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Distributed Programming in Java

Approx. 18 hours to complete

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Course Summary

Learn how to develop distributed applications in Java using various technologies and frameworks such as Java RMI, Apache Kafka, and Akka.

Key Learning Points

Understand the fundamentals of distributed programming in Java
Implement distributed applications using Java RMI, Apache Kafka, and Akka
Explore different strategies for fault tolerance and scalability in distributed systems

Job Positions & Salaries of people who have taken this course might have

- USA: $84,000 - $145,000
- India: ₹6,00,000 - ₹16,00,000
- Spain: €30,000 - €50,000
- USA: $84,000 - $145,000
- India: ₹6,00,000 - ₹16,00,000
- Spain: €30,000 - €50,000
- USA: $120,000 - $200,000
- India: ₹10,00,000 - ₹25,00,000
- Spain: €40,000 - €70,000
- USA: $84,000 - $145,000
- India: ₹6,00,000 - ₹16,00,000
- Spain: €30,000 - €50,000
- USA: $120,000 - $200,000
- India: ₹10,00,000 - ₹25,00,000
- Spain: €40,000 - €70,000
- USA: $110,000 - $180,000
- India: ₹8,00,000 - ₹20,00,000
- Spain: €35,000 - €60,000

Learning Outcomes

Develop distributed applications using Java RMI, Apache Kafka, and Akka
Implement fault tolerance and scalability strategies in distributed systems
Understand the fundamentals of distributed programming in Java

Prerequisites or good to have knowledge before taking this course

Basic knowledge of Java programming language
Familiarity with Object-Oriented Programming concepts

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced
Video Lectures

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Distributed Systems and Cloud Computing
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Building Scalable Java Microservices with Spring Boot and Spring Cloud

Related Education Paths

Notable People in This Field

Martin Fowler
Doug Lea

Related Books

Description

This course teaches learners (industry professionals and students) the fundamental concepts of Distributed Programming in the context of Java 8. Distributed programming enables developers to use multiple nodes in a data center to increase throughput and/or reduce latency of selected applications. By the end of this course, you will learn how to use popular distributed programming frameworks for Java programs, including Hadoop, Spark, Sockets, Remote Method Invocation (RMI), Multicast Sockets, Kafka, Message Passing Interface (MPI), as well as different approaches to combine distribution with multithreading.

Why take this course? • All data center servers are organized as collections of distributed servers, and it is important for you to also learn how to use multiple servers for increased bandwidth and reduced latency. • In addition to learning specific frameworks for distributed programming, this course will teach you how to integrate multicore and distributed parallelism in a unified approach. • Each of the four modules in the course includes an assigned mini-project that will provide you with the necessary hands-on experience to use the concepts learned in the course on your own, after the course ends. • During the course, you will have online access to the instructor and the mentors to get individualized answers to your questions posted on forums. The desired learning outcomes of this course are as follows: • Distributed map-reduce programming in Java using the Hadoop and Spark frameworks • Client-server programming using Java's Socket and Remote Method Invocation (RMI) interfaces • Message-passing programming in Java using the Message Passing Interface (MPI) • Approaches to combine distribution with multithreading, including processes and threads, distributed actors, and reactive programming Mastery of these concepts will enable you to immediately apply them in the context of distributed Java programs, and will also provide the foundation for mastering other distributed programming frameworks that you may encounter in the future (e.g., in Scala or C++).

Outline

Welcome to the Course!
Course Welcome
General Course Info
Course Icon Legend
Discussion Forum Guidelines
Pre-Course Survey
Mini Project 0: Setup

DISTRIBUTED MAP REDUCE
1.1 Introduction to Map-Reduce
1.2 Hadoop Framework
1.3 Spark Framework
1.4 TF-IDF Example
1.5 Page Rank Example
Demonstration: Page Rank Algorithm in Spark
1.1 Lecture Summary
1.2 Lecture Summary
1.3 Lecture Summary
1.4 Lecture Summary
1.5 Lecture Summary
Mini Project 1: Page Rank with Spark
Module 1 Quiz

CLIENT-SERVER PROGRAMMING
2.1 Introduction to Sockets
2.2 Serialization/Deserialization
2.3 Remote Method Invocation
2.4 Multicast Sockets
2.5 Publish-Subscribe Model
Demonstration: File Server using Sockets
2.1 Lecture Summary
2.2 Lecture Summary
2.3 Lecture Summary
2.4 Lecture Summary
2.5 Lecture Summary
Mini Project 2: File Server
Module 2 Quiz

Talking to Two Sigma: Using it in the Field
Industry Professional on Parallel, Concurrent, and Distributed Programming in Java - Jim Ward, Managing Director
Industry Professional on Distribution - Dr. Eric Allen, Senior Vice President
About these Talks

MESSAGE PASSING
3.1 Single Program Multiple Data (SPMD) model
3.2 Point-to-Point Communication
3.3 Message Ordering and Deadlock
3.4 Non-Blocking Communications
3.5 Collective Communication
Demonstration: Distributed Matrix Multiply using Message Passing
3.1 Lecture Summary
3.2 Lecture Summary
3.3 Lecture Summary
3.4 Lecture Summary
3.5 Lecture Summary
Mini Project 3: Matrix Multiply in MPI
Module 3 Quiz

COMBINING DISTRIBUTION AND MULTITHREADING
4.1 Processes and Threads
4.2 Multithreaded Servers
4.3 MPI and Threading
4.4 Distributed Actors
4.5 Distributed Reactive Programming
Demonstration: Parallel File Server using Multithreading and Sockets
4.1 Lecture Summary
4.2 Lecture Summary
4.3 Lecture Summary
4.4 Lecture Summary
4.5 Lecture Summary
Mini Project 4: Multi-Threaded File Server
Exit Survey
Module 4 Quiz

Continue Your Journey with the Specialization "Parallel, Concurrent, and Distributed Programming in Java"
Industry Professionals on Parallelism - Jake Kornblau and Margaret Kelley, Software Engineers, Two Sigma
Industry Professional on Concurrency - Dr. Shams Imam, Software Engineer, Two Sigma
Our Other Course Offerings

Summary of User Reviews

Read reviews of Distributed Programming in Java course on Coursera. Users have generally found the course to be helpful and informative. One key aspect that many users thought was good is the interactive nature of the course, which keeps them engaged throughout the lessons.

Pros from User Reviews

The course is well-structured and provides a clear understanding of distributed programming in Java
The interactive nature of the course keeps users engaged and interested in the material
The course is taught by knowledgeable instructors who are experts in the field
The assignments and quizzes are challenging and help users learn the material better
The course provides hands-on experience with real-world examples

Cons from User Reviews

Some users found the course to be too advanced for beginners
The course requires a strong foundation in Java programming
Some users found the course material to be outdated
Some users found the course to be too theoretical and not practical enough
The course can be time-consuming and requires a significant amount of effort

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