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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DataFrameBasicsRun

SparkDataframeExampleDB

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.

Mastering Big Data with Apache Spark and Java

In previous lessons, we used diagrams to slowly introduce to the reader how the Spark components interact, and how execution flow for a Spark application falls into place.

This lesson expand on this by presenting a broader picture of the Spark Landscape in a typical but straightforward application’s execution. It also dives into two of the most common cluster topologies in which a Spark application can run.


## The big picture

A diagram of the Spark ecosystem while executing a program is below:


In previous lessons, we used diagrams to slowly introduce to the reader how the Spark components interact, and how execution flow for a Spark application falls into place.

This lesson expand on this by presenting a broader picture of the Spark Landscape in a typical but straightforward application’s execution. It also dives into two of the most common cluster topologies in which a Spark application can run.


# The big picture

A diagram of the Spark ecosystem while executing a program is below:


This lesson expands the previous landscape for a Spark Execution flow and Architecture.

Course Introduction

Spark Introduction and Basics

Getting Started with Spark

DataFrame Basic Operations

DataFrame Advanced Operations

Spark SQL and Other Functionalities

Building a Big Data Batch Application

Deployment and Cluster Execution

Monitoring and Performance Fundamentals

Conclusion

Apendix

Deep Dive: Internals of Spark Execution

The big picture