Experimenting with parallelism using TypeScript/JS

Question

Experimenting with parallelism using TypeScript/JS

Currently, I am tackling a TS project that involves testing concurrent code and its interactions with a database, specifically focusing on idepotency. My goal is to ensure that multiple requests modifying the same resource will either apply changes correctly or fail, without experiencing lost updates or double processing.

While I have extensive experience testing similar scenarios in Java due to its abundance of concurrency primitives like semaphores and barriers, I am struggling to translate this knowledge into TypeScript.

In Java, for instance, I would initiate 2 threads using a CyclicBarrier with 2 parties. These threads would reach the barrier, wait for each other, then continue execution, allowing me to validate the code's functionality effectively. If parallel execution could not be guaranteed, I would repeat the test multiple times or use more threads to increase chances of parallelism.

Unfortunately, I have not come across any similar concurrency primitives in JS to replicate this process. The closest workaround I found was busy waiting on a shared value or utilizing worker threads as suggested by some blogs.

If anyone has suggestions on how to approach this challenge in TypeScript, I would greatly appreciate it! This topic poses several difficulties, so links to relevant blogs, articles, and books are welcome!

javascript typescript testing concurrency

Answer 1

Answer №1

It is crucial to note that unlike Java or other programming languages, JavaScript (in this case TypeScript) runs on a single thread. This means that only one line of TS/JS code can execute at a time. Although there are workarounds like WebWorkers, for the purpose of this discussion, let's assume they are not being utilized.

If your library will be used in an environment where multiple instances of your application are running concurrently, you will have truly parallel systems. For now, let's focus on the scenario where this is not the case.

Evaluating concurrency within a single node process

In this context, understanding how JS handles events via the event loop is key. Philip Roberts has an insightful talk on this topic from JSConf.

With a single node process and assuming the use of "async" functions, Promises are executed concurrently. However, the actual switching between asynchronous tasks occurs when performing operations like IO, web requests, etc.

A simple way to test your library under these conditions could be:

function test() {
    Promise.all([
        doSomething(),
        doSomething(),
    ]);
}

Evaluating concurrency in a multi-process environment

If your application is deployed across multiple machines simultaneously, testing becomes more complex. Directly simulating this scenario is challenging as initiating tests that call functions simultaneously requires starting multiple processes.

I would caution against attempting such tests, especially if the tasks you are evaluating are quick, as it may lead to unreliable results. Introducing an artificial delay by extending critical sections to take several seconds and calling both instances sequentially might provide better insights. Using Promise.all() here can help maximize concurrency effects. Ensure to account for potential misbehaviors during execution.

As for setting up and executing tests involving two processes, consider creating a web worker to establish a new V8 execution context in Node.js, or leverage a simple HTTP server for communication.

Considering alternative solutions

Given the inherent single-threaded nature of JavaScript, achieving true parallelism beyond Promise.all can be challenging. A possible workaround could involve writing a small script in another language to assess this behavior. While languages like Rust offer robust concurrency primitives, interoperability with JavaScript may present some challenges.

Answer 2

It is crucial to note that unlike Java or other programming languages, JavaScript (in this case TypeScript) runs on a single thread. This means that only one line of TS/JS code can execute at a time. Although there are workarounds like WebWorkers, for the purpose of this discussion, let's assume they are not being utilized.

If your library will be used in an environment where multiple instances of your application are running concurrently, you will have truly parallel systems. For now, let's focus on the scenario where this is not the case.

Evaluating concurrency within a single node process

In this context, understanding how JS handles events via the event loop is key. Philip Roberts has an insightful talk on this topic from JSConf.

With a single node process and assuming the use of "async" functions, Promises are executed concurrently. However, the actual switching between asynchronous tasks occurs when performing operations like IO, web requests, etc.

A simple way to test your library under these conditions could be:

function test() {
    Promise.all([
        doSomething(),
        doSomething(),
    ]);
}

Evaluating concurrency in a multi-process environment

If your application is deployed across multiple machines simultaneously, testing becomes more complex. Directly simulating this scenario is challenging as initiating tests that call functions simultaneously requires starting multiple processes.

I would caution against attempting such tests, especially if the tasks you are evaluating are quick, as it may lead to unreliable results. Introducing an artificial delay by extending critical sections to take several seconds and calling both instances sequentially might provide better insights. Using Promise.all() here can help maximize concurrency effects. Ensure to account for potential misbehaviors during execution.

As for setting up and executing tests involving two processes, consider creating a web worker to establish a new V8 execution context in Node.js, or leverage a simple HTTP server for communication.

Considering alternative solutions

Given the inherent single-threaded nature of JavaScript, achieving true parallelism beyond Promise.all can be challenging. A possible workaround could involve writing a small script in another language to assess this behavior. While languages like Rust offer robust concurrency primitives, interoperability with JavaScript may present some challenges.

Experimenting with parallelism using TypeScript/JS

Answer №1

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