HomeCoursesMastering Big Data with Apache Spark and Java

Intermediate

17h 15min

Updated 5 months ago

Mastering Big Data with Apache Spark and Java
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Gain insights into Spark Java API, learn about data transformations and SQL operations, and discover how to integrate big data and Java for scalable, high-speed processing.
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This course serves as a comprehensive introduction to the Spark Java API. Experienced Java developers will use object-oriented programming (OOP) principles to apply theory to Apache Spark and big data practice. You’ll learn the basic components and architecture of Spark, a leading framework for building big data applications, before implementing them in Java. You’ll also explore data transformations like grouping, sorting, and joining. Further, you’ll learn to support SQL operations in the database and create a big data and batch template application with Java. By the end of the course, you’ll be familiar with Apache Spark and know how to integrate big data with Java environments through the Spark Java API. You’ll wrap up by learning about monitoring and support functions for a live Spark Java environment. Combining a leading big data framework with a leading programming language, this course will empower you to work efficiently with large volumes of data, and process at scale and speed.
This course serves as a comprehensive introduction to the Spark Java API. Experienced Java developers will use object-oriented p...Show More

WHAT YOU'LL LEARN

Learn Apache Spark fundamentals and gain an overview of its building blocks
Learn Advanced Transformations and leverage Spark’s powerful library, Spark SQL
Acquire practical experience through examples, coding, and recipes
Develop a big data batch application with foundations in both design patterns and good programming practices using Spark
Learn Apache Spark fundamentals and gain an overview of its building blocks

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Content

55 Lessons7 Quizzes

1.

Course Introduction

2 Lessons

Get familiar with Apache Spark, its architecture, Java API, and big data processing.
About the Course
Course Structure

2.

Spark Introduction and Basics

5 Lessons

Get started with Apache Spark's architecture, in-memory computing, and scalable data processing.
Spark Fundamentals
Components and Architecture
Spark and Big Data
Spark's Java Main Abstraction: The DataFrame
Quiz Yourself: Spark Introduction

3.

Getting Started with Spark

5 Lessons

Explore setting up and running Spark programs, configuring Maven projects, and utilizing DataFrames.
Running the First Spark Program
Spark Maven Based Projects
Enriching the Basic DataFrame Program
Deep Dive: Transformations and Data Storage
Quiz Yourself: Getting Started with Spark

6.

Spark SQL and Other Functionalities

8 Lessons

Follow the process of leveraging Spark's SQL, schema manipulation, file/database ingestion, and serialization.
Spark SQL Goodness
Schema Manipulation
How to Ingest Files: Part I
How to Ingest Files: Part II
Ingesting Databases
Exporting Information
Serialization: Working through the Wire
Quiz Yourself: SparkSQL and Other Functionalities

7.

Building a Big Data Batch Application

8 Lessons

Piece together the parts of building a Spark batch application, including architecture, driver program design, ingestion, and testing.
The Application Architecture Ecosystem
Driver Program Design and Project Structure
Driver Program and Job Implementation: Part I
Driver Program and Job Implementation: Part II
Ingestion Job: Part I
Ingestion Job: Part II
Batch Pipelines and Other Types of Jobs
Testing and Spark

8.

Deployment and Cluster Execution

3 Lessons

Try out executing and deploying Apache Spark applications in local and cluster modes.
Local and Cluster-based Execution
Deploying and Running a Spark Application
Quiz Yourself: Deployment and Cluster Execution

9.

Monitoring and Performance Fundamentals

4 Lessons

Unpack the core of interpreting Spark logs, using SparkUI, and fundamental performance optimization techniques.
Interpreting Spark Logs
Cluster Monitoring and SparkUI
Performance Fundamentals and Recipes
Quiz Yourself: Monitoring and Performance Fundamentals

10.

Conclusion

1 Lessons

Examine further resources for Spark and Java development to continue your learning.
Where to Go from Here

11.

Apendix

2 Lessons

Break down complex tools and techniques for local Spark development and debugging using IntelliJ.
Tools to Develop in Spark Locally
IntelliJ: Debug and Inspect Spark Execution
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.

Course Author:

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