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A successful mutation changes data on the server; it does not automatically refresh every value your interface displays. The screen may still be rendering old component state, a stale query-cache entry, or a GraphQL list that was never updated. Confirm what the mutation returned, then trace the displayed value to the state or cache the component actually reads.
Why can the UI show old data after a successful mutation?
Your application can hold several representations of the same record. A mutation may persist a change on the server while a component continues to render a local state value, a query result, or a cached list that has not been reconciled. The fix depends on which representation feeds the screen; updating one store does not necessarily update another.
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Start by checking the mutation result and the network response. Verify that the request succeeded and that the returned object includes the field values you expect. A success toast or HTTP status alone does not establish that the response contains the updated data. Apollo Client also documents cases where a mutation result can be undefined, including certain error-policy and network-error cases.
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How do you update React local state after a mutation?
If the UI renders React state, changing an object or array in place is not enough. React’s documentation says to treat objects in state as immutable: create a replacement value and pass it to the setter. Without the setter, React has no signal that the state changed. See React’s guide to updating objects in state.
For an object, use a functional update that preserves fields you did not change:
setItem(previous => ({ ...previous, name: nextName }));For an array, create a new array and replace the matching item rather than assigning into the existing array or item:
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setItems(previous => previous.map(item => item.id === updated.id ? updated : item));For nested data, create a new object at each level along the changed path. Replacing only the outer object while mutating a nested object in place still risks leaving the state update unclear and can affect other references to that nested value.
How do you refresh data after a TanStack Query mutation?
First compare the query key used by the rendered query with the key you invalidate or update. A key mismatch means the intended query may remain unchanged. TanStack Query lets you invalidate matching keys by prefix or target an exact key. Its query invalidation guide explains that invalidation marks matching data stale, overriding its staleTime, and refetches matching queries that are actively rendered in the background.
Invalidate when the mutation affects lists, derived results, or data the response does not fully describe. For example, if a record’s new status can change which filtered list contains it, refetching the relevant query is often safer than editing one cached list and leaving another stale.
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onSuccess: () => queryClient.invalidateQueries({ queryKey: ['items'] })Use the narrowest key that covers the affected view. A broader prefix can match multiple related queries; use exact: true only when the query key should match exactly.
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If the mutation response contains the complete updated entity and you know which cached detail entry the component reads, write that response to the cache with setQueryData. This can update the screen without an extra fetch. TanStack Query’s v4 guide to updates from mutation responses shows this pattern for a returned object and a corresponding detail key.
onSuccess: updatedItem => {
queryClient.setQueryData(['item', { id: updatedItem.id }], updatedItem);
}Adapt the key and object shape to your application and the TanStack Query version you use. Cache updates must be immutable: construct a replacement value instead of modifying an object returned by getQueryData in place. If the response is incomplete, or the mutation changes related lists, invalidate those queries so the server can provide authoritative results.
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Why might an Apollo mutation update a record but not a list?
Apollo Client can normalize a returned entity into its cache without automatically adding that entity to every watched list. A detail view may show the changed record while a list query still has its previous membership or ordering. Apollo’s mutation documentation describes the choice between refetching affected queries and directly updating the cache.
- Refetch when the affected query is known: use
refetchQuerieswhen an additional network request is acceptable and you want the server to recalculate the query result. - Update the cache when the result is sufficient: use the mutation’s
updateflow or an appropriate cache operation to update the entity or list without a follow-up request.
Before inserting an entity into a cached list, check the query’s variables and filters. An item that belongs in one list may not belong in another filtered or sorted view. Direct cache editing avoids a request, but it also puts responsibility for correct list membership on the client.
Should you use an optimistic update?
Optimistic UI is about showing an expected result before the server confirms it; it is distinct from reconciling confirmed server data after success. TanStack Query documents two approaches: render mutation variables while the mutation is pending, or optimistically change cached data in onMutate. Rendering pending variables can avoid changing shared cached data. Cache-based optimism needs a recovery plan.
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For an optimistic cache update, the usual sequence is to cancel outgoing refetches, snapshot the current data, apply an immutable change, restore the snapshot if the mutation fails, and invalidate affected queries after settlement. This gives the interface a fast provisional response while ensuring failure does not leave the optimistic value in place. See TanStack Query’s optimistic updates guide.
What should you check if the screen still does not change?
- Mutation result: confirm the request completed and the response includes the expected updated fields.
- Render source: identify the exact state variable or query result used by the component.
- State replacement: for React local state, call the setter with a new object or array rather than mutating the existing value.
- Query key: verify that the invalidation or cache update targets the key and variables used by the rendered query.
- List membership: for Apollo or derived query data, check whether the mutation changed which records belong in the list, not just fields on one entity.
- Callback and failure path: ensure the cache update or invalidation runs in the intended success or settlement callback, and that pending and error states reflect the actual result.
The exact cause depends on your component and data flow. The reliable diagnostic is to follow the value from the server response into the particular state or cache entry that the screen renders.
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