TreeSelect: Fixing Search Pagination Issues

by Henrik Larsen 44 views

Hey guys! Today, we're diving deep into a tricky issue we've encountered with the TreeSelectComponent related to search queries and scroll pagination. This component is used in both the kbss-cvut and termit-ui projects, so it’s super important we get this sorted. We've noticed a weird behavior where search requests inherit the scroll pagination offset, leading to unexpected results. Let's break down the problem, see how it manifests, and then explore some potential solutions.

Understanding the Problem

The core issue lies in how the TreeSelectComponent handles pagination when you're scrolling through the list of items and then initiate a search. The component uses infinite scrolling, loading data in chunks of 100 items per page. So, as you scroll, it makes requests like roots?size=100&page=1, roots?size=100&page=2, and so on. This works perfectly fine for browsing.

However, the problem arises when you decide to use the search bar. Instead of resetting the pagination when you perform a search, the component incorrectly continues pagination from the current scroll position.

Let’s walk through an example to make it crystal clear:

  1. Initial Load: You open the component, and it fetches the first page of results: roots?size=100.
  2. Scroll Once: You scroll down, and it loads the next page: roots?size=100&page=1.
  3. Scroll Again: You scroll further, loading the third page: roots?size=100&page=2.
  4. Perform a Search: Now, you type “a” in the search bar. Instead of starting the search from the beginning, the request is sent as terms?searchString=a&size=100&page=3. This is not what we want! We want the search to start from page 0 or ignore pagination altogether.

This behavior leads to missing search results because the component is essentially skipping the initial pages of the search results. It’s like starting a book from chapter 3 instead of chapter 1 – you're going to miss a lot of important stuff!

Why is this happening? It seems the component is not correctly resetting or handling the pagination state when a search is initiated. It's crucial to address this because it directly impacts the usability and accuracy of the search functionality.

Proposed Solutions

Okay, so we know what the problem is. Now, let's talk about how we can fix it. We've brainstormed a few potential solutions, each with its own pros and cons. Let's dive in!

1. Reset Pagination to Page 0 (or Omit Page Parameter) When Initiating a Search

This is perhaps the most straightforward and intuitive solution. The idea here is simple: whenever a user performs a search, we reset the pagination to the beginning. This means that the search request will either start from page=0 or, even better, omit the page parameter entirely.

How it works:

  • Whenever the search input changes (e.g., the user types a new character), we trigger a function that resets the pagination state.
  • The next search request will then be sent without the page parameter or with page=0, ensuring we start from the beginning of the search results.

Pros:

  • Simple to implement: This solution is relatively easy to code and understand.
  • Intuitive behavior: Users expect search results to start from the beginning, so this aligns with their expectations.
  • Efficient for most cases: For most searches, starting from the beginning is the most logical approach.

Cons:

  • Potential performance issues for very large datasets: If the search returns a massive number of results, starting from page 0 might lead to performance bottlenecks. However, this is less likely if we optimize the backend to handle large result sets efficiently.

In summary, resetting the pagination is a solid option that provides a clean and predictable search experience. It’s our first and strongest recommendation.

2. Maintain Two Independent Paginations: One for Infinite Scroll, One for Search Results

This approach involves maintaining two separate pagination states: one for the infinite scrolling of the main list and another specifically for search results. This way, scrolling and searching operate independently without interfering with each other.

How it works:

  • We introduce a separate pagination counter or state variable specifically for search results.
  • When a search is performed, we use this separate pagination state to handle the search result pagination.
  • The infinite scroll pagination remains unaffected by search operations, and vice versa.

Pros:

  • Clean separation of concerns: This approach clearly separates the pagination logic for scrolling and searching, making the code more modular and maintainable.
  • Avoids conflicts: By having separate states, we completely eliminate the issue of search inheriting the scroll pagination offset.
  • Potentially more flexible: This allows for more fine-grained control over pagination behavior in the future if needed.

Cons:

  • More complex implementation: This solution is more complex to implement than simply resetting pagination, as it requires managing two separate states.
  • Increased memory usage: Maintaining two pagination states might consume slightly more memory, although this is unlikely to be a significant issue in most cases.

In summary, maintaining separate paginations offers a robust solution by isolating the scrolling and search pagination. It's a good option if we anticipate needing more complex pagination behaviors in the future.

3. Ignore Pagination for Search Requests Entirely

This solution proposes that we completely ignore pagination for search requests. Instead of paginating the search results, we would fetch all matching results in a single request. This simplifies the logic but might have performance implications for very large datasets.

How it works:

  • When a search is performed, the request does not include any pagination parameters (e.g., page and size).
  • The backend returns all matching results in a single response.
  • The component then handles the display of these results, potentially using its own internal mechanisms for pagination or virtualization.

Pros:

  • Simplest logic: This is the simplest solution in terms of code complexity, as we avoid dealing with pagination during search requests.
  • Guaranteed to find all results: Since we fetch all results at once, we ensure that no results are missed due to pagination issues.

Cons:

  • Performance issues for large datasets: Fetching all results at once can be inefficient and might lead to performance problems if the dataset is very large or the search query returns a significant number of matches.
  • Increased server load: The server might experience increased load due to handling larger requests.
  • Potential for UI freezing: Rendering a large number of results at once can potentially freeze the UI, leading to a poor user experience.

In summary, ignoring pagination for search requests is a simple solution but comes with significant performance risks for large datasets. We should only consider this option if we can guarantee that the search results will typically be small or if we implement robust client-side pagination.

Conclusion

So, there you have it! We've identified a tricky issue in the TreeSelectComponent where search pagination inherits the scroll offset, and we've explored three potential solutions: resetting pagination, maintaining separate paginations, and ignoring pagination for search.

Our recommendation is to start with the first solution: resetting pagination to page 0 (or omitting the page parameter). It's the most intuitive and straightforward approach. If we encounter performance issues with very large datasets, we can then consider the second solution, maintaining separate paginations.

We hope this breakdown was helpful, guys! Addressing this issue will greatly improve the usability and reliability of the TreeSelectComponent. Let's get this fixed!