Concurrency, Multithreading and Parallel Computing in Java from Udemy

This course is about the basics of multithreading and concurrent programming with some parallel concepts. In the 21st century this topic is becoming more and more popular with the advent of Big Data and Machine Learning. We will consider the low level concepts such as threads, synchronization and locks. The second chapter will be about concurrent library: of course there are built in classes and interfaces that we can use when implementing multithreaded applications. Then we develop little programs as show-cases for multithreading: the dining-philosopher problem and the students in library simulation. Last chapter is about parallel computing and MapReduce.

Section 1 - Multithreading Theory:

theory behind multithreading
pros and cons of multithreading
life cycle of a thead

Section 2 - Threads Manipulation:

starting threads (Runnable interface and Thread class)
join keyword
daemon threads

Section 3 - Inter-Thread Communication:

memory management of threads
synchronization and synchronized blocks
locks
wait and notify
producer-consumer problem and solution
concurrent collections
latch, cyclic barrier and blocking queues
delay queue, priority queue and concurrent maps

Section 4 - Multithreading Concepts:

volatile keywords
deadlocks and livelocks
semaphores and mutexes
dining philosophers problem
library application

Section 6 - Executors and ExecutorServices:

executors
executor services

Section 6 - Concurrent Collections:

synchronization with Collections
latches
cyclic barriers
delay and priority queues
concurrent HashMaps
CopyOnWriteArrayLists

Section 7 - Simulations:

dining philosophers problem
library problem

Section 8 - Parallel Algorithms:

what is parallel computing
parallel merge sort
parallel algorithms

Section 9 - Fork-Join Framework

Fork-Join framework
maximum finding in parallel manner

Section 10 - Stream API

the Stream API explained with examples
sequential streams and parallel streams

Section 11 - Virtual Threads

platform threads and virtual threads
understanding virtual thread creation and operations
StructuredTaskScope and Subtask
delimited continuation

Section 12 - BigData and MapReduce:

what is MapReduce
MapReduce and Fork-Join framework

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What's inside

Learning objectives

Understand basic concurrency
Understand the basics of multithreading
Understand parallel processing
Able to use the concepts in real life scenarios

Understand concurrent collections
Understand synchronization and locking
Understand the fork-join framework
Understand stream api

Understand basic concurrency
Understand the basics of multithreading
Understand parallel processing
Able to use the concepts in real life scenarios
Understand concurrent collections
Understand synchronization and locking
Understand the fork-join framework
Understand stream api

Syllabus

Introduction

### MULTITHREADING ###

Multithreading section

Multithreading Theory

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers the Fork-Join framework, which is essential for efficient parallel processing in Java applications, especially when dealing with computationally intensive tasks

Explores concurrent collections, which are designed to be thread-safe and highly performant in multithreaded environments, making them suitable for building scalable applications

Includes hands-on exercises such as the Dining Philosophers Problem and the Students Library Simulation, which are classic scenarios for understanding concurrency issues

Discusses the Stream API, which enables developers to process collections of data in parallel using functional-style operations, potentially improving performance on multi-core processors

Examines low-level concepts like threads, synchronization, and locks, which are fundamental for building robust and reliable concurrent applications in Java

Introduces MapReduce, which is a programming model and distributed computing framework for processing large datasets in parallel, although its relevance may be limited for some Java developers

Reviews summary

Java concurrency & multithreading fundamentals

According to learners, this course offers a solid introduction to the complex world of concurrency, multithreading, and parallel computing in Java. Students appreciate that it covers a wide range of topics, from core concepts like threads, synchronization, and locks to more advanced areas such as the Fork-Join framework, Stream API, and even newer features like Virtual Threads. While many find the explanations clear and the practical examples helpful for understanding tricky concepts like deadlocks and producer-consumer, some reviewers noted that the course provides a breadth of coverage rather than deep dives into every subject. A few mention that some code examples could be clearer or contain minor issues. Overall, it's seen as a strong starting point for developers looking to understand these essential Java concepts.

Covers breadth of related concurrency topics.

"I was impressed by the range of topics covered, including ForkJoin, Streams, and even Virtual Threads."

"Goes beyond just the basics to touch upon concurrent collections and parallel algorithms."

"The syllabus is quite comprehensive for an introductory course on the subject."

"It includes both traditional concepts and newer features like Virtual Threads."

Simulations aid in grasping abstract ideas.

"The dining philosophers and library simulations really helped me visualize and understand the problems and solutions."

"Using practical examples made the concepts of locks and semaphores much clearer."

"I found the hands-on coding examples useful for applying the theory."

"The demos were effective in showing how concurrency issues manifest and how to solve them."

Builds a strong understanding of core concepts.

"The course provides a really solid foundation on threads, synchronization, and locks. It's a great starting point."

"I feel much more confident with the basics of multithreading after taking this."

"Explains the fundamental concepts clearly, making it easier to grasp complex topics later."

"It covers the essential building blocks of concurrent programming effectively."

Occasional issues or lack of detail in code.

"I encountered minor issues with some code examples; they sometimes felt a bit disjointed."

