Apache Spark with Scala: Master Data Building & Analysis

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Apache Spark with Scala: Master Data Building & Analysis

This course is part of Spark and Python for Big Data with PySpark Specialization

Instructor: EDUCBA

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

9 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

9 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Apply Scala fundamentals including variables, functions, and advanced concepts.
Implement Spark RDD operations, streaming, and fault-tolerant pipelines.
Build real-time big data solutions integrating Spark with external systems.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments

Taught in English

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This course is part of the Spark and Python for Big Data with PySpark Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 2 modules in this course

This course provides a complete journey into Apache Spark with Scala, designed for learners who want to analyze, design, implement, and evaluate big data applications. Beginning with the foundations of Spark architecture and Scala programming, learners will explore variables, functions, collections, and advanced Scala concepts such as traits, abstract classes, and exception handling. The course then advances into Spark RDD operations, streaming, windowing, and checkpointing, helping learners apply distributed transformations and implement real-time data pipelines. Finally, learners will construct integrated projects using Maven, connect Spark to external systems like Twitter APIs, and evaluate the impact of Hadoop 1.x vs 2.x in managing resources for scalable applications.

This module introduces learners to the fundamentals of Apache Spark and the Scala programming language, equipping them with the foundational knowledge to build and manage big data applications. Starting with an overview of Spark’s architecture, flow, and integration with YARN, the module progresses to Scala essentials, covering variables, functions, loops, and collections. It then advances into key Scala concepts such as abstract classes, traits, exception handling, and access modifiers. By the end of this module, learners will be able to confidently apply Scala programming constructs within Spark environments to process and analyze data efficiently.

What's included

24 videos4 assignments

24 videosTotal 188 minutes

Introduction to Connecting to Twitter Using Spark9 minutes
Flowchart of Spark6 minutes
Components of Spark8 minutes
Different Services Running on YARN8 minutes
Introduction to Scala6 minutes
Case Classes and Pattern Matching7 minutes
Installation of Scala7 minutes
Variables and Functions7 minutes
Variables and Functions Continues5 minutes
Loops12 minutes
Collections11 minutes
More on Collections8 minutes
Abstract Class8 minutes
Example of the Abstract Class4 minutes
Trait6 minutes
Example of the Trait6 minutes
Exception6 minutes
Practical Example of Exceptions7 minutes
Customize Exceptions of Scala Project9 minutes
Modifiers11 minutes
Strings11 minutes
Methods in Strings10 minutes
Methods in Strings Continue6 minutes
Array10 minutes

4 assignmentsTotal 60 minutes

Scala Foundations and Spark Basics30 minutes
Spark Overview and Setup10 minutes
Scala Language Essentials10 minutes
Advanced Scala Concepts10 minutes

This module explores the advanced features of Apache Spark, focusing on Resilient Distributed Datasets (RDDs), Spark Streaming, and real-time application integration. Learners will understand how to perform transformations and actions on RDDs, process live streaming data, and implement checkpointing for fault tolerance. The module also covers integration with external systems such as Twitter, project setup using Maven and Scala, and explains the differences between Hadoop 1.x and 2.x for Spark compatibility. By completing this module, learners will gain the ability to build scalable, fault-tolerant, real-time big data applications using Spark and Scala.

What's included

18 videos4 assignments

18 videosTotal 136 minutes

RDD in Spark7 minutes
RDD in Spark Continues7 minutes
Different Operations12 minutes
Transformation Operations12 minutes
Action Operations7 minutes
Action Operations Continues5 minutes
Introduction Spark Streaming8 minutes
How to Process the Live Streaming Data7 minutes
How to Process the Live Streaming Data Continues 6 minutes
Windowed Wordcount7 minutes
Windowed Wordcount Example7 minutes
Check Pointing in Spark9 minutes
Check Pointing in Spark Example 8 minutes
Maven Creation11 minutes
Create Scala Project7 minutes
Difference between Hadoop 1.x and 2.x4 minutes
How to Connect Twitter Using Spark Application4 minutes
More on Connect Twitter Using Spark Application10 minutes

4 assignmentsTotal 60 minutes

Advanced Spark and Real-Time Applications30 minutes
Working with RDDs and Operations10 minutes
Spark Streaming and Checkpointing10 minutes
Integrations and Project Setup10 minutes

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Instructor

EDUCBA

1,125 Courses271,823 learners

Offered by

EDUCBA

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