Retrieving Top 10 Items in a Date Range from Firebase Firestore Ordered by Likes

Описание: Learn how to efficiently retrieve the top 10 items from Firebase Firestore within a date range, ordered by likes in descending order.
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This video is based on the question https://stackoverflow.com/q/66459288/ asked by the user 'Marcel Dz' ( https://stackoverflow.com/u/12186851/ ) and on the answer https://stackoverflow.com/a/66459825/ provided by the user 'Thierry' ( https://stackoverflow.com/u/10118505/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Efficiently Retrieving the Top 10 Items in Firebase Firestore

Firebase Firestore is a powerful tool for managing data in real-time applications, but it can come with its own set of challenges. One common request developers face is how to efficiently query and retrieve items ordered by certain parameters while applying various filters. In this guide, we’ll address a specific scenario: how to retrieve the top 10 items from a collection in Firestore, ordered by likes in descending order, while also considering a date range.

The Problem: Fetching the Right Data

Let’s set the stage for your query needs. You are looking to accomplish the following:

Retrieve items from a large collection.

Order them by the number of likes (in descending order).

Limit the results to a specific date range (e.g., items from the last 30 days).

Ensure that you get only the top 10 results based on the likes.

Here’s a brief rundown of what you might have already tried, which isn’t yielding the desired results:

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

This method runs into a limitation where the ordering by likes is ineffective because it’s performed after filtering by date. To really optimize your results, a different approach is required.

Understanding Firestore Limitations

Firestore enforces certain rules on how you can structure your queries:

If your query includes range comparisons (like >=, <=), the first orderBy must be on the same field as your filter.

This means that if you’re filtering by date, you cannot directly use a second orderBy on likes for effective sorting across the entire dataset.

Therefore, the current approach of sorting by date first and then trying to sort by likes isn’t giving you the desired outcomes, especially when you want broader filtering across datasets.

Exploring a Solution

So, what can we do? Here's a strategy that leverages Firestore's strengths and allows you to efficiently maintain top 10 lists.

Maintain Top 10 Lists in Firestore

Instead of calculating the top 10 items for each request (which is expensive), consider maintaining a precomputed list. This can be done with the help of Cloud Functions that run on a schedule to keep these lists updated. Here’s the step-by-step approach:

Create a Cloud Function: This function will run every few hours (or based on your application needs) to compute the top 10 lists.

Define Timeframes: Your function can differentiate between daily, weekly, and monthly top 10 lists.

Sample Implementation

Here’s what your Cloud Function might look like:

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

Advantages of This Approach

Efficiency: Accessing the precomputed top 10 lists in Firestore requires significantly fewer read operations compared to running the complex calculations in real time for each visitor.

Simplicity: Instead of dealing with range queries and multiple sort conditions during each request, you can serve up-to-date lists directly.

Conclusion

Maintaining a robust method for retrieving the top 10 items based on likes while considering specific date ranges can greatly improve the performance and user experience in your application. By using Cloud Functions to schedule updates for your top items, you achieve efficiency and clarity. Don't forget to continuously monitor and adjust your strategy based on application needs and user engagement. Happy coding!