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Home > Programming > Programming Language > Mastering Clojure
Mastering Clojure
Mastering Clojure

Mastering Clojure: Understand the philosophy of the Clojure language and dive into its inner workings to unlock its advanced features, methodologies, and constructs

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Mastering Clojure

Chapter 2. Orchestrating Concurrency and Parallelism

Let's now examine how concurrent and parallel programming are supported in Clojure. The term concurrent programming refers to managing more than one task at the same time. Parallel programming or parallelism, on the other hand, deals with executing multiple tasks at the same time. The distinction between these two terms is that concurrency is about how we structure and synchronize multiple tasks, and parallelism is more about running multiple tasks in parallel over multiple cores. The main advantages of using concurrency and parallelism can be elaborated as follows:

  • Concurrent programs can perform multiple tasks simultaneously. For example, a desktop application can have a single task for handling user interaction and another task for handling I/O and network communication. A single processor can be shared among several tasks. Processor utilization is thus more effective in concurrent programs.
  • Parallel programs take advantage...

Managing concurrent tasks

Clojure has a couple of handy constructs that allow us to define concurrent tasks. A thread is the most elementary abstraction of a task that runs in the background. In the formal sense, a thread is simply a sequence of instructions that can be scheduled for execution. A task that runs in the background of a program is said to execute on a separate thread. Threads will be scheduled for execution on a specific processor by the underlying operating system. Most modern operating systems allow a process to have several threads of execution. The technique of managing multiple threads in a single process is termed as multithreading.

While Clojure does support the use of threads, concurrent tasks can be modeled in more elegant ways using other constructs. Let's explore the different ways in which we can define concurrent tasks.

Note

The following examples can be found in src/m_clj/c2/concurrent.clj of the book's source code.

Using delays

A delay can be used to define...

Managing state

A program can be divided into several parts which can execute concurrently. It is often necessary to share data or state among these concurrently running tasks. Thus, we arrive at the notion of having multiple observers for some data. If the data gets modified, we must ensure that the changes are visible to all observers. For example, suppose there are two threads that read data from a common variable. This data gets modified by one thread, and the change must be propagated to the other thread as soon as possible to avoid inconsistencies.

Programming languages that support mutability handle this problem by locking over a monitor, as we demonstrated with the locking form, and maintaining local copies of the data. In such languages, a variable is just a container for data. Whenever a concurrent task accesses a variable that is shared with other tasks, it copies the data from the variable. This is done in order to prevent unwanted overwriting of the variable by other tasks while...

Executing tasks in parallel

The simultaneous execution of several computations is termed as parallelism. The use of parallelism tends to increase the overall performance of a computation, since the computation can be partitioned to execute on several cores or processors. Clojure has a couple of functions that can be used for the parallelization of a particular computation or task, and we will briefly examine them in this section.

Note

The following examples can be found in src/m_clj/c2/parallel.clj of the book's source code.

Suppose we have a function that pauses the current thread for some time and then returns a computed value, as depicted in Example 2.17:

(defn square-slowly [x]
  (Thread/sleep 2000)
  (* x x))

Example 2.17: A function that pauses the current thread

The function square-slowly in Example 2.17 requires a single argument x. This function pauses the current thread for two seconds and returns the square of its argument x. If the function square-slowly is invoked over a collection...

Summary

We have explored various constructs that can be used to create concurrent and parallel tasks in Clojure. You learned to handle shared mutable state through the use of reference types, namely vars, refs, atoms and agents. As we described earlier, the dining philosophers problem can be easily implemented using refs and agents. You also studied how tasks can be executed in parallel. Lastly, we explored the claypoole library, which allows us to control the amount of parallelism used for a given computation.

In the next chapter, we will continue our exploration of parallelism in Clojure through the use of reducers.

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Key benefits

  • Learn to handle data using sequences, reducers, and transducers in Clojure
  • Explore the lesser known and more advanced features, constructs, and methodologies of the Clojure language and its ecosystem, such as asynchronous channels, actors, logic programming, and reactive programming
  • Sharpen your Clojure skills through illustrative and comprehensive examples

Description

Clojure is a general-purpose language from the Lisp family with an emphasis on functional programming. It has some interesting concepts and features such as immutability, gradual typing, thread-safe concurrency primitives, and macro-based metaprogramming, which makes it a great choice to create modern, performant, and scalable applications. Mastering Clojure gives you an insight into the nitty-gritty details and more advanced features of the Clojure programming language to create more scalable, maintainable, and elegant applications. You’ll start off by learning the details of sequences, concurrency primitives, and macros. Packed with a lot of examples, you’ll get a walkthrough on orchestrating concurrency and parallelism, which will help you understand Clojure reducers, and we’ll walk through composing transducers so you know about functional composition and process transformation inside out. We also explain how reducers and transducers can be used to handle data in a more performant manner. Later on, we describe how Clojure also supports other programming paradigms such as pure functional programming and logic programming. Furthermore, you’ll level up your skills by taking advantage of Clojure's powerful macro system. Parallel, asynchronous, and reactive programming techniques are also described in detail. Lastly, we’ll show you how to test and troubleshoot your code to speed up your development cycles and allow you to deploy the code faster.

