Distributed Programming in Java

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Distributed Programming in Java

Coursera · Intermediate ·🔄 Data Engineering ·5mo ago

Key Takeaways

Distributed programming using Java 8 and popular frameworks

Original 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 o
AI explanation not available for this lesson yet
This lesson is still being prepared for the AI tutor. In the meantime, explore lessons that are ready.
Browse explainer-ready lessons →

Related Reads

📰
Announcing Orchestra and n8n | The ultimate way to automate workflows
Learn to automate workflows with Orchestra and n8n, a powerful tool for data science and engineering
Medium · Data Science
📰
ELT is moving back to best-of-breed and Orchestration is the missing piece
Learn why ELT is shifting back to best-of-breed and how orchestration is the key missing piece, and why it matters for data engineering efficiency
Medium · Data Science
📰
Azure Data Engineer Course in Telugu: Build a Successful Data Engineering Career
Learn how to build a successful data engineering career with Azure Data Engineer Course in Telugu
Medium · DevOps
📰
Your Data Lake Is a Junk Drawer. Apache Iceberg Fixes That.
Apache Iceberg organizes data lakes by adding a table layer, making it behave like a database and handling large datasets efficiently
Medium · Python
Up next
The Agent Cloud: Databricks’ Bet on the Future of AI — Matei Zaharia and Reynold Xin
Latent Space
Watch →