How to Serialize Execution of an Array of Observables in RxJS

Discover how to effectively serialize the execution of an array of observables in RxJS, ensuring accurate data validation while managing shared resources.
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How to Serialize Execution of an Array of Observables in RxJS

In the world of asynchronous programming, managing the execution order of operations can be crucial, especially when shared resources are involved. One common scenario in JavaScript development is validating data in an array of items, particularly when each item requires access to a shared resource.

In this guide, we will explore how to serialize the execution of an array of observables using RxJS, ensuring that each validation runs in the correct order and maintains the integrity of shared resource access.

The Problem

Imagine you have a validation process that operates on an array of data rows, validating each row individually. Each row validation relies on a shared resource that must be accessed sequentially. Using forkJoin might not be suitable here, as it doesn't wait for each observable to complete before moving to the next, which can lead to conflicts.

Here’s the challenge: How can you accomplish the same sequential execution as concat while also collecting the results of all validations, like forkJoin?

The Solution

To tackle this problem, we will use RxJS operators effectively. Let’s break down the solution into two main approaches, depending on whether the observables emit a single value or multiple values.

1. Using concat and toArray()

Example Code:

[[See Video to Reveal this Text or Code Snippet]]

Explanation:

concat(...): This operator queues the observables and executes them one at a time.

toArray(): Once all the observables complete, it gathers their emissions into an array, which is re-emitted.

This approach is effective when each validation emits a single result, providing a neat and organized array of outcomes.

2. Handling Multiple Emissions with scan()

In cases where the observable for validateSingleRow might emit multiple values, you would want to capture only the latest emitted value for each validation. This is where using scan() comes in handy.

Example Code:

[[See Video to Reveal this Text or Code Snippet]]

Explanation:

map(result => [index, result]): This transforms the emitted value to include its index, allowing us to build a result object.

scan(...): This operator accumulates the latest results into an object, indexed by their original order, so we can maintain the order of the original array.

takeLast(1): This ensures that we only emit the last accumulated value, thus giving us the final state of all validations.

Conclusion

By leveraging the power of RxJS, you can effectively serialize the execution of observables to manage shared resources and ensure accurate data validation. Whether using toArray() for single emissions or scan() for multiple emissions, these techniques provide a robust solution to your problem.

Now you can confidently implement serialization in your asynchronous operations using RxJS and improve the quality of your data validation processes!