5. How would you implement optimistic UI updates for POST/DELETE using RTK Query or Thunk?
Implementing Optimistic UI Updates in RTK Query and Thunks
Optimistic UI updates make the application feel faster by updating the UI immediately before the server confirms the change. If the request fails, the state is rolled back to its previous value. Both RTK Query and createAsyncThunk can handle optimistic updates, though RTK Query simplifies the process through its built-in onQueryStarted lifecycle method.
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1. Use onQueryStarted: Inside a mutation endpoint, perform temporary cache updates before the server response.
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2. Update Query Data: Use
api.util.updateQueryData()to modify the cache for the relevant query. - 3
3. Rollback on Error: Use the
patchResult.undo()method if the mutation fails to revert the UI state.
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1. Dispatch an Immediate State Change: Update the local slice before the API call resolves.
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2. Handle Errors Gracefully: Revert to the old state in the
rejectedreducer case if the request fails.
RTK Query is ideal for optimistic updates because it handles cache invalidation and rollback automatically. Thunks are more flexible for custom logic but require manual state management. The choice depends on whether your data flow is cache-based (RTK Query) or business logic–driven (Thunk).
Scenario Questions
0-2 years experience
- 1Imagine you're adding a new comment via a POST request using RTK Query. How would you make the UI show the comment instantly, and what steps would you take to roll back if the server returns an error?
- 2You're implementing a delete button for a todo item with a thunk. Walk me through how you'd optimistically remove the item from the list and handle a failure response.
2-5 years experience
- 1We have a list of posts fetched with RTK Query, and we need to support adding and deleting posts optimistically. How would you structure the cache updates, and what trade‑offs do you consider when choosing between onQueryStarted vs manual dispatches?
- 2During a sprint you notice that after an optimistic delete, the UI sometimes shows stale data when another component re‑fetches the list. What could be causing this, and how would you debug/fix it?
- 3If the backend occasionally returns a 409 conflict on a POST, how would you adjust your optimistic update logic to keep the UI consistent?
5-8 years experience
- 1Design an optimistic update strategy for a high‑traffic feed where multiple users can add or delete items concurrently. How would you ensure cache consistency across pages and avoid race conditions?
- 2Explain how you would integrate optimistic updates with RTK Query's tag invalidation system to keep related queries in sync while minimizing unnecessary refetches.
- 3What performance implications arise from storing optimistic patches in the Redux store, and how would you mitigate memory bloat in a large app?
8+ years experience
- 1Our product is migrating from a custom thunk‑based data layer to RTK Query across dozens of services. How would you plan a phased rollout of optimistic UI updates to minimize risk and maintain backward compatibility?
- 2Consider a micro‑frontend architecture where different teams own separate slices of the UI but share a common RTK store. How would you standardize optimistic update patterns to avoid duplicated logic and ensure consistent error handling?
- 3From a long‑term maintenance perspective, what guidelines would you establish for when to use optimistic updates versus eventual consistency, especially in a system with offline support and sync conflicts?
Follow-up Questions
- How would you test that your optimistic update logic works correctly?
- What would you do if the optimistic update caused a UI flicker due to rapid re‑fetches?
- Can you explain how you’d handle multiple concurrent optimistic mutations on the same entity?