"A few times the code presented wasn't immediately clear or seemed to have small errors that were distracting."

"Could use more detailed explanations accompanying the code snippets."

"Some code demos could be improved for better clarity and robustness."

Some topics lack deep or detailed exploration.

"While it covers many topics, I feel some areas could go into more depth."

"Good as an overview, but I needed external resources for a deeper understanding of certain concepts."

"Some sections felt a bit rushed, leaving me wanting more detailed explanations or examples."

"It's more of a breadth-first introduction than a deep dive into any single advanced area."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Concurrency, Multithreading and Parallel Computing in Java with these activities:

Review Java Fundamentals

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Solidify your understanding of core Java concepts like classes, objects, inheritance, and polymorphism. This will provide a strong foundation for understanding multithreading and concurrency.

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Review basic Java syntax and data structures.
Practice writing simple Java programs.
Study object-oriented programming principles.

Read 'Java Concurrency in Practice'

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Deepen your understanding of Java concurrency with a comprehensive guide. This book provides practical examples and best practices for building robust multithreaded applications.

View Java Concurrency in Practice on Amazon

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Read the book cover to cover.
Work through the examples provided in the book.
Take notes on key concepts and techniques.

Implement Producer-Consumer with Different Approaches

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Reinforce your understanding of inter-thread communication by implementing the producer-consumer problem using different synchronization mechanisms. This will help you compare and contrast the various approaches.

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Implement producer-consumer using wait and notify.
Implement producer-consumer using locks.
Implement producer-consumer using blocking queues.

Four other activities

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Follow Java Stream API Tutorials

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Enhance your understanding of the Stream API by working through online tutorials. This will provide hands-on experience with using streams for parallel processing.

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Find online tutorials on the Java Stream API.
Work through the examples provided in the tutorials.
Experiment with different stream operations.

Write a Blog Post on Deadlocks

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Solidify your understanding of deadlocks by explaining the concept in a blog post. This will force you to articulate the causes, prevention, and detection of deadlocks in a clear and concise manner.

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Research the causes, prevention, and detection of deadlocks.
Write a clear and concise explanation of deadlocks.
Include examples of deadlocks in Java code.
Proofread and edit the blog post.

Build a Concurrent Web Server

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Apply your knowledge of concurrency to build a practical application. This project will challenge you to design and implement a web server that can handle multiple client requests concurrently.

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Design the architecture of the concurrent web server.
Implement thread pooling for handling client requests.
Implement synchronization to protect shared resources.
Test the web server with multiple concurrent clients.

Explore 'Effective Java'

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Improve your Java coding skills with a guide to best practices. This book offers valuable insights into writing high-quality, thread-safe code.

View Effective Java (3rd Edition) on Amazon

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Read the relevant chapters on concurrency.
Apply the best practices to your own code.
Refactor existing code to improve thread safety.

Career center

Learners who complete Concurrency, Multithreading and Parallel Computing in Java will develop knowledge and skills that may be useful to these careers:

Software Engineer

A software engineer often designs and develops applications, and this course is directly applicable to that work. Specifically, the course's emphasis on multithreading, concurrency, and parallel computing is highly relevant for building efficient, responsive, and scalable software systems. Many applications, especially those dealing with large datasets or real-time processing, depend on the principles covered in this course. Concepts like thread management, synchronization, and concurrent data structures, all taught in this course, are critical for a software engineer who wants to write high-performance code. Knowledge of parallel algorithms and frameworks such as MapReduce, which are covered in the last section of this course, are also very valuable to a software engineer.

See salaries and explore the career path for Software Engineer

High-Performance Computing Engineer

A high performance computing engineer designs and optimizes software for high-performance computing environments, and this course on concurrency and parallel computing aligns directly with the requirements of their work. The course covers many essential concepts such as multithreading, parallel algorithms, and the Fork-Join Framework, which are all critical for high performance computing. The sections on parallel merge sort, stream API, and the MapReduce framework would be especially useful. A high-performance computing engineer should take this course to expand their understanding of how to design parallel algorithms and write efficient code for these environments.

See salaries and explore the career path for High-Performance Computing Engineer

Application Developer

An application developer builds software applications, and this course is very helpful to those who work with complex, high-load applications. The course’s focus on multithreading, concurrent programming, and parallel computing is very valuable when creating applications that require fast and efficient processing. Concepts like thread synchronization, executors, and concurrent collections covered in this course are important when developing applications that handle multiple user requests concurrently. The course also goes into parallel algorithms and frameworks such as MapReduce, which are important components for efficient applications, particularly those that process large amounts of data. An application developer wanting to develop high-performance applications should take this course.

See salaries and explore the career path for Application Developer

Systems Programmer

A systems programmer works on low-level software such as operating systems and device drivers and this course is beneficial to them. The low-level concepts of threads, locks, and synchronization which are covered in this course are essential for systems programmers. Understanding concurrency, multithreading, and parallel computing, as taught here, helps in designing more efficient and responsive systems-level software. The course's discussions of memory management and inter-thread communication would be very valuable to a systems programmer. The exploration of topics such as virtual threads and the Fork-Join framework would be particularly helpful here. A systems programmer would benefit greatly from taking this course because it provides essential knowledge for working with low-level software.

