basics of Spark MLlib and Spark Streaming
How Spark runs on clusters using YARN, Mesos, or standalone
How to write simple Spark programs in Python (PySpark)

Course Content

Module 1: Introduction to Apache Spark
What is Spark and why it’s important Ecosystem overview: Core, SQL, MLlib, Streaming, GraphX

Module 2: Spark Architecture Deep Dive
DAGs, Executors, Drivers, and Tasks Spark Cluster Modes and Resource Managers

Module 3: Working with RDDs
Creating, transforming, and persisting RDDs Actions vs. Transformations

Module 4: Spark SQL & DataFrames
Working with structured data Reading from CSV, JSON, and Parquet Querying with Spark SQL

Module 5: Introduction to MLlib and Streaming
Basic machine learning workflows in Spark Real-time data processing with Spark Streaming

Module 6: Hands-On Projects
Word count and log analysis Mini-project with real dataset (COVID-19, social media, or finance)

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Introduction to Apache Spark

About Course

What Will You Learn?

Course Content

Module 1: Introduction to Apache Spark
What is Spark and why it’s important Ecosystem overview: Core, SQL, MLlib, Streaming, GraphX

Module 2: Spark Architecture Deep Dive
DAGs, Executors, Drivers, and Tasks Spark Cluster Modes and Resource Managers

Module 3: Working with RDDs
Creating, transforming, and persisting RDDs Actions vs. Transformations

Module 4: Spark SQL & DataFrames
Working with structured data Reading from CSV, JSON, and Parquet Querying with Spark SQL

Module 5: Introduction to MLlib and Streaming
Basic machine learning workflows in Spark Real-time data processing with Spark Streaming

Module 6: Hands-On Projects
Word count and log analysis Mini-project with real dataset (COVID-19, social media, or finance)

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About Course

What Will You Learn?

Course Content

Module 1: Introduction to Apache Spark What is Spark and why it’s important Ecosystem overview: Core, SQL, MLlib, Streaming, GraphX

Module 2: Spark Architecture Deep Dive DAGs, Executors, Drivers, and Tasks Spark Cluster Modes and Resource Managers

Module 3: Working with RDDs Creating, transforming, and persisting RDDs Actions vs. Transformations

Module 4: Spark SQL & DataFrames Working with structured data Reading from CSV, JSON, and Parquet Querying with Spark SQL

Module 5: Introduction to MLlib and Streaming Basic machine learning workflows in Spark Real-time data processing with Spark Streaming

Module 6: Hands-On Projects Word count and log analysis Mini-project with real dataset (COVID-19, social media, or finance)

Student Ratings & Reviews

Trending Courses

Trending College Workshops

Company

Contact

Categories

Module 1: Introduction to Apache Spark
What is Spark and why it’s important Ecosystem overview: Core, SQL, MLlib, Streaming, GraphX

Module 2: Spark Architecture Deep Dive
DAGs, Executors, Drivers, and Tasks Spark Cluster Modes and Resource Managers

Module 3: Working with RDDs
Creating, transforming, and persisting RDDs Actions vs. Transformations

Module 4: Spark SQL & DataFrames
Working with structured data Reading from CSV, JSON, and Parquet Querying with Spark SQL

Module 5: Introduction to MLlib and Streaming
Basic machine learning workflows in Spark Real-time data processing with Spark Streaming

Module 6: Hands-On Projects
Word count and log analysis Mini-project with real dataset (COVID-19, social media, or finance)