Who is this book for?

If you’re looking to learn more about the core libraries and dive deep into the Clojure language, then this book is ideal for you. Prior knowledge of the Clojure language is required.

What you will learn

  • Maximize the impact of parallelization, functional composition, and process transformation by composing reducers and transducers
  • Process and manipulate data using sequences, reducers, and transducers in Clojure
  • Modify and add features to the Clojure language using macros
  • Explore the features of category theory and custom data sources for logic programming in Clojure
  • Orchestrate parallelism and concurrency using built-in primitives as well as community libraries in Clojure
  • Handle data with asynchronous and reactive programming methodologies and leverage it using the core.async library
  • Test your code with unit tests, specs, and type checks to write testable code
  • Troubleshoot and style your Clojure code to make it more maintainable

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 28, 2016
Length: 266 pages
Edition : 1st
Language : English
ISBN-13 : 9781785882050
Category :
Programming
Languages :
Clojure
Concepts :
Programming Language

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Product Details

Publication date : Mar 28, 2016
Length: 266 pages
Edition : 1st
Language : English
ISBN-13 : 9781785882050
Category :
Programming
Languages :
Clojure
Concepts :
Programming Language

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Mastering Clojure
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Table of Contents

13 Chapters
1. Working with Sequences and Patterns Chevron down icon Chevron up icon
1. Working with Sequences and Patterns
Defining recursive functions
Thinking in sequences
Working with pattern matching
Summary
2. Orchestrating Concurrency and Parallelism Chevron down icon Chevron up icon
2. Orchestrating Concurrency and Parallelism
Managing concurrent tasks
Managing state
Executing tasks in parallel
Summary
3. Parallelization Using Reducers Chevron down icon Chevron up icon
3. Parallelization Using Reducers
Using reduce to transform collections
Using fold to parallelize collections
Processing data with reducers
Summary
4. Metaprogramming with Macros Chevron down icon Chevron up icon
4. Metaprogramming with Macros
Understanding the reader
Reading and evaluating code
Quoting and unquoting code
Transforming code
Summary
5. Composing Transducers Chevron down icon Chevron up icon
5. Composing Transducers
Understanding transducers
Comparing transducers and reducers
Transducers in action
Summary
6. Exploring Category Theory Chevron down icon Chevron up icon
6. Exploring Category Theory
Demystifying category theory
Using monoids
Using functors
Using applicative functors
Using monads
Summary
7. Programming with Logic Chevron down icon Chevron up icon
7. Programming with Logic
Diving into logic programming
Thinking in logical relations
Summary
8. Leveraging Asynchronous Tasks Chevron down icon Chevron up icon
8. Leveraging Asynchronous Tasks
Using channels
Using actors
Summary
9. Reactive Programming Chevron down icon Chevron up icon
9. Reactive Programming
Reactive programming with fibers and dataflow variables
Using Reactive Extensions
Using functional reactive programming
Building reactive user interfaces
Introducing Om
Summary
10. Testing Your Code Chevron down icon Chevron up icon
10. Testing Your Code
Writing tests
Testing with specs
Generative testing
Testing with types
Summary
11. Troubleshooting and Best Practices Chevron down icon Chevron up icon
11. Troubleshooting and Best Practices
Debugging your code
Logging errors in your application
Thinking in Clojure
Summary
A. References Chevron down icon Chevron up icon
A. References
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.5
(2 Ratings)
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saokat ali Jun 06, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a well written book about Clojure and its ecosystem. There's no other book that explains reducers, transducers, core.async and core.logic with the level of detail as described in this book. All code examples are well explained and give the reader a good idea of what real world Clojure code looks like.
Amazon Verified review Amazon
el Feb 04, 2017
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
Topics are very interesting; but the book is very dry. Examples are ill conceived and leave you wondering for a while. You can get the same amount of information by reading product tutorials. There are better advanced Clojure books around.
Amazon Verified review Amazon

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About the author

Profile icon Wali
Wali
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Akhil Wali is a software developer. He has been writing code as a hobbyist since 1997 and professionally since 2010. He completed his post graduation from Santa Clara University in 2010, and he graduated from Visvesvaraya Technological University in 2008. His areas of work include business intelligence systems, ERP systems, search engines, and document collaboration tools. He mostly works with Clojure, JavaScript, and C#. Apart from computers, his interests include soccer, guitar solos, and finding out more about the universe.
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