See salaries and explore the career path for Systems Programmer

Backend Developer

A backend developer builds the server-side logic that powers applications and websites. The focus of this course on concurrency, multithreading, and parallel computing is directly applicable to backend development, where applications must often handle many requests simultaneously. This course provides valuable tools such as executors, concurrent collections, and locking mechanisms that can assist a backend developer to build robust and efficient backend systems. The discussion of parallel algorithms and the Fork-Join framework are also very relevant. This course is especially useful for a backend developer who wants to understand how to build high-performance server applications.

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Data Engineer

A data engineer designs and builds systems for data storage and processing. Many of the concepts taught in this course, such as parallel processing and the MapReduce framework, are very useful when developing systems that handle large amounts of data. Data engineers need to have a firm grasp of multithreading and concurrency to ensure their systems can process data efficiently. The course's coverage of concurrent collections, executors, and the Fork-Join framework would also be very valuable. This course is very helpful to data engineers as the field requires an understanding of concurrent and parallel computing.

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Cloud Computing Engineer

A cloud computing engineer develops and manages cloud infrastructure and services, and this course is useful to their job. The topics of concurrency, multithreading, and parallel processing are central to the development of scalable cloud applications and services. The knowledge gained from the course on concurrent collections, executors, and the Fork-Join framework is essential when developing robust distributed systems. This course's discussions on the MapReduce framework and parallel algorithms are also crucial for a cloud computing engineer. A cloud computing engineer would find this course helpful as it provides instruction on important topics applicable to cloud computing.

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Embedded Systems Engineer

An embedded systems engineer works on software for devices with real time constraints and limited resources and this course is helpful for them. The course goes into low level concepts like threads, locks, and synchronization and this information helps in efficiently using the resources on embedded devices. This course on multithreading and concurrency can help an embedded systems engineer develop software that handles multiple tasks and threads on embedded devices. The sections covering memory management of threads are also be particularly helpful. This course is helpful for an embedded systems engineer who needs to write efficient and responsive software.

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Game Developer

A game developer creates video games, and this course may be relevant to the work they do. The concepts of multithreading and concurrency become especially valuable when developing complex and high-performance games. The course's coverage of thread synchronization, executors, and concurrent collections helps game developers manage multiple game processes. The course's teachings on parallel algorithms and the Fork-Join framework may also be useful, for example when handling complex game engine tasks. Game developers may find this course helpful because it does cover some areas relevant to game development.

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Quantitative Analyst

A quantitative analyst develops mathematical and statistical models for financial markets and this course might be useful to them. The course may help in writing more efficient code since a quant often must handle very large datasets and perform complex calculations. The sections on parallel processing, multithreading and concurrent programming could be useful. The course's discussions on the Fork-Join framework and stream API might also be relevant. While not directly related to finance, a quantitative analyst may find this course useful for improving the performance of their models.

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Machine Learning Engineer

A machine learning engineer develops and implements machine learning models and this course may be useful to them. The course's discussions of parallel processing and the MapReduce framework can be useful when training models on large datasets, as this course provides a foundation for parallel computation. The concurrency and multithreading aspects of the course might also lead to faster model training code. While not directly focused on machine learning, this course may be helpful for a machine learning engineer who wants to utilize the concepts of parallel processing.

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Database Administrator

A database administrator manages and maintains databases and this course may be relevant to some of their work. The course’s introduction to concurrency and multithreading can help database administrators better understand how database systems handle multiple requests. The knowledge of concurrent collections and synchronization techniques may be helpful when optimizing database performance. While not directly related, a database administrator may find some of the concepts introduced by this course to be helpful.

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Mobile Application Developer

A mobile application developer creates mobile applications and this course may be useful to some of their work. The course touches on concurrent programming and multithreading which can be helpful for developers who need to ensure the responsiveness of their applications. The discussion of executors and concurrent collections can be helpful when performing background tasks. Although mobile development is not the principal focus, a mobile application developer may find that this course provides useful knowledge of concurrent programming.

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Technical Writer

A technical writer creates software documentation and guides and this course may be helpful in their career. The course provides a deep understanding of multithreading, concurrent programming, and parallel computing, all of which can be useful when documenting complex systems. The technical writer may be able to write more comprehensive documentation if they understand these concepts. While not a core skill, taking this course may be a useful method of augmenting a technical writer's expertise.

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Project Manager

A project manager oversees software development projects and this course may be useful to them. The course may help them understand the challenges and trade-offs of multithreading and parallel processing, particularly when managing teams working on complex applications. This course could be useful as it gives a project manager insight into one of the core technologies they manage. This course may be helpful for a project manager who wants to be more familiar with fundamental concepts.

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Concurrency, Multithreading and Parallel Computing in Java

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Learning objectives

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Reviews summary

Java concurrency & multithreading fundamentals

Activities

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